phd thesis in actuarial science

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Statistics and Actuarial Sciences Theses and Dissertations

This collection contains theses and dissertations from the Department of Statistics and Actuarial Sciences, collected from the Scholarship@Western Electronic Thesis and Dissertation Repository

Theses/Dissertations from 2023 2023

Parameter Estimation for Normally Distributed Grouped Data and Clustering Single-Cell RNA Sequencing Data via the Expectation-Maximization Algorithm , Zahra Aghahosseinalishirazi

Statistical modelling and applications for sustainable-development goals , Yiyang Chen

Multivariate Regression Analysis for Data with Measurement Error, Missing Values, and/or Sparsity Structures , Jingyu Cui

Addressing the Impact of Time-Dependent Social Groupings on Animal Survival and Recapture Rates in Mark-Recapture Studies , Alexandru M. Draghici

Generalized Poisson random variables: Their distributional properties and actuarial applications , Pouya Faroughi

Optimizing Dynamic Treatment Regimes with Q-Learning: Complications due to Error-Prone Data and Applications to COVID-19 Data , Yasin Khadem Charvadeh

Estimating the spatial correlation structure of measurement error in functional magnetic resonance imaging (fMRI) to improve multivariate inference , Lingling Lin

Cyber risk valuation via a hidden Markov-modulated modelling approach , Yuying Li

Advances in Copula Estimation and Distribution Theory , Yishan Zang

Modelling long-term security returns , XINGHAN ZHU

Theses/Dissertations from 2022 2022

Efficiency Improvements in the Least-Squares Monte Carlo Algorithm , François-Michel Boire

Portfolio Optimization Analysis in the Family of 4/2 Stochastic Volatility Models , Yuyang Cheng

Early-Warning Alert Systems for Financial-Instability Detection: An HMM-Driven Approach , Xing Gu

The Analysis of Mark-recapture Data with Individual Heterogeneity via the H-likelihood , Han-na Kim

Statistical Applications to the Management of Intensive Care and Step-down Units , Yawo Mamoua Kobara

Regression-based Methods for Dynamic Treatment Regimes with Mismeasured Covariates or Misclassified Response , Dan Liu

Statistical Roles of the G-expectation Framework in Model Uncertainty: the Semi-G-structure as a Stepping Stone , Yifan Li

Risk theory: data-driven models , Yang Miao

New Developments on the Estimability and the Estimation of Phase-Type Actuarial Models , Cong Nie

Copulas, maximal dependence, and anomaly detection in bi-variate time series , Ning Sun

Interdisciplinary Knowledge Exchange in Statistics with Applications in Fire Science and Statistical Education , Chelsea Uggenti

On the Geometry of Multi-Affine Polynomials , Junquan Xiao

Understanding Deep Learning with Noisy Labels , Li Yi

An Analysis of Weighted Least Squares Monte Carlo , Xiaotian Zhu

Application Of A Polynomial Affine Method In Dynamic Portfolio Choice , Yichen Zhu

Theses/Dissertations from 2021 2021

A class of phase-type ageing models and their lifetime distributions , Boquan Cheng

Application of Stochastic Control to Portfolio Optimization and Energy Finance , Junhe Chen

Making Sense of Noisy Data: Theory and Applications , Lingzhi Chen

The Mean-Reverting 4/2 Stochastic Volatility Model: Properties And Financial Applications , Zhenxian Gong

Compound Sums, Their Distributions, and Actuarial Pricing , Ang Li

On the Estimation of Heston-Nandi GARCH Using Returns and/or Options: A Simulation-based Approach , Xize Ye

Theses/Dissertations from 2020 2020

A Treatise of PD-LGD Correlation Modelling , Wisdom S. Avusuglo WSA

Visualization and Joint Analysis of Monitored Multivariate Spatio-Temporal Data with Applications to Forest Fire Modelling and Sports Analytics , Devan Becker

Generalized 4/2 Factor Model , Yuyang Cheng

Renewable-energy resources, economic growth and their causal link , Yiyang Chen

Some Insurance Options on Stochastic Drawdowns , Filip Dikic

Extensions of Classification Method Based on Quantiles , Yuanhao Lai

Point Process Modelling of Objects in the Star Formation Complexes of the M33 Galaxy , Dayi Li

Classification-based method for estimating dynamic treatment regimes , Junwei Shen

Statistical Methods with a Focus on Joint Outcome Modeling and on Methods for Fire Science , Da Zhong Xi

Ranking comments: An Entropy-based Method with Word Embedding Clustering , Yuyang Zhang

Theses/Dissertations from 2019 2019

A computationally efficient methodology in pricing a guaranteed minimum accumulation benefit , Yiming Huang

Some Recent Developments on Pareto-optimal Reinsurance , Wenjun Jiang

Classification with Measurement Error in Covariates Or Response, with Application to Prostate Cancer Imaging Study , Kexin Luo

Exploring the Estimability of Mark-Recapture Models with Individual, Time-Varying Covariates using the Scaled Logit Link Function , Jiaqi Mu

Split credibility: A two-dimensional semi-linear credibility model , Jingbing Qiu

Advances in Moment-Based Distributional Methodologies , Yishan Zang

How to Rank Answers in Text Mining , Guandong Zhang

On the Sparre-Andersen Risk Models , Ruixi Zhang

Valuation and Risk Management of Some Longevity and P&C Insurance Products , Yixing Zhao

Theses/Dissertations from 2018 2018

Modelling the Common Risk among Equities Using a New Time Series Model , Jingjia Chu

Stochastic modelling of implied correlation index and herd behavior index. Evidence, properties and pricing. , Lin Fang

Optimal Trading of a Storable Commodity via Forward Markets , Behzad Ghafouri

Statistical Modeling of CO2 Flux Data , Fang He

Advances in the Modeling of Heavy-tailed Distributions , Sang Jin Kang

The Statistical Exploration in the $G$-expectation Framework: The Pseudo Simulation and Estimation of Variance Uncertainty , Yifan Li

Statistical tools for assessment of spatial properties of mutations observed under the microarray platform , Bin Luo

Valuation of Multiple Exercise Option Using a Modified Longstaff and Schwartz Approach , Rahim Mohammadhasani Khorasany

Statistical Applications in Healthcare Systems , Maryam Mojalal

Exact Box-Cox Analysis , Samira Soleymani

Anisotropic kernel smoothing for change-point data with an analysis of fire spread rate variability , John Ronald James Thompson

Some applications of higher-order hidden Markov models in the exotic commodity markets , Heng Xiong

Advances in Semi-Nonparametric Density Estimation and Shrinkage Regression , Hossein Zareamoghaddam

Analysis Challenges for High Dimensional Data , Bangxin Zhao

Theses/Dissertations from 2017 2017

Properties of k-isotropic functions , Tianpei Jiang

Data-Adaptive Kernel Support Vector Machine , Xin Liu

Annuity Product Valuation and Risk Measurement under Correlated Financial and Longevity Risks , Soohong Park

Statistical Modelling, Optimal Strategies and Decisions in Two-Period Economies , Jiang Wu

Theses/Dissertations from 2016 2016

Joint Models for Spatial and Spatio-Temporal Point Processes , Alisha Albert-Green

Applications of Credit Scoring Models , Mimi Mei Ling Chong

Joint Analysis of Zero-heavy Longitudinal Outcomes: Models and Comparison of Study Designs , Erin R. Lundy

Data Smoothing Techniques: Historical and Modern , Lori L. Murray

Joint Modelling in Liver Transplantation , Elizabeth M. Renouf

Probability Models for Health Care Operations with Application to Emergency Medicine , Azaz Bin Sharif

Advances in Portmanteau Diagnostic Tests , Jinkun Xiao

Actuarial Modelling with Mixtures of Markov Chains , Yuzhou Zhang

Theses/Dissertations from 2015 2015

Healthy And Unhealthy Statistics: Examining The Impact Of Erroneous Statistical Analyses In Health-Related Research , Britney Allen

Recent Advances in Accumulating Priority Queues , Na Li

Quantitative Techniques for Spread Trading in Commodity Markets , Mir Hashem Moosavi Avonleghi

A Novel Method for Assessing Co-monotonicity: an Interplay between Mathematics and Statistics with Applications , Danang T. Qoyyimi

Completely monotone and Bernstein functions with convexity properties on their measures , Shen Shan

Online Nonparametric Estimation of Stochastic Differential Equations , Xin Wang

On the Dual Risk Models , Chen Yang

Theses/Dissertations from 2014 2014

Statistical methods for the analysis of RNA sequencing data , Man-Kee Maggie Chu

Valuation and Risk Measurement of Guaranteed Annuity Options under Stochastic Environment , Huan Gao

Statistical Applications in Wildfire Management and Prediction , Lengyi Han

Computing and Approximation Methods for the Distribution of Multivariate Aggregate Claims , Tao Jin

The Doubly Adaptive LASSO Methods for Time Series Analysis , Zi Zhen Liu

Risk models with dependence and perturbation , Zhong Li

Censored Time Series Analysis , Nagham Muslim Mohammad

A Spatial Analysis of Forest Fire Survival and a Marked Cluster Process for Simulating Fire Load , Amy A. Morin

Estimation of Hidden Markov Models and Their Applications in Finance , Anton Tenyakov

Perfect and Nearly Perfect Sampling of Work-conserving Queues , Yaofei Xiong

Decision Theory Based Models in Insurance and Beyond , Raymond Ye Zhang

Theses/Dissertations from 2013 2013

Seasonal Decomposition for Geographical Time Series using Nonparametric Regression , Hyukjun Gweon

Stochastic simulation and spatial statistics of large datasets using parallel computing , Jonathan SW Lee

Flexible Partially Linear Single Index Regression Models for Multivariate Survival Data , Na Lei

Joint outcome modeling using shared frailties with application to temporal streamflow data , Lihua Li

Asymptotic Theory for GARCH-in-mean Models , Weiwei Liu

Polynomially Adjusted Saddlepoint Density Approximations , Susan Zhe Sheng

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COLLEGE OF LIBERAL ARTS AND SCIENCES

Department of Mathematics

• Ph.D. in Mathematics with Thesis in Actuarial Science
• General Information
• Financial Aid
• Answers to FAQ
• Ph.D. in Mathematics
• M.S. in Mathematics
• M.S. in Actuarial Science
• M.S. in Applied Financial Mathematics
• M.S. in Applied Financial Mathematics – Actuarial Science
• Course Schedule
• Preliminary Exams

Introduction

• The University of Connecticut’s actuarial program is a vibrant program for undergraduate, master’s students and  PhD students majoring in Actuarial Science.
• It is one of the leading actuarial science programs in the country and the only one of its kind in New England.
• For PhD students, UConn offers a unique blend of rigorous theoretical framework with practical grounding in problems of intense emerging interest in the marketplace.

