epfl thesis timeline

A best practices guide to PhD programs at EPFL

• French 2021 2020 2019 2018
• German 2021 2020 2019 2018
• English 2021 2020 2019 2018

EPFL has published a guide that sets out the rules of its PhD programs, as well as the rights and responsibilities of PhD students and their thesis supervisors.

A large part of a PhD program is the relationship between students and their thesis supervisors. The quality of this relationship has a significant influence on the quality of the work produced and the well-being of everyone involved. Starting a PhD program can be daunting. In addition to their classes and research, students may also be adjusting to different habits and customs, adapting to a new culture, and learning certain unspoken rules. As for supervisors, they have to juggle many different responsibilities at once, are under pressure to deliver results, and must always be familiar with the best practices for overseeing PhD thesis projects.

Since 2017, PhD students have been asked to complete a survey each year. This gives them a chance to express their opinions and share their experience completing a PhD at EPFL. In 2019, three-quarters of respondents said they were satisfied with their experience, but many students also said they were under extreme pressure and were experiencing symptoms of stress and depression. Some students said they felt they had not received enough guidance on managing their thesis projects. This prompted EPFL’s doctoral school to create a best practices guide for both PhD students and supervisors.

© 2021 Adrien Miqueu

“The 2019 survey and comments we received from supervisors highlighted the need for a guide that summarizes the rules, systems and procedures for PhD programs at EPFL.”

– Luisa Lambertini, Associate Vice President for Postgraduate Education

Clarifying the relationship between PhD students and their supervisors

“We took all this feedback into account,” says Marius Burgat, a scientific advisor and lead writer of the guide. “We raised these issues with the Doctoral Commission (Cdoct), an advisory body that includes program heads as well as PhD student representatives.” Luisa Lambertini, Associate Vice President for Postgraduate Education, adds: “The 2019 survey and comments we received from supervisors highlighted the need for a guide that summarizes the rules, systems and procedures for PhD programs at EPFL. This information was previously out there, but was split up in many separate documents or had not yet been formalized in writing.”

“The aim of our guide is to give everyone involved in PhD programs a useful resource for information and contacts,” says Burgat. “It’s intended to be helpful both at the start of and during PhD studies, and can always be referred back to if someone experiences a problem.” The guide also offers advice to students and supervisors about settling into a PhD program, achieving a healthy work-life balance and preventing harassment. The paragraphs are color-coded, so it’s easy to see which parts are intended for students and which parts are for supervisors. “Students therefore understand what they can expect from their supervisors, and vice-versa,” says Burgat.

Understanding the aims of a PhD program

The guide also clearly outlines EPFL’s position on what a PhD program should lead to and how it should be conducted. Students must of course write a thesis, but there is more to it than that. “PhD students also need develop soft skills, such as project management and networking, which will be useful to them throughout in their careers, whether they decide to stay in academia or not,” says Burgat. “It’s important that supervisors encourage students in these skills as well.”

A work in progress

“Developing the PhD guide was a real team effort,” explains Burgat. Four PhD students and several supervisors volunteered their time to help put it together. “I would like to thank the many people and departments that contributed to this initiative,” says Burgat. “Special thanks go to PhD student Alice J. Gillen, to Jeroen van Hunen, who was then the Deputy Vice President for Postgraduate Education, and to Juliane Kuntschen and Anikó Borbély, who added the finishing touches and made sure the guide was ready for publication.” Lambertini points out that “the contents of this guide are destined to continually change and evolve. We therefore welcome any contributions from members of the PhD community.”

Excellence through Diversity

Semester Project and Thesis

The SPRING lab offers project opportunities for BSc, MSc, and PhD students. We encourage interested students to have a look at the Thesis & Project Guidelines from the MLO lab , where you will gain an understanding about what can be expected of us and what we expect from students.

Last Update: 18th April 2024

How to apply

Please, apply via Google form (login may be required) . You will need to specify which project(s) you are interested in, why you are interested, and if you have any relevant experience in this area.

External students , i.e., students who are not from EPFL nor ETHZ, should get in touch with the supervisors of the project(s) via email.

Applications are processed in two rounds. For each round, we collect applications before the deadline. Then, we will get back to selected applicants during the corresponding “First Contact From Supervisors” period. If we do not get back to you during the indicated period, it means that we probably do not have space any more.

