I'm on the Faculty Market in Computer Science and Machine Learning!

Please see my cv, research statement, and teaching statement.


I am a fifth-year PhD student at MIT, where I empirically study deep learning with Prof. Michael Carbin. My current research focus is on developing experimental methods for understanding the behavior of the neural networks we use in practice. My thesis is about my work on the lottery ticket hypothesis, where I study the capacity necessary for neural networks to learn in practice.

2016-21: PhD Computer Science  -  Machine Learning Mass. Institute of Tech.
2014-15: MSE Computer Science  -  Programming Languages Princeton University
2011-14: BSE Computer Science (Highest Honors) Princeton University
Work Experience
2019-20: Researcher Topics in the Science of Deep Learning Facebook AI Research
2019: Intern The Early Phase of Neural Network Training Facebook AI Research
2018-19: Researcher Sparsity for NLP Transfer Learning Google Brain
2018: Intern Program Synthesis Google Brain
2017: Intern Fully Homomorphic Encryption Google
2015-16: Fellow Staff Technologist, Center on Privacy and Technology Georgetown Law
2014: Intern Encryption Key Management Infrastructure Google
2013: Intern Project Siena (Pre-Beta) Compiler Team Microsoft
2019: Professor Adjunct Professor of Law, Lead Instructor (Programming for Lawyers) Georgetown Law
2018: TA Teaching Assistant (Computer and Network Security) Mass. Institute of Tech.
2016: Professor Adjunct Professor of Law, Co-Instructor (Programming for Lawyers) Georgetown Law
2015: Award Departmental Award for Excellence in Graduate Teaching Princeton University
2015: TA Teaching Assistant (General Computer Science - COS126) Princeton University
2014: Award Engineering Council Teaching Award Princeton University
2014: TA Teaching Assistant (Information Security - COS432) Princeton University
2014: Award Departmental Award for Excellence in Undergraduate Teaching Princeton University
2020 Invited Expert: Network of Experts on AI OECD
2018-19 Invited Expert: Expert Group on Artificial Intelligence OECD
Open-Source Code
2020 OpenLTH: A Framework for Lottery Tickets and Beyond Facebook AI Research
2018 An Implementation of the Lottery Ticket Hypothesis Google Brain
2017 SHELL: Simple Homomorphic Encryption Library with Lattices Google
Papers & Publications (* = First Author)
2021 Pruning Neural Networks at Initialization: Why Are We Missing the Mark?* ICLR Poster
Training BatchNorm and Only BatchNorm* ICLR Poster
2020 The Lottery Ticket Hypothesis for Pre-Trained BERT Networks NeurIPS Poster
On the Predictability of Pruning Across Scales Arxiv
Linear Mode Connectivity and the Lottery Ticket Hypothesis* ICML Talk
Comparing Fine-Tuning and Rewinding in Neural Network Pruning ICLR Oral
The Early Phase of Neural Network Training* ICLR Poster
What is the State of Neural Network Pruning? MLSys
Revisiting "Qualitatively Characterizing Neural Network Optimization Problems"* NeurIPS DL-IG Workshop
Trade-Offs of Local SGD at Scale: An Empirical Study NeurIPS OptiML Workshop
Are All Negatives Created Equal in Contrastive Instance Discrimination? Arxiv
2019 Stabilizing the Lottery Ticket Hypothesis/The LTH at Scale* Arxiv
Dissecting Pruned Neural Networks* ICLR Debugging Workshop
The Lottery Ticket Hypothesis* ICLR Oral & Best Paper
2018 Practical Accountability of Secret Processes* Usenix Security
Desirable Inefficiency* Florida Law Review
2016 The Perpetual Lineup: Unregulated Police Face Recognition in America* Investigative Report
How Russia's New Facial Recognition App Could End Online Anonymity* The Atlantic
Facial-Recognition Software Might Have a Racial Bias Problem* The Atlantic
Example-Directed Synthesis: A Type-Theoretic Interpretation* POPL
2015 Type-Directed Synthesis of Products* MSE Thesis
2014 Programming Recursive Software-Defined Networks* BSE Thesis
Why King George III Can Encrypt Course Project
In Progress Computer Programming for Lawyers (Textbook)* No Starch Press
Selected Press
2021 At Dubai Airport, Travelers' Eyes Become Their Passports Associated Press
2020 Facial Recognition Last Week Tonight
2019 New Way to Build Tiny Neural Nets Could Put Powerful AI on Your Phone The MIT Tech Review
How China is Using AI to Profile a Minority The New York Times
2018 Public Accountability of Secret Processes BBC Radio
An Airline Scans Your Face...But Few Rules Govern Where Your Data Goes The New York Times
Newspaper Shooting Shows Widening Use of Facial Recognition The New York Times
US Schools Turn to Facial Recognition to Help Stop Gun Attacks CBC Radio
2017 Technology Is Biased Too. How Do We Fix It? FiveThirtyEight
Where Non-Technies can Get With the Programming The New York Times
2016 Researchers Find Flaws in Police Facial Recognition Technology NPR Morning Edition
Government Lawyers Don't Understand the Internet. That's a Problem The Washington Post