• Our faculty also blends academic and practical industry experience. More on our program is available on its website .
• While emphasizing research that will benefit practicing actuaries, the PhD program prepares for an academic career in research and teaching.   It is not intended to prepare students to become practicing actuaries. Those intending a career in actuarial practice should pursue the M.S degree.

Overview of Graduation Requirements

To graduate with a PhD in Mathematics, a student must satisfy all of the following requirements:

• 45 credits, including 15 doctoral dissertation research credits/GRAD 6950
• If you have a Master’s degree in mathematics at UConn, then 30 credits are required, including 15 doctoral dissertation research credits.
• Pass at least one prelim exam after each semester for the first three semesters of their graduate study.
• Finish all prelim exam requirements by the beginning of the spring semester in their second year.
• Finish all core course requirements by the end of their second year of graduate study,
• Choose a thesis advisor no later than the end of the fall semester of the third year.
• Form your advisory committee :  Major Advisor and at least two Associate Advisors or Co-Major Advisors and at least one Associate Advisor.
• Meant to further the student’s education, scholarship and professional development.
• Material should be in the broad area in which the student intends to write a dissertation, but should not focus on the actual thesis research.  Students present and answer questions about the material they have studied.
• The exam is normally taken at the end of the third year or beginning of the fourth year.
• Submit Dissertation Proposal
• Submit Plan of Study
• Apply for Graduation in Student Admin by the fourth week of the final semester.
• Dissertation Specifications under Dissertation Information
• Thesis templates (for LaTex) are available on our Thesis Formatting page
• Submit Approval Page – Step 7
• Complete Survey of Earned Doctorates – Step 7
• Add Diploma Address in Student Admin and Diploma Info.

Preliminary Examination and Core Course Requirements

Actuarial Science:

• Math 5160/Probability Theory and Stochastic Processes I
• Math 5639/Actuarial Loss Models
• Math 5111/Measure and Integration
• Math 5120/Complex Function Theory
• Math 5210/Abstract Algebra
• Math 5310/Introduction to Geometry and Topology I
• Math 5410/Introduction to Applied Mathematics I
• Math 5510/Numerical Analysis and Approximation Theory I
• Math 5161/Probability Theory and Stochastic Processes II
• Math 5210/Abstract Algebra I
• Math 5211/Abstract Algebra II
• Math 5360/Differential Geometry
• Math 5440/Partial Differential Equations
• Math 5520/Finite Element Solution Methods I

Past Prelim Exams

College of Liberal Arts & Sciences

Program of Actuarial and Risk Management Sciences

Phd in mathematics – concentration in actuarial science and risk analytics.

This PhD concentration is intended for students with strong quantitative skills who want to acquire advanced analytical tools for academic careers and research and development careers  in insurance, consulting, investment, pension, healthcare, banking and financial services .

The University of Illinois is an ideal place for education and research in actuarial, financial and risk management, due to its well-established system of interdisciplinary collaborations among various units. Highlights of the University’s achievements in these areas can be found  here . Based in the renowned Department of Mathematics, this program offers a unique blend of a world-class rigorous mathematical education with practical research and professional training in actuarial science, quantitative finance and risk analytics. Read more at our  poster for graduate studies in actuarial science and risk management .

PhD candidates cover most of the material for professional exams, and build on that foundation to receive in-depth education on modern techniques and challenges in the financial, actuarial and risk management professions through coursework, seminars, internships and research. Due to the interdisciplinary nature of actuarial and financial research, PhD candidates are encouraged to broaden their knowledge by taking courses in statistics, finance, insurance, risk management, data analytics, etc.

The Department of Mathematics offers a unique multi-year internship program where PhD candidates are encouraged and supported to receive internship experience in summer breaks during their PhD studies. More information can be found  here . There are also internship opportunities on campus at the  University of Illinois Research Park . Students are also exposed regularly to cutting-edge research development in industry and academia by attending and presenting at the  Actuarial Science and Financial Mathematics Seminar , where a wide range of prominent researchers are invited to speak and visit. In addition, students can participate in the seminar series on  Mathematical Finance, Risk and Uncertainty , jointly organized with the Department of Industrial and Enterprise Systems Engineering.

Our program offers opportunities for PhD candidates to work in a wide range of research areas, including stochastic analysis in actuarial and financial modeling, quantitative risk management of equity-linked insurance, pension and social security, industry solvency assessment, collective risk theory, Monte Carlo simulations, and more. The  Illinois Risk Lab  also provides a channel for practical research to address emerging problems from industrial partners and professional organizations.

Financial support is offered for up to six years to every student admitted to our PhD program, in the form of teaching assistantships, research assistantships and corporate-sponsored fellowships. We also provide full reimbursement of exam fees for those who choose to take professional exams. To help students develop communication and networking skills, we also provide financial support for PhD candidate to travel to research summer schools and conferences in related areas.

Admissions Requirements

Students with a Bachelor’s degree in any quantitative field can apply directly to the PhD program. Applicants are expected to demonstrate competence in real analysis, linear algebra, and probability and statistics, either through undergraduate coursework or by means of Graduate Record Examination (GRE) mathematics subject test.

Complete information regarding graduation requirements can be found in the  Guide for Graduate Students in Mathematics . The following list only serves as a summary for prospective students.

PhD candidates in this concentration are required to complete the core courses: MATH 540 (Real Analysis) MATH 561 (Theory of Probability I) MATH 563 (Risk Modeling and Analysis) STAT 510 (Mathematical Statistics I) One additional course from a list of approved core courses for all PhD students.

PhD candidates in this concentration must also demonstrate competence in three additional supporting courses: MATH 564 (Applied Stochastic Processes) STAT 425 (Applied Regression and Design) FIN 591 (Theory of Finance)

and in two of the following actuarial graduate courses: MATH 565 (Actuarial Models for Life Contingencies) MATH 567 (Actuarial Models for Financial Economics) MATH 568 (Actuarial Loss Models)

Although not required, many PhD candidates in the Actuarial Science and Risk Analytics Concentration take elective courses in functional analysis, partial differential equations, linear and nonlinear programming, multivariate analysis, statistical computing, macro and micro economics, portfolio management, predictive modeling, machine learning.

How to Apply

The application process for this concentration is the same as the regular Mathematics PhD program. Detailed instruction as well as general requirements can be found  here . Candidates should clearly identify the Actuarial Science and Risk Analytics Concentration on the application form, and in their personal statement.

Frequently Asked Questions

If I want to become a practicing actuary, should I consider PhD education in Actuarial Science?

The actuarial profession in North America highly values professional credentials obtained through passing professional exams with credentialing bodies such as the Society of Actuaries and Casualty Actuarial Society. A PhD education in Actuarial Science is not a necessary component for a career path as an actuary. Students who are interested in career paths in traditional actuarial roles should pursue our MS program in Actuarial Science. The PhD concentration prepares students for academic careers and research and development offices/departments in the insurance and financial service industries. For example, a graduate may find a tenure-system position in a university, work as a quantitative reinsurance analyst, a catastrophe modeling analyst, a quantitative strategy researcher in a proprietary trading firm, and so on.

What qualifications are you looking for in admissions?

A typical PhD applicant should have a bachelor’s degree or its equivalent in a quantitative field, including but not limited to pure mathematics, applied mathematics, statistics, engineering, quantitative finance, physics, etc. Students should take the GRE General test.

How much do GRE scores get weighted into the application of a prospective student? What other factors weigh the most in an application?

We consider the whole application to find students with sufficient preparation and motivation to succeed in our program. Applicants typically perform strongly on the GRE General exam (80th percentile and above on the quantitative portion, and we like to see good scores on the other sections too). Scores on the GRE Mathematics subject exam (if taken) vary quite widely. Coursework relevant to actuarial science and risk analytics is valuable. 

The transcripts from your bachelor’s and master’s institutions are important. We pay close attention to courses and grades. If you come in with an actuarial or financial mathematics background, we do consider your track record of passing professional exams. However, students in this concentration also come from other quantitative fields.

What funding is available to students ?

All admitted students are offered a full tuition waiver, and a teaching assistantship (the stipend is $20,000 for the academic year; most students get some summer funding too). The funding offer runs for 5 or 6 years, depending on your level of preparation. Fellowship and RA support is available to some continuing students who perform strongly in the program.

How do the requirements for those pursuing the Actuarial Science emphasis differ from those pursuing other fields of study?