We will make a mark on the project once it is taken. We strongly recommend that you apply as soon as possible for best consideration, since we expect most projects would be taken after the first round. However, we will leave the form open after the second round and consider all applications, if there are still available projects at that time.

Early deadline: 6th July 2024

First Contact From Supervisors: 8th July 2024 - 22nd July 2024

Late deadline: 23rd August 2024

First Contact From Supervisors: 26th August 2024 - 6th September 2024

If you encounter any technical issue, please get in touch with Saiid El Hajj Chehade .

Projects on Cryptography

Crypto1: a library for lattice parameter selection.

Many constructions for post-quantum-secure cryptographic tools and privacy-enhancing technologies rely on hardness assumptions based on lattice problems. However, setting the parameters for the underlying lattice problem in order to achieve a desired level of security is non-trivial, and really only accessible to a handful of experts today.

To date, the best tool for lattice parameter selection is the lattice estimator [1]; however, this tool is written in SageMath, and cannot easily be used as-is in production-ready codebases. Additionally, it does cover important variants of standard assumptions (e.g., MSIS, vSIS).

As part of our effort to port lattice-based cryptographic primitives from research to practice, you will design and implement a Rust library for lattice parameter selection. Concretely, this library should: (i) provide an intuitive and hard-to-misuse interface, (ii) internally use precise estimates for the hardness for lattice problems (e.g., by reducing to the shortest vector problem), and (iii) compute estimates for variants of standard problems of interest (e.g., new lattice assumptions, or standard assumptions with additional leakage). This library would be designed to be integrated into lattirust (to be open-sourced soon), our Rust library for lattice-based cryptography.

Requirements

• You should be familiar with Rust.
• Ideally, you have some knowledge of cryptographic lattice assumptions (Learning With Errors, Short Integer Solution), and/or lattice reduction techniques (LLL, L*, BKZ)

Applying to this project

This research project/master’s project (PDM) is aimed at one MSc student. The student will work with Christian Knabenhans .

[1] https://github.com/malb/lattice-estimator

CRYPTO2: Systematization of Knowledge of Private Information Retrieval protocols

Private Information Retrieval (PIR) [1] protocols allow a client to retrieve an element of a public database held by a server without revealing its query to the server. In addition, the communication costs between the client and the server are much less than the size of the database. As such, PIR is a very useful building block for privacy-enhanced applications such as private messaging and private search/lookups.

The past few years have seen an explosion of PIR protocols with a flurry of different assumptions and efficiency characteristics. Comparing these protocols is non-trivial, as they can be analyzed under many different angles (cryptographic assumption, client/server processing time, client/server storage overhead, communication bandwidth, pre-processing time/size, behaviour under updates/churn, size/format of database entries (e.g., small entries vs text vs images), etc.).

In this project, you will review existing/recent PIR protocols, establish a formal way of comparing them (e.g., by targeting a few specific use cases). Ideally, you will (re-)implement these protocols in Rust, using our lattirust library (to be open-sourced soon).

• Ideally, you have some knowledge of cryptographic lattice assumptions such as (Ring/Module)-Learning With Errors
• If we opt for a more implementation-oriented project, knowledge of Rust is desirable.

This research project/master’s project (PDM) is aimed at one/two BSc/MSc student(s). The student(s) will work with Christian Knabenhans .

[1] https://en.wikipedia.org/wiki/Private_information_retrieval

Projects on Machine Learning

Ml1: reconstruction attacks using diffusion models.

Perceptual hashing algorithms are widely used to detect edited copies of targeted content, such as CSAM or non-consensually shared intimate images, in social media platforms. A perceptual hashing algorithm maps an image to a fixed-size vector representation, which captures the main features of the image and is called a perceptual hash. Perceptual hashes are different from cryptographic hashes in that they are robust to small transformations applied to the image, such as grayscaling and resizing. Perceptual hashes are believed to be privacy-preserving because of the signal loss with respect to the original image, as they are typically very low dimensional and consist of bits.

The goal of this project is to design and evaluate reconstruction attacks against perceptual hashes, whose goal is to recover a version of the original image given the hash, and to explore different adversary assumptions. The starting point will be to replicate an existing proof of concept [1]. Then, the student will explore more advanced reconstruction techniques including through the use of generative models such as diffusion-based approaches.

• Previous experience with Pytorch.
• Previous experience in training neural networks in a research or industry context.
• Solid grasp of machine learning fundamentals.