Notably, students in the Actuarial Science and Risk Analytics Concentration are not required to take Math 500 Abstract Algebra. Instead, they take Stat 510 Mathematical Statistics I. The full requirements for students in the Concentration are listed  here .

What should be my focus to prepare for this program beyond admissions?

Take as much undergraduate real analysis as possible (called “advanced calculus” at some universities), and tackle the hardest problems you can get your hands on. Learn metric space topology, with normed vector spaces being an important example. Get familiar with spherical coordinates, the divergence theorem (Gauss theorem), and  Green’s first and second identities .

Real analysis lays the foundation for probability, stochastic processes, and differential equations, at the graduate level. If you are strong in real analysis, then you can learn and pass the material in the first year comprehensive courses in a PhD program like ours.

Statistics and Actuarial Science

• Graduate Theses
• Statistics Workshop
• Actuarial Science
• Data Science
• Course Information
• Getting Involved
• Accreditation
• EAL and Other Resources
• Actuarial Science Info Session
• Statistics Admission
• Actuarial Science Admission
• Data Science Admission
• Moving to SFU
• Program Information
• Teaching Assistant Positions
• Intranet Grad Students
• Statistics M.Sc.
• Statistics Ph.D.
• Actuarial Science M.Sc.
• Tuition and Financial Support
• Academic Resources
• M.Sc. and Ph.D. Defences
• Statistical Consulting
• Graduate Students
• News and Events

Graduate Theses 2015-2019

Statistics and Actuarial Science

Graduate theses.

• Statistics Workshop
• Actuarial Science
• Data Science
• Course Information
• Getting Involved
• Accreditation
• EAL and Other Resources
• Actuarial Science Info Session
• Statistics Admission
• Actuarial Science Admission
• Data Science Admission
• Moving to SFU
• Program Information
• Teaching Assistant Positions
• Intranet Grad Students
• Statistics M.Sc.
• Statistics Ph.D.
• Actuarial Science M.Sc.
• Tuition and Financial Support
• Academic Resources
• M.Sc. and Ph.D. Defences
• Statistical Consulting
• Graduate Students
• News and Events

Below is a list of the theses produced by graduate students in the Department of Statistics and Actuarial Science.

Projects and Theses From Previous Years

2015 - 2019 2010 - 2014 2005 - 2009 2000 - 2004 1990's 1980's and prior

PhD in Actuarial Studies

The PhD program in Actuarial Studies at the Research School of Finance, Actuarial Studies and Statistics (RSFAS) equips graduates with the necessary skills to undertake independent research and develop knowledge and expertise in a specialised research topic within the field of actuarial studies.

The program is focused on developing candidates for careers in academia, government or industry. Positions in government or industry may include researcher or analyst in the banking, insurance, data analytics, actuarial and management consulting or financial sectors; and researcher or policy adviser at institutions, including central banks, bank regulators, international organisations such as the World Bank, IMF, OECD and ADB, and government departments such as Treasury, Finance, Health and Education.

CRICOS #: 048345A

Duration: 2 to 4 years full time (4 to 8 years part time)

Before you submit an application for entry to the program, you should:

• ensure you meet the admission requirements outlined below
• identify potential supervisors – that is, one or two actuarial studies or statistics academics at ANU who conduct research in your area of interest.

You can find information on researchers and their research areas in the  ANU researchers database , and on the  RSFAS Actuarial Studies faculty  and  RSFAS Statistics faculty  pages.

While other ANU schools may recommend contacting potential supervisors before submitting an application,  this is not required  for entry into RSFAS’s PhD programs. Instead, you only need to list the name(s) of potential supervisors in your online application form.

Potential supervisors cannot guarantee entry into the PhD program. Admission will depend on the strength of your application relative to others in the pool.

After you’ve completed the steps above, you can proceed with an  online application .

Application deadlines

The first semester of the ANU academic year starts in February, and the second semester starts in July. While all applications for first semester entry must be submitted  before 31 October,  international applicants wishing to be considered for an  ANU scholarship  should submit their applications  before   31 August .

To be considered for a scholarship, your application must be accompanied by all the supporting documents listed below, including the referee reports. Request for referee reports are triggered and sent to your nominated referees at the time of submission of program application. It is thus important that you submit your application in advance (2-3 weeks) to allow time for your referees to provide their reports prior to the scholarship deadline.

If you’re currently completing an academic degree and haven’t yet received your final results and transcript, you should still submit all available documents before the deadline, and forward remaining results once you receive them. We won’t make a final decision on your application until we’ve received all the required documents.

The admission requirements for the PhD program in Actuarial Studies reflect the advanced knowledge that candidates will need to undertake the coursework component of the degree, and the research experience and skills needed to successfully undertake and complete the research thesis.

The minimum qualification requirement for admission to the PhD program in Actuarial Studies is:

• an Australian Bachelor degree (or equivalent) with First Class Honours or Second Class Honours Division A in actuarial studies (or a related discipline), or
• another qualification (e.g. a Master degree) with a substantial research thesis component that the RSFAS HDR (higher degree by research) committee is satisfied is equivalent or superior to a degree mentioned in (a), or
• a combination of qualifications and professional experience that the RSFAS HDR committee is satisfied is equivalent or superior to a degree mentioned in (a).

Admission to the PhD program in Actuarial Studies is competitive and we can only admit a limited number of applicants each year. Meeting the minimum entry requirements does not guarantee you a place in the program.

If you don’t have sufficient research experience for entry into the PhD program, you might consider applying to the MPhil program . If you’d like to consider this pathway, contact the RSFAS HDR convenor for more information.

English language requirements

All applicants must satisfy the University’s  English language admission requirements . An international applicant who is not a native English speaker may satisfy these requirements by submitting evidence of an  IELTS  overall score of at least 6.5, and with no component less than 6.0, or a paper-based  TOEFL  score of at least 570, with at least 4.5 in the essay component.

Application and supporting documentation

You must submit your application online via the  ANU Application Manager .

In addition to the standard information required in the online application, you must submit the following supporting documents as part of your application:

• a one-page statement of purpose outlining your motivation to undertake a PhD in Actuarial Studies at ANU
• a research proposal – see details below, as well as these guidelines on how to  prepare a persuasive research proposal
• copies of written research work, e.g. honours or Master thesis, research project or published works
• official  TOEFL  or  IELTS  results (where applicable) to demonstrate that you satisfy the University’s  English language requirements .

Research proposal

The online application requires you to submit a research proposal. The proposal should set out an original research idea, provide an introduction or background to your research idea, clearly set out the research objectives, data and methods you expect to use, and explain why the research is important and the contribution it will make to the discipline. Among other things, the research proposal will require you to demonstrate an understanding of the key literature in your chosen topic area. As a guide, you should aim for between 1,500 and 2,000 words, including a list of key references.

The RSFAS HDR committee uses the research proposal as an indicator to assess the quality and originality of your ideas and your skills in critical thinking. Note that the research proposal does not restrict you to this field of study should you be admitted to the PhD program.

Offers of admission

The RSFAS HDR committee will review all complete applications submitted by the relevant deadline.

If your application is short-listed, you may be required to attend an interview (face to face or online).

We may send you an offer of admission if you satisfy the eligibility criteria and your area of interest matches those of RSFAS academics with supervisory capacity. However, since admission is competitive and supervisory capacity is limited, we won’t send any offers of admission until  after the relevant application deadline , irrespective of the date when you submit your application.

The PhD program in Actuarial Studies consists of two components –  coursework  and  research .

Candidates undertake the research component after successfully completing the required coursework.

PhD coursework component

PhD candidates may be required to complete up to six semester-length courses during the first year of the program. Required coursework must be completed to a satisfactory level for candidates to progress to the research component. Courses may be chosen from a wide range of graduate-level courses in actuarial studies, statistics, finance, or suitable advanced courses from other disciplines. The specific coursework requirements will depend on each candidate’s background, and the courses will be chosen in consultation with the HDR convenor and the chair of the candidate’s supervisory panel.

PhD research component

Following the successful completion of coursework, PhD candidates undertake specialised research training and independent research.

Research supervisory panel

When a PhD candidate is admitted to the program, a provisional supervisor is appointed. The provisional supervisor has the responsibility of overseeing the candidate’s progress until a supervisory panel is chosen. During the first year, it is important that PhD candidates start developing their research topic ideas by consulting with their provisional supervisor and other academic staff within RSFAS.

Either in a candidate’s first year of study, or soon after completion of their coursework, a supervisory panel will be chosen. The role of the panel is to assist, advise, and provide support and encouragement to the candidate for a timely and successful completion of the research thesis. The HDR convenor will determine the composition of the supervisory panel in consultation with the candidate.

RSFAS actuarial studies seminar program

The RSFAS actuarial studies seminar program consists of regular seminars presented by national and international researchers. PhD candidates are expected to attend and actively participate in the seminars throughout their candidature.

Research integrity training

Within three to six months of enrolment, all PhD candidates must complete the  Research Integrity Training  and pass the exam. Completion of this course and exam is a compulsory milestone for all PhD candidates.

Thesis proposal review

During the second year, PhD candidates must submit a thesis proposal for review to their supervisory panel and present it as a seminar to the School. The purpose of the thesis proposal review is to assess the originality, significance, adequacy and achievability of the candidate’s thesis plan.

The proposal includes a description of the research to be undertaken in the thesis, and a summary of the thesis structure and time plan.

Successful completion of the thesis proposal review (as determined by the Delegated Authority following consultation with the HDR convenor and supervisory panel) is required to continue in the PhD program.