This research project/master’s project (PDM) is aimed at one MSc student. The student will work with Ana-Maria Cretu .

[1] Anish Athalye. Inverting PhotoDNA (2021).

Projects on System Security

System1: constant-time fully homomorphic encryption/decryption/key generation.

Fully Homomorphic Encryption (FHE) allows for arbitrary computations to be performed on encrypted data, and is a very useful building block for more complex privacy-preserving protocols. FHE schemes are now fast enough to be deployed in practice, and are poised to be more widely deployed than ever in 2024 – 2026 thanks to the emergence of FHE hardware accelerators, various standardization efforts, and user-friendly compilers. FHE schemes are implemented in several libraries, but most libraries do not offer constant-time key-generation, encryption, and decryption operations, which can lead to devastating key-recovery attacks in practice [1-3].

Ensuring that these algorithms are actually constant-time is nigh impossible when using a high-level language (e.g., C, C++, Rust) and relies heavily on trusting the compiler and platform, which is an extremely brittle guarantee in practice. In this project, you will implement FHE key generation / encryption / decryption using the low-level Jasmin language , which automatically proves secret-independence of implementations using the EasyCrypt framework . A Jasmin implementation of ML-KEM (a key encapsulation mechanism based on similar cryptographic assumptions as FHE schemes) will provide a starting point for your implementation, but you will need to implement additional FHE-specific operations (e.g., arithmetic over polynomial rings, random sampling from truncated Gaussians, number-theoretic transforms). Ideally, your implementation will be bit-for-bit compatible with an existing FHE library, and will thus be a major step forward for more secure deployments of FHE in the real world.

• You should be comfortable with low-level programming (assembly-like languages).
• Ideally, you have some knowledge of Fully Homomorphic Encryption or some other cryptographic primitive based on (Ring) Learning With Errors.
• Ideally, you have some experience with formal verification tools such as EasyCrypt or F*.

[1] F. Aydin, E. Karabulut, S. Potluri, E. Alkim, and A. Aysu, “ RevEAL: Single-Trace Side-Channel Leakage of the SEAL Homomorphic Encryption Library ”. 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), IEEE, Mar. 2022

[2] Wei Cheng, Jean-Luc Danger, Sylvain Guilley, Fan Huang, Amina Bel Korchi, et al., “ Cache-Timing Attack on the SEAL Homomorphic Encryption Library ”. 11th International Workshop on Security Proofs for Embedded Systems (PROOFS 2022), Sep. 2022

[3] F. Aydin and A. Aysu, “ Leaking secrets in homomorphic encryption with side-channel attacks ”. J. Cryptogr. Eng., Jan. 2024

Projects on Web Security

Web1: replay user interactions for interactive web measurement.

The vast majority of web privacy studies [1] rely on automated crawls to perform scalable and large measurement studies and extrapolate conclusions about real visits. Underlying most of them an implicit assumption about the representativeness of these simulations to real users.

Today however, the web is becoming more and more interactive [2] as websites turn to webapps and full ecosystems, requiring complex and intentional user interactions to navigate them (eg: searching for a keyword, filling a form, navigating a menu, …). This raises concerns about the capabilities of crawling tools (OpenWPM [3], Puppeteer [4], …) to resemble the visits by users.

As shown by many works disputing the representativeness of crawls [5], the limits of crawlers cause a disparity in metrics of interest to studies (like the total number of contacted ATS domains, total count of fingerprinting scripts, … ) and in turn weaken the generalizeability of their insight to real users.

A main limitation to crawlers is their interactivity with the webpage. Most crawlers are fully static [1], while few interact in preset manners (logging in [6]). A new wave of generative web agents [7] emerged with complex techniques, but exploring the replay of user interactions was skipped altogether. Replaying user interactions is more efficient, more faithful to the user population, and deterministic across repetitions.

In this project, you will explore the problem of recording and replaying user interactions for web measurement, working through alternative designs from related work and language modeling field, devising evaluation frameworks to validate the designs in terms of advantage over static crawling and feasibility, and potentially launching a pilot study.

• Experience with crawling, instrumentation, and parsing webpages (HTML, JS, Network)
• Comfortable with docker, virtual machines and pipelining
• Comfortable with machine learning
• Comfortable with Python

This research project is aimed at one MSc student. The student will work with Saiid El Hajj Chehade .