Annual progress review

It is University policy that each candidate’s progress be reviewed periodically. In each year of their program, PhD candidates are required to submit an  annual plan and report  as a basis for periodic progress review. This document provides details on work completed by the candidate since the previous review, current progress, and any problems that may impact their research. It also outlines the coursework and research the candidate intends to undertake in the following 12 months.

Oral presentation

In their final year, candidates are required to give a final  oral presentation  on their research, usually three months before submitting their thesis.

Read more about  research candidate milestones .

Thesis submission and examination

The culmination of the PhD in Actuarial Studies is a written thesis which, upon completion, is submitted for examination. The thesis is examined by examiners who are experts in the relevant field.

For more information on the process, visit our page on  submitting a thesis .

For information about scholarships available to HDR candidates, visit our page on  scholarships and fees .

Read details of some of our alumni’s recent  job placements .

See our list of current  Actuarial Studies PhD students .

Course Catalog

Mathematics: actuarial science & risk analytics, phd.

for the Doctor of Philosophy in Mathematics, Actuarial Science and Risk Analytics Concentration

The Concentration attracts students with strong interest in financial risk analytics and actuarial applications of mathematics, and equips them with advanced analytical tools for professional and academic careers. Students in the Concentration complete coursework or professional exams in Probability, Risk Modeling and Analysis, Mathematical Statistics, Theory of Finance, and Actuarial Models for Life Contingencies or Financial Economics.

  for the Doctor of Philosophy in Mathematics, Actuarial Science and Risk Analytics Concentration

Students working toward a Ph.D. degree usually require four to six years to complete the requirements. Each student must pass the comprehensive examinations/courses and the preliminary examination (testing the student's ability to begin or continue research in a chosen field). Students must also write and defend a research thesis in their field of mathematics.

For additional details and requirements refer to the department's  Guide to Graduate Studies  and the  Graduate College Handbook . 

Requirements

Other requirements.

Graduate Degree Programs in Mathematics

• Actuarial Science, MS
• Applied Mathematics, MS
• Mathematics, MS
• Actuarial Science & Risk Analytics
• Computational Science and Engineering

Mathematics Department Department Chair: Vera Hur Director of Graduate Studies: Yuliy Baryshnikov Mathematics Department website Mathematics Department  faculty Actuarial Science faculty research 273 Altgeld Hall, 1409 West Green Street, Urbana, IL 61801   (217) 333-5749 Mathematics email

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Statistics and Actuarial Science

Doctor of philosophy in statistics, earn your phd in statistics.

The Doctor of Philosophy program in statistics requires a minimum of 76 semester hours of graduate credit, including work completed for the MS degree.

The Graduate College requires a minimum grade-point average (GPA) of 3.00 to graduate with a PhD degree; however, the Department of Statistics and Actuarial Science requires a higher GPA of at least 3.40 to earn the PhD in Statistics. This includes all courses used to meet degree requirements plus additional courses that are relevant to a student's program.

PhD students complete required course work, including courses in one of four concentration areas: biostatistics, probability/mathematical statistics, data science, or actuarial science/financial mathematics. They may take course work or seminars in other departments to relate an area of specialization to other fields of knowledge, to acquire the ability to use electronic digital computing equipment, or to learn non-English language skills necessary for reading scientific journals and communicating with scholars in other languages.

Requirements and program planning

Key milestones of the phd program.

Meeting these milestones on time constitutes adequate progress toward the PhD degree.

• Pass the MS final exam before the start of year 2.
• The student will receive an MS degree in Statistics upon fulfilling all of the MS requirements while working towards their PhD.
• Pass the PhD comprehensive exam (prospectus) within 12-18 months (12 months is ideal, 18 months is acceptable) of being admitted to the PhD program.
• Write and defend dissertation within 24-30 months (24 months is ideal, 30 months is acceptable) of passing the prospectus.

Remark. Students who demonstrate a high level of proficiency in their MS exam will receive a letter that not only communicates the exam result, but also provides encouragement to apply for the PhD program.

PhD qualifying procedure

Students enter the PhD program in one of two tracks:

After passing the MS final examination, a student who will choose either biostatistics, probability/mathematical statistics, or data science as the selected concentration area, can request, by notifying the director of graduate studies, to go through the PhD qualifying procedure. Upon this request, the faculty evaluates the student's body of work which includes the MS final examination in statistics, course work, and evidence for research potential. Usually, students need to have achieved A in at least one 7000 level course, have completed at least 1 semester hour of STAT:6990 Readings in Statistics (and is enrolled in a second semester of STAT:6990), and have identified a faculty member who agreed to serve as the student’s PhD advisor to get admitted. This evaluation and assessment results in one of three decisions—the student is officially admitted into the PhD program; the student must reapply to go through the PhD qualifying procedure after accumulating a larger body of work for evaluation; or the student is not admitted into the PhD program.

In exceptional cases, a student may petition to go through the PhD qualifying procedure early, or be admitted to the PhD program directly. However, passing the MS final exam is required before any student can take the PhD comprehensive exam (see the Section below on PhD comprehensive exam/prospectus).

Actuarial science

After successfully passing the MS final examination in actuarial science (in exceptional cases, a student may petition to go through the PhD qualifying procedure early), a student who will choose actuarial science/financial mathematics as the selected concentration area, can request, by notifying the director of graduate studies, to go through the PhD qualifying procedure. Upon this request, the faculty evaluates the student's body of work and assesses the student's potential for research. The body of work will include the MS final examination in actuarial science, professional examinations passed, and course work. This evaluation and assessment results in one of two decisions—the student is officially admitted into the PhD program in the actuarial science/financial mathematics concentration area, or the student is not admitted into the PhD program.

Coursework for different concentration areas

Remark 1. A program that does not conform to the requirements described below but is of high quality may be approved by the department chair.

Remark 2. If a PhD student in statistics registers for 6 semester hours or more (not including STAT:6990 Readings in Statistics and STAT:7990 Reading Research) in a semester, then at least 2 semester hours of these need to be from course(s) offered by the statistics department. (This rule is intended to discourage students from taking too many non-statistical courses, especially after they start doing research for their dissertation. Exceptions to the rule require approval by the advisor and the DGS.)

Actuarial science/financial mathematics concentration area

Actuarial science/financial mathematics emphasizes the theory of actuarial science, finance, and risk management.  It is excellent preparation for academic positions in universities that offer actuarial science programs and for positions in the insurance, pension, and financial industries.

Biostatistics concentration area

Biostatistics emphasizes exposure to various biostatistical methods, such as survival analysis, categorical data analysis, and longitudinal data analysis. It prepares students for consulting and other positions in industry.

Data science concentration area

The data science track emphasizes the theory, methodology, and application of techniques for working with and learning from data. This concentration area prepares students to develop new methods for visualizing and modeling data, managing reproducible data analysis workflows, and collaborating with scientists and other data stakeholders. It is excellent preparation for students interested in academic, industrial, or government positions that involve data visualization, modeling, and analysis.

Probability/Mathematical Statistics Concentration Area

Probability/mathematical statistics emphasizes a broad, solid foundation in techniques and underpinnings of mathematical statistics.  Its focus on breadth and depth is intended to produce well-rounded, knowledgeable scholars.  It is excellent preparation for academic positions in mathematical statistics and industrial or government positions that require broadly trained statisticians with a strong understanding of statistical theory.

Finding an adviser and a research topic

Choosing an adviser is an important decision for a PhD student. Here are some suggestions.

• Talk to professors. Email them, read their websites, talk to them after seminars, interview them as a required activity of alpha seminar (STAT:5090), etc.
• Take Readings in Statistics (STAT:6990) with professors you are interested in working with for your dissertation. Note that having registered for STAT:6990 is required before students can petition to go through the PhD qualifying procedure. Students will conduct readings and work on research-oriented or applied problems that are of mutual interest to both parties. See the description of STAT:6990 details.
• Many students might feel nervous about approaching professors outside the classroom. Remind yourself that by working with a professor, you will be a valuable addition to their research program.
• Talk to other students, attend their presentations, and gain insight into their research topics and advisors.

Attend weekly colloquium, defense of dissertations of other students, etc.

PhD committee

After admission to the PhD program and before taking the PhD comprehensive exam, the candidate chooses a committee of at least four members, which is approved by the advisor. At least three of the faculty members must be University of Iowa tenure-track faculty members. At least two of the faculty members are from the major department (defined as faculty members who hold any appointment in the major department), and are members of the University of Iowa tenure-track faculty.

The department may request the Graduate College dean's permission to replace one of the four committee members by a recognized scholar of professorial rank from another academic institution.

The committee members (including the advisor) of the prospectus and the defense need not be the same. But this is common practice and offers certain advantages.

PhD comprehensive exam (prospectus)

After passing the MS final exam and within 12 months of being admitted to the PhD program, the candidate should present a written and oral prospectus to the committee, which serves as the PhD Comprehensive Exam. The prospectus describes the problems the student is considering for the thesis, an extensive review of relevant background materials, open problems of interest and ideas for solving the problems, and any preliminary results. Failure to successfully complete the prospectus within 18 months of being admitted to the PhD program will jeopardize the continuation of a student's financial support.

Each PhD committee member will sign the examination report as satisfactory, reservations, or unsatisfactory. A vote of "Reservations" should only be used when a faculty member feels that the deficiencies displayed by the student were modest, and can be readily rectified. In the event of a report with two or more votes of "Reservations," the actions required of the student, by the committee, that are necessary to correct the deficiencies must be recorded and submitted to the Graduate College with the examination report form. The statement must specify the time allowed for completion of the aforementioned actions. For instance, if additional course work is required, a list of suitable courses must be presented. If the candidate needs to rewrite their research prospectus, the deficient areas must be identified, etc. If the candidate satisfies the required actions in the specified period of time, the comprehensive exam will be recorded as "Satisfactory" as of that date. If the actions are not satisfied on time, or if the actions are not of sufficient quality, the comprehensive exam will be recorded as "Unsatisfactory" as of that date. The candidate will not be admitted to the PhD final examination of the dissertation until a grade of "Satisfactory" has been recorded for the comprehensive exam.                                         

In the case of a report of unsatisfactory on a comprehensive examination, the committee may grant the candidate permission to attempt a reexamination not sooner than four months after the first examination. The examination may be repeated only once, at the option of the department.

PhD final exam (defense of the dissertation)

Students should plan to defend their dissertation within 24 months of passing the PhD comprehensive exam. Failure to successfully defend the dissertation within 30 months of passing the PhD comprehensive exam or within 5 years of starting the graduate program at the University of Iowa, whichever data comes first, will jeopardize the continuation of a student's financial support.

Application for degree

The student must file an application for an anticipated degree with the Registrar not later than ten weeks after the start of the semester or one week after the start of the summer session in which the degree will be conferred. The student must have the application signed by his or her advisor. Failure to file the Application for Degree by the deadline will result in postponement of graduation to a subsequent session.

Sample schedules

Standard schedule.

A sample plan for students who enter the program with a baccalaureate degree:

• Complete at least 18 semester hours of coursework, including courses needed to prepare for the MS final examination.
• Begin working on identifying a potential advisor. Ideally, talk to the advisor and pick a topic, so literature review and preparation for research in STAT:6990 can start in the summer before year 2 starts.
• Take the MS Final Exam before classes start in the fall. If the student did not pass either the theoretical or the applied part or both parts of the exam in the first attempt, re-take that part of the exam in January.
• Complete at least 18 semester hours of coursework, including one or more 7000 level courses and at least 2 semester hours of STAT:6990.
• Meet all requirements of the MS in Statistics.
• For STAT:6990, give a short oral presentation to a committee of three professors approved by the advisor by early March. (In some years, the Department may establish a committee to oversee all students' 6990 presentations). All students and faculty members are welcome to attend these presentations
• Petition to go through the PhD qualifying procedure once the oral presentation is completed. Get admitted to the PhD program.
• Identify the dissertation topic and the prospectus committee.
• Submit and present the prospectus, which is the same as the PhD Comprehensive exam, within 12 months of admission to the PhD program. Ideally, this is done in Fall.
• Complete most remaining courses.
• Conduct research. Give an annual report to the committee in spring.
• Meet all course requirements.
• Complete and defend dissertation, within 30 months of passing the PhD comp.

Expedited schedule

A sample plan for students who enter the program with Master’s degree, who has received equivalent trainings to all of STAT:5100-1, 5200-1 and 5400 and pass the MS exam the August before year 1 starts:

• Ask the DGS for permission to take the MS Final Examination before classes start in the fall. Pass the exam.
• Complete at least 18 semester hours of coursework, including one or more 7000 level courses.
• Identify a potential research topic and an advisor for research as soon as possible. Register for STAT:6990.
• Give a 15 minute oral presentation to a committee of three professors approved by the advisor in Spring.
• Present the dissertation prospectus in spring, which is the same as the PhD Comprehensive exam, within 12 months of admission to the PhD program.
• Complete more courses.
• Complete most remaining core and concentration-area.
• Conduct research (Stat:7990). Give an annual report to the committee or in public in spring.

Year 4 (and 5 if needed)

• Conduct research. Give an annual report to the committee or in public in spring.
• Complete and defend the dissertation.

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Insurance Economics and Actuarial Analytics

About the program.

The Wisconsin PhD Program in insurance economics and actuarial analytics is offered by the Risk and Insurance Department at the Wisconsin School of Business. We are a nationally recognized Center of Actuarial Excellence . We have received grants to support a variety of industry-related research projects and the introduction of our Technology-Enhanced Learning initiative.

Core Areas of Research

Student research is supported by faculty in four core areas:

Actuarial science

Risk management

Decision-making under risk and uncertainty

Our faculty have specific areas of expertise in microinsurance, insurance regulation, financial management of insurance organizations, corporate risk management, behavioral economics, predictive modeling, healthcare analytics, health services management, and statistical methods development.

Our faculty members contribute to significant advancements in the field, as evidenced by our recently published journal articles .

Academic Requirements

All students must meet the general PhD requirements of both the UW–Madison Graduate School and the Wisconsin School of Business. Applicants to the program should have the following:

• A strong mathematics and statistics background. We generally look for three semesters of calculus and linear algebra at a minimum for mathematics. For statistics training, we look for coursework covering applied regression models in statistics and/or econometrics.
• A background in some combination of economics/finance, insurance, actuarial science, and statistics.

Program Coursework

The course sequence for PhD students in insurance economics and actuarial analytics is customized to fit each student’s unique research interests and background.

You will work with a PhD faculty advisor to set an appropriate course sequence during your first two years of study. However, all students are expected to take the following minimum core course sequence:

Two semesters of PhD-level Microeconomic Theory

Two semesters of PhD-level Econometrics

Panel-data statistics/econometrics

Seminar in Actuarial Science, Risk Management, and Insurance I

Seminar in Actuarial Science, Risk Management, and Insurance II

See Guide for all course requirements

Faculty Research Interests

Daniel Bauer Research interests: Risk evaluation Quantitative finance Risk management Insurance economics View full profile Stuart Craig Research interests: Industrial organization of health care and health insurance markets Employer-sponsored health insurance Business-to-business price setting Applied econometrics View full profile Tyler Leverty Research interests: Economics of insurance markets Insurance company operations Insurance regulation Public policy issues in insurance View full profile Anita Mukherjee Research interests: Insurance markets Development economics Law and economics Psychology and economics View full profile Philip Mulder Research interests: Climate finance Disaster insurance Real estate and household finance View full profile Marjorie Rosenberg Research interests: Applications of statistics and actuarial science Bayesian methodology related to health insurance View full profile Peng Shi Research interests: Predictive modeling Multivariate regression models Longitudinal/panel data Asymmetric information in insurance View full profile Dan Sacks Research interests: Social insurance, including Social Security and the Affordable Care Act Health insurance, moral hazard, and adverse selection Applied econometrics Industrial organization View full profile Justin Sydnor Research interests: Psychology and economics Applied microeconomics Behavioral industrial organization Insurance markets Decision-making under risk View full profile Connect With Current Students

We encourage you to contact our doctoral students in actuarial science, risk management, and insurance to hear their perspectives on the Wisconsin PhD Program.

View current student profiles

See Our Placement Results

Graduates of our PhD specialization in actuarial science, risk management, and insurance have accepted tenure-track positions at top research universities.

View recent placements

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Doctor of Philosophy (PhD) Risk and Actuarial Studies

How to apply.

If you are interested in pursuing a PhD with the School of Risk and Actuarial Studies (UNSW Business), then you will need to receive an Invitation to Apply from the school’s Postgraduate Research Coordinator .

To receive an Invitation to Apply, you should 1) self-assess your eligibility, and 2) then submit an Expression of Interest (EOI) by 31 st July 2024 . Only selected applications will be invited to apply via the UNSW central portal. Details of what to include in your EOI can be found here .

About the Doctor of Philosophy (PhD) Risk & Actuarial Studies

UNSW’s Doctor of Philosophy (PhD) Risk & Actuarial Studies will prepare you to become a globally focused and socially engaged research leader. You’ll join a cohort of high-achieving research students working at the forefront of research in actuarial studies, risk analytics, superannuation and population ageing, alongside leaders in the field (ranked 1st in the UNL Global Research Rankings of Actuarial Science and Risk Management & Insurance TM ). This is your opportunity to become integrated into the UNSW Business School’s community of scholars.

Most admitted students will enter the pathway program, the Master of Pre-Doctoral Business Studies (MPDBS). If you are invited to apply for Direct Entry into a PhD, either before or after successful completion of the MPDBS, then the minimum time commitment is 35-40 hours per week for 3-4 years (full time) or 15 hours a week (part time).

You’ll first undertake rigorous coursework covering risk theory, multivariate models for risks, longevity risk management, data analytics, economic and regulatory capital and investment and asset liability modelling. As part of your PhD program, you’ll also be involved in research projects from an early stage. This training will equip you with the skills required to identify, analyse and solve problems in the field.

You’ll then pursue full-time research under the supervision of high-profile UNSW academics, culminating in a doctoral thesis. There will also be exciting opportunities throughout to interact with industry leaders, and to develop your teaching portfolio. The training is geared toward preparing you for a career in academia, although other career paths (e.g., consulting, government, industry, non-profit) are also enabled.

Your PhD thesis will showcase your research skills and enable you to make an original contribution to your field.

Linked Master of Pre-Doctoral Business Studies (MPDBS) + PhD

Although a few students may be invited to apply for Direct Entry into our PhD program, most applicants are invited to first complete our Master of Pre-Doctoral Business Studies (MPDBS).

The MPDBS is a one-year pathway for students wanting to undertake a PhD in the UNSW Business School. The MPDBS is a fully funded program, which includes a tuition waiver and stipend (of ~A$37K) for all accepted applicants. This degree constitutes one year of advanced coursework including a research project. Upon completion of the MPDBS, the vast majority of students have historically gone on to our PhD with a scholarship covering tuition and a stipend (~ A$47K).