[1] Stafeev, A., Center, C. H., & Pellegrino, G. SoK: State of the Krawlers–Evaluating the Effectiveness of Crawling Algorithms for Web Security Measurements.

[2] https://publications.waset.org/10013485/evolution-of-web-development-techniques-in-modern-technology

[3] https://github.com/openwpm/OpenWPM

[4] https://pptr.dev/

[5] David Zeber, Sarah Bird, Camila Oliveira, Walter Rudametkin, Ilana Segall, Fredrik Wollsén, and Martin Lopatka. 2020. The Representativeness of Automated Web Crawls as a Surrogate for Human Browsing. In Proceedings of The Web Conference 2020 (WWW ‘20). Association for Computing Machinery, New York, NY, USA, 167–178.

[6] Yana Dimova (imec-DistriNet, KU Leuven), Tom Van Goethem (Google / imec-DistriNet, KU Leuven), Wouter Joosen (imec-DistriNet, KU Leuven). Everybody’s Looking for SSOmething: A large-scale evaluation on the privacy of OAuth authentication on the web . PETS.

WEB2: Evaluating the effectiveness of network volume metrics for web privacy insights

To measure the effectiveness of PETs, the capabilities of attacks, or argue about the viability of crawlers, researchers need to quantify privacy impact with respect to a set of representative page visits. Most studies use aggregate counting metrics (like the number of total 3rd party domains contacted, total number of API calls, … ) as a proxy for the privacy leakage – either as exposing the user to trackers or fingerprinting the user, depending on the adversarial model.

However, for many cases quantity is not only what matters. For example, more leakage can be caused by a smaller set of high prevalence trackers and the connection between them. Also, some studies show that crawlers contact more 3rd party domains than real users which is counter-intuitive and weakens the representativeness of this metric [1]. This could be partly due to the statefulness of user browser sessions compared to primarily stateless crawlers, blasting the latter with more ATS traffic for cookie syncing for example [2].

In this project, you will tackle this problem in the context of a web evaluation study for various ad blockers, by building a representation of ATS inter-relations and impact on the website, exploring various new metrics for privacy leakage, and comparing them to the baseline across a dataset of popular webpages.

[1] David Zeber, Sarah Bird, Camila Oliveira, Walter Rudametkin, Ilana Segall, Fredrik Wollsén, and Martin Lopatka. 2020. The Representativeness of Automated Web Crawls as a Surrogate for Human Browsing. In Proceedings of The Web Conference 2020 (WWW ‘20). Association for Computing Machinery, New York, NY, USA, 167–178.

[2] Steven Englehardt and Arvind Narayanan. 2016. Online Tracking: A 1-million-site Measurement and Analysis. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (CCS ‘16). Association for Computing Machinery, New York, NY, USA, 1388–1401.

WEB3: Reproducing/extending privacy measurement and Analysis of 1-Million sites

The web domain is an ever-evolving ecosystem, with new practices introduced rapidly in every direction. Unfortunately, while some improve user web experience, other advances push trackers and advertisers to new heights, increasing the privacy risks for users. In 2016, Englehardt and Narayanan [1] conducted a large-scale study to measure the prevalence and prominence of tracking on the web. This study has been widely cited and has influenced the design of privacy-enhancing technologies. Among other things, they found that only 123 out of 81,000 trackers appear on more than 1% of webpages. Later studies have shown that the landscape has been changing in the last 7 years, we would like to investigate whether the same trends are still valid today, or if new trends have emerged.

In this project, you will reproduce the study of Englehardt and Narayanan [1] and extend it to the present day. You will crawl a large number of websites, measure the prevalence and prominence of tracking, and analyze the results. You will also extend the study by investigating new metrics proposed by newer studies and discuss the implications of the results.

• Experience with Python

This research project is aimed at one BSc/MSc student. The student will work with Saiid El Hajj Chehade .

[1] Steven Englehardt and Arvind Narayanan. 2016. Online Tracking: A 1-million-site Measurement and Analysis . In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (CCS ‘16). Association for Computing Machinery, New York, NY, USA, 1388–1401.