The MPDBS gives students an extra year to develop their research skills and to find a match with appropriate supervisors. 

The application processes for both the PhD and the Linked MPDBS + PhD are identical as shown in How to Apply.  

PhD Program Structure

Year one: master of pre-doctoral business studies (mpdbs).

Your first year of study is designed to provide a rigorous foundation to conduct independent research. You’ll learn a range of methodologies and build your communication and presentation skills.

Your first year of coursework study will cover fundamental research methods. You’ll also start developing key research skills such as identifying, framing, presenting, and writing academic contributions. You’ll work as a research assistant on faculty research projects and start working on your own research as your skills develop.

The first year will help you identify your potential thesis supervisor for the PhD component of the program. Upon successful completion of the first year, you’ll be awarded a Master of Pre-Doctoral Business Studies. A brief overview of the first year is presented below. Please visit the  UNSW Handbook  for full course structure details. 

• Program Core Course:  COMM8100
• Two Elective Courses
• Program Core Course:  COMM8101  or  COMM8102
• Stream Core Course: Research Assistance Work
• One Elective Course
• Program Core Course:  COMM8103

Year Two: Specialised Coursework & Identification of Thesis Topic

During the second year, you’ll continue in the Risk & Actuarial Studies stream with a further year of advanced coursework.

You’ll choose up to eight additional research courses from a range of electives in consultation with your supervisor, with an opportunity to take at least one subject outside of your specialised discipline.

Your second year is also when you’ll identify your thesis topic with your supervisor. You’ll engage in literature review and research design and present your research proposal to the School at the end of the year.

Year Three – Four: Original Research & Your Doctoral Thesis

The final two years of the program are focused on conducting full-time research and completing your doctoral thesis. This is your opportunity to address some of the biggest challenges in Risk & Actuarial Studies and make a significant contribution to knowledge in your field. Your research will offer new critical thinking and withstand critical analysis from expert researchers in the area.

As with most other OECD countries, the number of PhD completions in Australia has grown dramatically – more than doubling in the last two decades.

An increasing number of PhD graduates find employment in business, government, and the non-profit sector. Nineteen of the largest ASX companies have PhD graduates on their senior executive teams.

Your PhD thesis will set you on the path to a career in a premier research institution, anywhere in the world. Throughout your research degree, you’ll also have many opportunities to develop your teaching portfolio.

Beyond academia, there is also significant demand in the private and public sectors for people with deep knowledge and sound research and analytical skills*.

Whether you’re looking to pursue a career in academia, or take your research skills out to industry, a PhD in Risk & Actuarial Studies from UNSW will get you there.

*Source:  2019 Advancing Australia’s Knowledge Economy Report

Degree type

Postgraduate Research

4 years full-time, 5-8 years part-time

Commencing terms

Term 1 – February

Program code

Delivery mode, domestic / international.

International

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Graduate Studies in Actuarial Science

Students interested in studying actuarial science at the graduate level at the Illinois State University should pursue graduate studies in Mathematics: Sequence in Actuarial Science. There are two options for obtaining a Master degree: with Master Thesis (requiring 30 credit hours of graduate classes, and 15 of those at the 400 level), or without a thesis (requiring 32 credit hours of graduate classes with 16 of those at the 400 level, and a culminating experience, in the form of a professional internship, a project, or a comprehensive examination).

Our program reserves the right to enforce professional standards of practice as specified by the Society of Actuaries and the Casualty Actuarial Society. These standards may be taken into consideration in program retention decisions. Practically, this means that graduate actuarial students are expected to pass several professional actuarial examinations and obtain professional actuarial internship(s) before they graduate.

Prospective graduate students can obtain information about graduate admission from  Graduate School. Graduate Adviser in Mathematics is Professor Maochao Xu. Questions can also be sent to:  [email protected].

Financial support for graduate students is provided in the form of competitive Graduate Teaching Assistantships (GTA). Available positions are announced online: go to  www.ilstu.edu,  click on “jobs”, follow that to Graduate Assistantships and search for mathematics. Actuarial students may also compete for Graduate Assistantships in the Department of Finance, Insurance and Law. For mathematics applications, two letters of reference should be sent directly to  Masters Program Director,  and those letters should address academic and job skills, as well as for an international student, spoken English ability. An optional optional statement of purpose from the student candidate may also be submitted.

The following actuarial classes in the  Department of Mathematics  are offered only at the graduate level:

• Mathematics 480: Applications of Actuarial Principles (covers reserving and pricing for various forms of insurance, pension funding, and some issues of insurance and pensions regulation), and
• Mathematics 483: Mathematical Models in Finance and Investments (covers the mathematical portion of topics from advanced actuarial examinations on finance and investments).

The following actuarial classes in the  Department of Mathematics  are available for graduate credit:

• Mathematics 351: Statistics and Data Analysis (meets all  VEE Statistics  requirements),
• Mathematics 353: Regression and Time Series Analysis (covers material on the  SOA  Course SRM and the  CAS  Course MAS I),
• Mathematics 355: Introduction to Statistical Learning (covers material on the  SOA  Course SRM and the  CAS  Course MAS II),
• Mathematics 380: Actuarial Models (covers  SOA  Course FAM examination, and a part  CAS  Course MAS I, and is an approved FAM-L University Earned Credit class),
• Mathematics 381: Actuarial Models II (covers the rest of  SOA  Course ALTAM and some material on the  CAS  Course MAS I), note that at this time, MAT 381 is only offered in the Fall semester, also note that effective with the Fall 2023 semester, MAT 381 is approved for University Earned Credit for Society of Actuaries Course ALTAM examination,
• Mathematics 383: Actuarial Models III, and
• Mathematics 384, Actuarial Models IV (covers the material on the  SOA  Courses FAM-S and ASTAM, and is an approved FAM-S University Earned Credit class.

Professional internship in actuarial science is available as  Mathematics 498 . Internship information is available  here . Students should also consider taking graduate classes in mathematics, statistics, finance, and economics.

Statistics classes:

• Mathematics 351: Statistics and Data Analysis
• Mathematics 354: Nonparametric Statistics
• Mathematics 355: Introduction to Statistical Learning
• Mathematics 356: Statistical Computing
• Mathematics 443: Statistical Learning and Data Mining (this class is strongly recommended)
• Mathematics 450: Finite Sampling
• Mathematics 453: Regression Analysis
• Mathematics 455: Applied Stochastic Processes
• Mathematics 456: Multivariate Statistics
• Mathematics 458: The Design of Experiments

Economics classes:

• Economics 437: Fundamentals of Econometrics
• Economics 438: Microeconometrics
• Economics 440, Advanced Microeconomic Theory
• Economics 441, Advanced Macroeconomic Theory

Finance classes:

MBA 440: Financial Management. This class, along with ACC 131, FIL 242 or MAT 483 satisfies  VEE Accounting and Finance  requirements. Graduate actuarial students interested in taking MBA 440 must contact the  College of Business MBA Program  advising office and request a special permission for non-majors to take it. Such students must prove knowledge of material in MAT 350 (or having passed Course P/1 actuarial examination), and MAT 280 (or having passed Course FM/2 actuarial examination). If you have questions about enrollment in those classes, you can also send them to:  [email protected].

Doctor of Philosophy (PhD)

Graduate studies | Our programs | Doctor of Philosophy

Program Details

Phd in actuarial science, who is this program for.

This program is for students who have completed a Master’s or Bachelor's degree in statistics, actuarial science, mathematics, or other quantitative discipline and would like to pursue research in actuarial science. Graduates from this program typically enter academia or work in the private sector after graduation.

What does it take to get in?

A Master's degree in statistics, actuarial science, mathematics, or other quantitative discipline completed or expected with a cumulative GPA of at least 78% from a Canadian university ( or its equivalent ). A demonstrated ability to conduct high level research is helpful but not required. 

Students with a four-year Bachelor's degree are invited to apply directly to the PhD program. The admissions committee will review each applicant's background for suitability and may recommend admission to our Master's program instead. 

When should I apply?

Priority application deadline: December 15th. Applications must be completed by this date with all documents uploaded to be considered for early admission, invitation to our Grad Visit Day, and entrance awards. 

Final application deadline: January 15 th  for fall admissions (there are no Winter or Spring admissions). 

PhD in Biostatistics

This program is for students who have completed a Master’s or Bachelor's degree in statistics, actuarial science, mathematics, or other quantitative discipline that are looking to develop research skills to address a wide range of challenges arising in health, biology, and the environment. Demand for biostatisticians in Canada and internationally is high and graduates typically find employment in areas such as pharmaceutical companies, contract research organizations, regional or national centers for health research, academic centers, and public health agencies.

PhD in Statistics

This program is for students who have completed a Master’s or Bachelor's degree in statistics, actuarial science, mathematics, or other quantitative discipline. The PhD will build on this background with the goal of training first-class independent researchers. Graduates from this program find career opportunities in academia, research, and private industry.

Research Areas

Actuarial science.