Study plans

Doctoral School

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• Block Courses
• Chemistry and Chemical Engineering
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• Joint EPFL - ETH Zurich Doctoral Program in the Learning Sciences
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Transforming to Excellence: Ecole Polytechnique Federale de Lausanne (EPFL)

• Original Article
• Published: 07 December 2018
• Volume 34 , pages 175–194, ( 2021 )

Cite this article

• Xiaohua Jiang   ORCID: orcid.org/0000-0001-5023-1008 1 ,
• Ying Cheng 1 &
• Qi Wang 1  

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This paper investigates an institutional transformation at a European research university, École Polytechnique Fédérale de Lausanne (EPFL) by adopting a qualitative case study method. Open-ended interviews were held with 45 faculty members and administrators to investigate the driving forces and overall transformation of EPFL as well as their effects on the success of EPFL. The study reveals that the then president played an important role in driving the university’s transformation under the support of the federal government during his tenure. His strategies aimed at integrating American systems into the European context led to an improvement in the university’s academic culture, contributing greatly to the concentration of talent, the acquisition of competitive research funding, and the scientific excellence of EPFL. Furthermore, it also shows that leadership needs to gain the support from faculty members to secure a successful transformation.

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Jiang, X., Cheng, Y. & Wang, Q. Transforming to Excellence: Ecole Polytechnique Federale de Lausanne (EPFL). High Educ Policy 34 , 175–194 (2021). https://doi.org/10.1057/s41307-018-00127-9

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• Entertainment

A Recent Timeline of the Drake vs. Kendrick Lamar Beef

T he long-simmering beef between Kendrick Lamar and Drake has exploded in recent days as the rappers repeatedly lobbed insults and allegations about one another’s families and personal lives in a series of escalating diss tracks that has also invoked other hip-hop greats, including Metro Boomin and DJ Mustard.

The feud, in which each rapper has made numerous unverified allegations, prompted Drake to respond in a song on Sunday that he’s “disgusted” by Lamar’s claims about him, including that he has a secret child and engages in sex with underage girls, which he denies.

In “The Heart Part 6”—a title that references Lamar’s “The Heart” song series—Drake said he would have “been arrested” were there any truth to the allegations about him having inappropriate relationships with underage girls. The 37-year-old Canadian rapper, who has a 6-year-old son, also suggested that he leaked false information about having a daughter to Lamar, singing: “We plotted for a week and then we fed you the information/ A daughter that’s eleven years old, I bet he takes it.”

The fight between the two men reached its climax (at least, to date) over the weekend, resulting in the release of multiple songs by and featuring the two artists. While their tense relationship dates back years, the origins of this most recent dispute can be traced to Drake’s song “First Person Shooter,” which was released as part of his album, For All the Dogs, last October. During that track, featured guest J. Cole called himself, Drake, and Lamar the “big three.” When Lamar was featured on Future’s “Like That” on March 22, he ripped into Cole and Drake for suggesting they are on the same level.

Read More: Why Drake Had to Take Down His Song That Featured AI-Tupac Vocals

The ensuing drama has brought forward serious, unverified claims, and shows no signs of slowing down. It is the latest chapter in a long tradition of rap feuds that has seen rivalries between the likes of Jay-Z and Nas and Tupac and Biggie. 

Here’s a recent timeline of the beef between Drake and Kendrick Lamar. 

The backstory and "First Person Shooter”

Both rappers achieved mainstream fame at around the same time in the early 2010s. They’ve worked together in the past; on Drake’s 2011 album, Take Care , Lamar is featured on an interlude, and Lamar had Drake on his second studio album, 2012’s Good Kid, M.A.A.D City , on the song “Poetic Justice.” 

The first sign of trouble seems to have cropped up around 2013, when Lamar appeared on Big Sean’s “Control.” Lamar called out Drake and several other rappers on the song, but Drake didn’t engage at first, suggesting in interviews at the time that he was not going to take the bait.

Instead, Drake's beef with Meek Mill in 2015 consumed much of his time, and later, in 2018, he got into it with Pusha T, who revealed that Drake was hiding a secret baby in the song “The Story of Adidon”—which Drake later admitted was true.

It wasn’t until “First Person Shooter” came out last year that Drake reopened the conflict with Lamar, intentionally or not, after Cole referred to himself, Drake, and Lamar as the “Big Three.” 

Kendrick’s featured verse on “Like That” 

Lamar, who won the Pulitzer Prize in 2018 for his album DAMN. , took offense to the idea that he and Drake are on the same skill level. The standout line in Future’s song “Like That,” which is produced by Metro Boomin, is, “Motherf-ck the big three, it’s just big me.” 