• Capital allocation
• Portfolio optimization
• Pricing and hedging of investment-linked products
• Risk management
• Ruin theory
• Stochastic modelling 
• Monte Carlo and quasi-Monte Carlo

Biostatistics

• Analysis of life history data
• Causal inference
• Clustered data
• Design and analysis of clinical trials
• Epidemiological methods
• Event history analysis
• Generalized linear models
• Longitudinal data analysis
• Methods for dealing with incomplete data and measurement error
• Stochastic processes
• Statistical computing
• Studies of biological systems
• Artificial intelligence
• Business and industrial statistics
• Computational statistics
• Data science
• Exploratory data analysis
• Machine learning
• Non-parametric methods
• Probability theory
• Statistical modeling and inference
• Statistical geometry
• Survey methods
• Survival analysis
• Time series

Additional Information

• Admission and degree requirements
• Course listings
• Actuarial Science faculty members
• Biostatistics faculty members
• Statistics faculty members

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PhD in Actuarial Science

Doctoral studies at the Department of Actuarial Science offer candidates the possibility of acquiring a high level of knowledge through intensive research training. The Faculty of Business and Economics and the Department of Actuarial Science offers a stimulating and productive research environment where PhD candidates work in close interaction with the professors. The main goal of the program is to attract the best doctoral students and develop them to be competent in conducting independent research. A PhD in Actuarial Science opens the way for an academic career but also offers very diverse opportunities in the financial, insurance, pensions risk management, and consulting sectors.

Doctoral studies aim at developing the ability to complete an independent scientific study within an agreed timetable, to make an original contribution to research, and to add to the body of knowledge in the chosen area. Undertaking a doctoral program implies a personal commitment for three to five years. It involves a long course of study dedicated to research, the results of which will be presented in a thesis.

The potential research areas cover both theoretical topics (e.g., risk theory, credibility theory, financial mathematics, statistics) and applied topics (evaluation of insurance companies and pensions funds, financial markets and services, insurance products, etc.). The doctoral courses include the yearly International Summer School of the Swiss Actuarial Association that is held in Lausanne as well as many research seminars and specific courses in the candidate’s fields covering the whole range of topics related to Actuarial Science.

The Department of Actuarial Science has a strong international reputation and the training of PhD students is closely linked to the research of the faculty. The PhD program plays an important role in involving the PhD students in original research production. Thus, many students succeed in publishing their work during their studies in the top journals of their field. PhD students also present their work at international conferences where regularly awards are won.

The doctoral program attracts students having masters from various fields including actuarial science, mathematics, finance, economics and management. The strength of the program is evidenced in the students’ placements in top institutions both in terms of academic and business appointments.

You can find more information about the PhD in Actuarial Science on the other pages of the website.

Doctoral Program in Actuarial Science University of Lausanne HEC Lausanne Extranef 236 Quartier de Dorigny CH-1015 Lausanne

catherine.lombardvonlanthen@unil.ch +41 21 692 33 82

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Actuarial Science

Qualifying as an actuary is a passport to a wide variety of careers in insurance companies, investments, pensions, health care and banking – not just in the UK, but throughout the world. Kent is one of a very few universities in the UK to teach the subject.

Key information

• Duration 3 to 4 years full-time
• Start date September, January, May
• Location Canterbury

The PhD in Actuarial Science offers the opportunity to begin or consolidate your research career under the guidance of internationally renowned researchers and professionals in the School of Mathematics, Statistics and Actuarial Science (SMSAS).

This research programme, which can be taken three to four years full-time or five to six years part-time, offers the opportunity to work in highly topical areas such financial modelling and estimation, quantification of diversification benefits, quantifying financial risks, and derivatives pricing. Applications for PhD research in these and other areas will be welcomed.

There's an active seminar programme involving a wide range of speakers and members of the PhD community regularly attend/present their work at leading conferences and institutes.

Before applying for this course, it is strongly recommended that you contact the School of Mathematics, Statistics and Actuarial Science in the first instance to discuss your study plans with the programme director.

About the School of Mathematics, Statistics and Actuarial Science (SMSAS)

The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills.

In 2010 the Centre for Actuarial Science, Risk and Investment (CASRI) was set up within SMSAS to reflect the widening scope of the teaching and research of the staff. Areas of research interest include economic capital and risk management for financial services firms, mortality and longevity modelling, longevity indices and markets. Other research topics include genetics and insurance, insurance economics, pensions and corporate reporting.

The Centre includes 13 professionally qualified actuaries with many years’ practical experience in insurance and pensions, and who maintain excellent links with the actuarial profession.

Everything you need to know.

Entry requirements, study support.

A first or upper second class honours degree in a relevant subject (or equivalent).

All applicants are considered on an individual basis and additional qualifications, professional qualifications and relevant experience may also be taken into account when considering applications. 

Please see our International Student website for entry requirements by country  and other relevant information. Due to visa restrictions, students who require a student visa to study cannot study part-time unless undertaking a distance or blended-learning programme with no on-campus provision.

English language entry requirements

This course requires a Good level of English language, equivalent to B2 on CEFR.  

Details on how to meet this requirement can be found on our English Language requirements webpage . 

Examples:  

IELTS 6.0 with a minimum of 5.5 in each component 

PTE Academic 63 with a minimum of 59 in each sub-test 

A degree from a UK university 

A degree from a Majority English Speaking Country 

Need help with English?

Please note that if you are required to meet an English language condition, we offer a number of pre-sessional courses in English for Academic Purposes through Kent International Pathways .

Postgraduate research is a fantastic opportunity and significant investment in your future, enabling you to expand your knowledge, skills and career options – all while making a meaningful impact and contribution to an area you are passionate about.

At Kent, we also recognise the significant financial investment that comes with postgraduate study, and we offer a range of scholarships for our postgraduate researchers, to help keep your mind on your studies, and off your finances.

Scholarships can be broad, or specific to your situation, background or even country – so please do use our scholarships finder to discover the options available to you.

We also have research partnership funding with research councils and government schemes in specific areas of interest that can help you take your research to the next level with additional financial support.

Find out more on our fees and funding page and discover what option is right for you.

Postgraduate resources

The University’s Templeman Library houses a comprehensive collection of books and research periodicals. The University of Kent has entered into an exclusive arrangement with SunGard, a global leader in integrated software and processing solutions primarily for financial services, who market the industry’s leading actuarial software package PROPHET.

Links with industry

The Centre for Actuarial Science, Risk and Investment maintains close relationships with industry actuaries through the Invicta Actuarial Society, a regional actuarial society which holds its meetings at the Canterbury campus and is organised by University of Kent students and academic staff. The Society hosts an annual lecture in conjunction with the Worshipful Company of Actuaries, featuring prestigious speakers from industry and the profession. The Society also arranges talks from external speakers including practitioners, careers advisers and recruiters from the UK and overseas.

Dynamic publishing culture

Staff publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: British Actuarial Journal ; Actuary Australia ; Annals of Actuarial Science ; Journal of Pension Economics and Finance . Details of recently published books can be found under staff research interests.

Researcher Development Programme

Kent's Graduate School co-ordinates the Researcher Development Programme for research students, which includes workshops focused on research, specialist and transferable skills. The programme is mapped to the national Researcher Development Framework and covers a diverse range of topics, including subject-specific research skills, research management, personal effectiveness, communication skills, networking and teamworking, and career management skills.

Work in actuarial science at the University of Kent can be divided into three broad themes achieving a balance of theoretical and applied investigations, as well as addressing social policy implications.

Economic capital and financial risk management

With the advent of new risk-based regulations for financial services firms, specifically Basel 2 and Basel 3 for banks and Solvency 2 for insurers, there is now a heightened focus on the practical implementation of quantitative risk management techniques for firms and defined benefit pension schemes operating within the financial services sector.

In particular, financial services firms are now expected to self-assess and quantify the amount of capital they need to cover the risks they are running. This self-assessed quantum of capital is commonly termed risk, or economic, capital.

At Kent we are actively involved in developing rigorous risk management techniques to explicitly measure how much risk a firm or pension scheme is taking, holistically, across the entire spectrum of risks it accepts.

More about our research in this area

Longevity risk

Longevity risk represents a substantial threat to the stability of support programmes for the elderly, most notably to the subset that provides income protection but also to non-traditional products such as home equity release schemes.

One approach to dealing with longevity risk is to model key factors that influence mortality; this may be achieved using aggregate (causal) mortality rates or panel data with individual-specific covariates. Another approach to modelling longevity risk is via an investigation of positive quadrant dependence between lives, which requires a multivariate framework. Once this is in place, longevity risk may be investigated on various fronts ranging from entire populations to couples.

Public policy aspects of risk classification

Restrictions on risk classification can lead to adverse selection, and actuaries usually regard this as a bad thing. However, restrictions do exist in many countries, suggesting that policymakers often perceive some merit in such restrictions. Careful re-examination of the usual actuarial arguments can help to reconcile these observations.

Models of insurance purchasing behaviour under different risk classification regimes can quantify the effects of particular bans, e.g. on insurers’ use of genetic test results, or gender classification in the European Union.

Staff research interests

Kent’s world-class academics provide research students with excellent supervision. The academic staff in this school and their research interests are shown below. You are strongly encouraged to contact the school to discuss your proposed research and potential supervision prior to making an application. Please note, it is possible for students to be supervised by a member of academic staff from any of Kent’s schools, providing their expertise matches your research interests. Use our ‘ find a supervisor ’ search to search by staff member or keyword.

Full details of staff research interests can be found on the School's website .

Helping our students to develop strong employability skills is a key objective within the School and the University. We provide a wide range of services and support to equip you with transferable vocational skills that enable you to secure appropriate professional positions within industry. Within the School we run specialist seminars and provide advice on creating a strong CV, making job applications and successfully attending interviews and assessment centres.

Our graduates have gone on to successful careers in the actuarial, finance, insurance and risk sectors.

The 2024/25 annual tuition fees for this course are:

For details of when and how to pay fees and charges, please see our Student Finance Guide .

For students continuing on this programme fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.* If you are uncertain about your fee status please contact [email protected] .

Your fee status

The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from  UKCISA  before applying.

General information

For students continuing on this programme, fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.* 

Additional costs

General additional costs.

Find out more about  general additional costs  that you may pay when studying at Kent. 

Search our scholarships finder for possible funding opportunities. You may find it helpful to look at both:

• University and external funds
• Scholarships specific to the academic school delivering this programme.

We have a range of subject-specific awards and scholarships for academic, sporting and musical achievement.

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Learn more about the  application process  or begin your application by clicking on a link below.

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UW-Milwaukee Academic Catalog

Mathematical sciences.

Mathematics, MS: Actuarial Science

Objective of mathematics ms: actuarial science (option c).

The program provides a mathematically rigorous education in actuarial science, prepares students for actuarial professional exams, and develops their economics and business reasoning skills. Students obtain thorough knowledge in the fundamentals of actuarial science such as applied probability models, applied statistics, credibility, financial economics, life contingencies, loss models, and risk theory. Emphasis is placed on developing skills that are highly valued by employers and thus are essential for a successful career as actuary. This program is intended for students who will seek employment as an actuary upon completion of the degree. Those interested in entering the department’s Ph.D. program should consider a different Master’s option.

Overview of Mathematical Sciences Department MS programs

The Department of Mathematical Sciences offers graduate programs of study in mathematics with specializations in the fields of algebra, analysis, topology, applied mathematics, probability and statistics, and actuarial science.

The programs of study at the master’s level are designed to suit both the student intending to continue toward a PhD as well as the student who wishes to begin a professional career upon completion of the master’s program.

The student may prepare for a career in teaching at the secondary or college level and for a career in research in the academic, industrial, government, or business communities.

Three options for the master’s degree are offered: the standard mathematics option (A), the statistics option (B), and the actuarial science option (C). Students who plan to continue for a PhD degree with a focus on mathematics/statistics should elect an option from options A, B, C, or the dual master’s degree option. 

Dual Master’s Degree Option

In addition to multiple options available for MS in mathematics, the Department of Mathematical Sciences at UWM and the Department of Technomathematics of Fachhochschule Aachen (FHA), Germany have recently created a Dual Master’s Degree Program in Mathematics. The students enrolled in this program will be able to earn Master’s degrees from both institutions upon completion of the common course requirements.

The program is designed in such a way that students typically will be able to complete all the course requirements within a two-year time period (one year at each institution). Within this program students can choose courses that will allow them to concentrate in the areas of Statistics, Numerical Analysis or General Mathematics. Complete information on the admission policy and graduation requirements, including sample schedules, is available at the Department of Mathematical Sciences web page  http://uwm.edu/math/graduate/ .

Admission Requirements

Credits and courses, additional requirements, application deadlines.

Application deadlines vary by program, please review the application deadline chart for specific programs. Other important dates and deadlines can be found by using the One Stop calendars .

Students with undergraduate degrees in mathematics, statistics, actuarial science, economics or a related area are eligible for admission. Applicants should have a strong mathematical background that includes three semesters of calculus, linear algebra, probability, and mathematical statistics. Students lacking this background may be admitted provided that the deficiencies amount to no more than two courses. Although not required, having one actuarial professional exam passed would be an asset.

The minimum degree requirement is 33 credits. In order to graduate, the following requirements must be completed:

Students who have completed program courses for undergraduate credit should discuss alternative graduate-level courses to substitute for those courses in their programs of study.

A thesis is not required for the actuarial science option. Rather, students must pass three departmental written proficiency exams, which are based on the learning objectives of the actuarial professional exams P, FM and one of FAM, ALTAM, ASTAM. Waivers for departmental exams are granted for students who have passed the corresponding professional exams.

Professional Development

For future advancement in the field of actuarial science, “Validation by Educational Experience” (VEE) credits are required. VEE credits may be earned from the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) with a grade of B- or better in the following courses:

Courses taken at other universities may be used to meet the VEE requirement of the SOA/CAS.

Major Professor as Advisor

The student must have a major professor, selected from the members of the Actuarial Science Committee, to advise and supervise the student's studies. The entering student is assigned an advisor by the chair of the committee. Before the start of studies, each student in the program must develop a plan of study in consultation with the Committee.

Full-time students are expected to complete the program in two years. Students must complete all degree requirements within five years of initial enrollment.

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RIT graduate pursues Ph.D. across time zones

Nastaran Nagshineh, center, defended her Ph.D. thesis at RIT in April. Faculty from RIT’s Rochester and Dubai campuses served on her thesis committee and include, from left to right, Kathleen Lamkin-Kennard, Steven Weinstein, Nathaniel Barlow, and David Kofke (a professor at the University at Buffalo). Mohamed Samaha participated remotely and appears on the video screen behind the group and alongside Nagshineh’s picture.

Nastaran Nagshineh is one of the first Ph.D. candidates to bridge RIT’s Rochester and Dubai campuses. Her accomplishment creates a path for future students at the university’s international campuses.

Nagshineh completed her Ph.D. in mathematical modeling while working full time as a mathematics lecturer at RIT Dubai in the United Arab Emirates, teaching as many as five classes a semester. She described her Ph.D. journey as “an exercise in perseverance” due to competing demands and long days. Rochester is eight hours behind Dubai, and the time difference meant many late-night classes and meetings.

“I saw this collaboration as an opportunity, rather than as a challenge, because my primary adviser, Dr. Steven Weinstein (RIT professor of chemical engineering), and my co-adviser, Dr. Mohamed Samaha (RIT Dubai associate professor of mechanical engineering), both have the same area of research interest,” she said. “They both worked toward my success.”

Nagshineh is one of 67 RIT Ph.D. students who defended their thesis this academic year and who will earn their doctorate. RIT awarded 63 Ph.D. degrees in 2023.

In 2020-2021, RIT’s Graduate School met and surpassed the university’s goal of conferring 50 Ph.D. degrees during an academic year. That number will continue to grow as students cycle through the seven new Ph.D. programs that RIT has added since 2017, said Diane Slusarski , dean of RIT’s Graduate School.

Meeting these goals puts RIT on a path toward achieving an “R1,” or research-intensive designation, from the Carnegie Classification of Institutions of Higher Learning. RIT is currently ranked as an R2 institution . Many factors go into changing a university’s status, including research investment and maintaining a three-year average of 70 Ph.D. degrees awarded per year, according to Slusarski.

“We have met the goals of the strategic plan, and now we look forward to contributing to the research innovation in the future,” Slusarski said. “We want to help the new programs thrive and win national research awards.”

RIT’s emphasis on high-level research is seen in Nagshineh’s Ph.D. work. She applies mathematical modeling to the field of fluid dynamics. Her research has been published in top-tier journals and has gained notice, said Weinstein, her thesis adviser.

Weinstein describes Nagshineh’s accomplishments as “a testament to a fantastic work ethic and commitment” and is inspirational to younger students at Rochester and Dubai.

“The collaboration between RIT Dubai/Rochester has continued,” he said. “Another paper was submitted a few weeks ago with Mohamed Samaha and Nate Barlow (RIT associate professor in the School of Mathematics and Statistics) as co-authors, as well as Cade Reinberger, a younger Ph.D. student in my research group.”

Mathematical modeling is one of RIT’s newer Ph.D. degree programs, and Nagshineh is among its earliest graduates. The program has doubled in size since it began accepting students in 2017, Slusarski said. This past fall, the mathematical modeling program had 35 students, with two graduating this year.

Altogether, RIT has 13 Ph.D. degree programs currently enrolling 438 students, with computing and information sciences accounting for the largest with 117 students. RIT’s other Ph.D. programs include astrophysical sciences and technology , biomedical and chemical engineering , business administration , color science , electrical and computer engineering, imaging science , mechanical and industrial engineering , microsystems engineering , and sustainability .

New programs in cognitive science and physics will launch in the fall.

The growth in RIT graduate education—with more than 3,000 master’s and doctoral students—reflects a demographic change in the student population, Slusarski said. “We have a higher percentage of women in the graduate programs than we have for RIT undergraduate programs.”

RIT’s graduate programs enroll 42 percent women, according to Christie Leone , assistant dean for the Graduate School.

Nagshineh, who also holds an MS in electrical engineering from RIT Dubai, welcomes her role as a mentor to other women students on both campuses.

“As a young woman in an Arabic country, the power of women is often underestimated and undervalued, and I hope to serve as a role model to female students, especially those that question their path,” Nagshineh said.

She plans to continue in her career as a professor and a researcher. “I would like to pursue a research program where I can advise my own students and teach them more deeply.”

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Congratulations, mss class of 2023, may 17, 2024.

The faculty and staff of the Department of Statistical Science offers heartfelt congratulations to the MSS Class of 2024! Members of this graduating class are part of an incredibly accomplished group. Eight students will be entering prestigious Ph.D. programs at Duke, Johns Hopkins, and UPenn, among others, and most received multiple Ph.D. admissions offers.  Other members of the class are stepping into a myriad of industry roles, including data scientists, engineers, and analysts at companies like American Express, Deutsche Bank, and Aetna/CVS Health. We wish them continued success in their professional careers, or in continuing their academic journey.

We’d also like to recognize our thesis, portfolio, and TA winners:

Zhengyu “Ryan” Tang – BEST Award winner (thesis) Yicheng Shen – BEST Award Honorable Mention (thesis)

2024 Portfolio Awardees Junghwa Jang Yunhong Bao Yinyihong Liu

Honorable Mentions Bei Yu Kwong Yu Chong Yize (Howard) Jin William Tirone

Master’s TA of the Year Yicheng Shen

Honorable Mentions Christopher Oswald William Turone

Congratulations to all award recipients and the honorable mentions for their outstanding work and achievements  

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