He also refers to Drake’s most recent album, For All The Dogs , rapping, “‘Fore all your dogs gettin' buried/ That's a K with all these nines, he gon' see Pet Sematary .”

J. Cole enters the beef with “7-Minute Drill,” but quickly bows out

Shortly after “Like That” came out, Cole released a surprise album called Might Delete Later, and one of the songs, “7 Minute Drill,” includes a diss directed at Lamar. 

In it, he raps, “Your first sh-t was classic, your last sh-t was tragic/ Your second sh-t put n----s to sleep, but they gassed it/ Your third sh-t was massive, and that was your prime,” a line that many listeners took issue with because Cole suggests that To Pimp a Butterfly (an album widely regarded as Lamar’s best) was boring. He says in the song that people don’t care about Lamar, rapping, “He averagin’ one hard verse like every thirty months or somethin’/ If he wasn’t dissin’, then we wouldn’t be discussin’ him.”

However, Cole then decided to distance himself from the beef. He later said that the song “didn’t sit right with his spirit” and removed it from streaming services on April 12, saying his actions are some of the “lamest, goofiest sh-t” he’s participated in.

Drake tells Lamar he needs to do some “Push Ups”

Rap fans waited with bated breath for Drake’s response, and he returned to the beef with not one song, but two, “Push Ups” and “Taylor Made Freestyle,” released on April 19. The Toronto rapper attempts to put Lamar in his place, calling him a “pipsqueak” and rapping, “How the f-ck you big steppin’ with a size-seven men’s on?” Drake also attempts to make fun of Lamar for doing features on pop songs. “Maroon 5 need a verse, you better make it witty/ Then we need a verse for the Swifties," he raps on “Push Ups,” referring to the 2015 remix of Swift’s “Bad Blood” and “Don’t Wanna Know” with Maroon 5 the following year. 

But Lamar isn’t the only person called out on this record. Drake also dissed Future, The Weeknd, Rick Ross, NBA player Ja Morant, Metro Boomin, and Cole on the song.

“Taylor Made Freestyle,” AI Tupac and Snoop Dogg

Following “Push Ups,” Drake briefly released “Taylor Made Freestyle,” sharing the song in a now-deleted Instagram post on April 19 with the caption: “While we wait on you, I guess.” In the song, Drake alleged Lamar did not release a response to his diss track because Taylor Swift had just put out her latest album The Tortured Poets Department . “Now we gotta wait a f-cking week 'cause Taylor Swift is your new top, and if you boutta drop, she gotta approve,” rapped Drake.

Read More: How AI is Wreaking Havoc on the Fanbases of Taylor Swift, Drake, and Other Pop Stars

But the track was short-lived after Drake was served a cease-and-desist letter from Tupac Shakur’s estate for using AI-generated vocals from the rap legend, who died in 1996. Drake was then forced to remove “Taylor Made Freestyle” from all public platforms. The estate said they would have never approved of using Shakur’s voice for the track. 

The song also featured AI vocals from Snoop Dogg, who joked about it on Instagram.

“6:16 in LA” and the multiple meanings behind the title

Lamar dropped a second song in the same week he released “Euphoria,” with multiple possible meanings behind the cryptic title. He released “6:16 in LA” as an Instagram Reel on his page on Friday. The cover art for the song features a single black glove, seemingly a nod to the O.J. Simpson trial —which began on June 16, 1995. Tupac’s birthday is also on June 16, as is Father’s Day this year. It's also the day the television show Euphoria dropped its first episode. There is also a Bible verse, Corinthians 6:16, that could be read as a dig at Drake’s alleged taste in women: “Do you not know that he who unites himself with a prostitute is one with her in body? For it is said, ‘The two will become one flesh.’”

One of the most surprising aspects about the song was the inclusion of Jack Antonoff’s name on the producer credits. The Bleachers frontman is known for working closely with Taylor Swift and hasn’t previously been publicly involved in this rap feud. Lamar digs further into Drake to suggest that the Toronto rapper might have moles on his team, feeding him information.

“Family Matters”

Drake responded to Lamar by questioning the true father of Lamar’s child with fiancé Whitney Alford, and possibly alleging that Lamar is unfaithful and physically abusive in his current relationship in “Family Matters.” “You the Black messiah wifin' up a mixed queen. And hit vanilla cream to help out with your self-esteem,” Drake raps on the track released on May 3. (Lamar has not directly addressed these claims, although he did say in his response track “Meet the Grahams,” “This supposed to be a good exhibition within the game/ But you fucked up the moment you called out my family's name/ Why you had to stoop so low to discredit some decent people?”) 

Later in that verse, Drake specifically names Dave Free, a record executive who works as Lamar’s manager, saying, “I heard that one of 'em little kids might be Dave Free.” Drake also called Lamar and his body of work, which often addresses racism, inauthentic, saying, “Always rappin’ like you ‘bout to get the slaves freed/ You justin actin’ like an activist, it’s make-believe.” 

The music video shows the destruction of a van used in the 2012 album cover of Lamar’s Good Kid, M.A.A.D City . As of Monday morning, the track is #1 on “trending for music ” on YouTube.

“Meet the Grahams”

Less than an hour after Drake released “Family Matters,” Lamar put out “Meet the Grahams.” The track is arguably the most aggressive of songs released in the past few months, and starts with Lamar apologizing to Drake’s son for having him as a father. Lamar then goes on to claim without evidence that Drake takes Ozempic, and used photos of medication with Drake’s legal name, Audrey Drake Graham, on it, as the cover art for the song. (The images have not been verified as legitimate.) He alludes to gossip that Drake has had a Brazilian butt lift (a rumor—which Drake has not directly responded to—that prompted Rick Ross to coin the nickname “BBL Drizzy”), and even mentions the way that Drake hid his son from the public eye. “Don't be ashamed 'bout who you wit', that's how he treat your moms. Don't have a kid to hide, a kid to hide again,” Lamar raps.

In the second verse, Lamar makes severe implications about Drake by comparing him to Hollywood sex offender Harvey Weinstein, saying, “Him and Weinstein should get fucked up in a cell for the rest they life.” (Weinstein’s 2020 rape conviction was recently overturned in New York, which has opened a new chapter in his case.)

Lamar dedicates the third verse to Drake’s daughter, claiming that Drake is “not active” in her life and calling him a “narcissist, misogynist.” Drake denied claims he has a daughter on his Instagram story on Saturday. 

“Not Like Us”

Lamar doubled down on his allegations against Drake, releasing another four-and-a-half-minute track not even a full 24 hours later on Saturday evening. The cover art is allegedly a photo of Drake’s mansion in Toronto with red markers that seem similar to the ones used to mark homes where sex offenders reside. “Say, Drake, I hear you like 'em young,” Lamar rapped. 

He also says that Drake is not a “colleague” but a “colonizer.”

Lamar also called out Drake for using Tupac’s AI voice: “You think the Bay gon' let you disrespect Pac, n---a? I think that Oakland show gon' be your last stop.”

Metro Boomin’s “BBL Drizzy” 

Metro Boomin—one of the producers on “Like That”—put his foot in the game when he shared a post on X about a “BBL Drizzy Beat Giveaway” on May 5. The rapper encouraged fans to rap over the beat, which looks to be a sample of a parody song written by comedian and AI storyteller King Willonious, according to Complex . 

Drake mentioned Metro Boomin by his legal name in “Family Matters,” calling him “lame” and also alleging that he influenced disagreements between Drake and Future. 

Drake commented on an Instagram post sharing one of Metro Boomin’s tweets about him writing , “you just cheffed a beat about my a-s?”

“The Heart Part 6”

The most recent response to the beef came on Sunday night, when Drake released “The Heart Part 6.” In a post to X , he wrote, “And we know you’re dropping [six] minutes after, so instead of posting my address, you have a lot to address.” He denies the allegations that Lamar lobbed at him, saying he purposefully fed Lamar fake information to see if he’d fall for it and tells him that he should get better at fact-checking. Drake called this beef a “good exercise” and laughed it off, suggesting that Lamar would be a “worthy competitor if [he] was really a predator.”

Drake also directly mentioned Stranger Things actor Millie Bobby Brown, saying that he “Only fuckin' with Whitneys, not Millie Bobby Browns, I'd never look twice at no teenager.” This marks at least the second time Drake has responded to online criticism about his friendship with the actress, whom he first met when she was a young teen . Drake previously addressed comments about her in his song “Another Late Night.”

The Drake vs. Kendrick Lamar beef seems to have no end in sight as the two continue to trade disses with ever-increasing severity in the allegations made towards each other.

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Write to Moises Mendez II at [email protected]