Contact:
jlazarsfeld [at] gmail.com
About:
I am a postdoctoral researcher at SUTD in Singapore
working with Georgios Piliouras and Antonios Varvitsiotis.
I received my PhD in computer science at Yale in May 2024,
where I was advised by James Aspnes. Previously, I was also a
visitor at IST Austria in 2023 and summer 2024, where
I was hosted by Dan Alistarh and Krish Chatterjee.
My research interests are broadly at the intersection
of theoretical computer science and machine learning, including:
- online learning, game theory, decision making, and optimization
- distributed algorithms, opinion dynamics,
and computation in multi-agent settings
- differentially private statistics and optimization
News:
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September 2024: started as a postdoctoral research fellow at SUTD in Singapore.
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June 2024: attended PODC in Nantes, and the GAIMSS summer school
and workshop in Metz.
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April/May 2024: successfully defended my thesis and graduated from Yale.
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December 2023: attended OPT2023 @ NeurIPS
to present our work on decentralized learning dynamics.
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August 2023: presented at the
Yale Theory Student Seminar.
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August 2023: gave a short talk and poster at
WOLA 2023.
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Winter/Spring/Summer 2023: visited
IST Austria, hosted by Dan Alistarh.
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Summer 2022: interned with the privacy-preserving machine learning
research group at Meta in NYC, where I collaborated with Sen Yuan
and Huanyu Zhang.
Publications:
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John Lazarsfeld and Dan Alistarh
Simple Opinion Dynamics for No-Regret Learning
July 2024 -- preprint; preliminary version appeared in OPT workshop at NeurIPS 2023
[ArXiv]
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Dan Alistarh, Krishnendu Chatterjee, Mehrdad Karrabi, and John Lazarsfeld
Game Dynamics and Equilibrium Computation in the Population Protocol Model
PODC 2024
[ArXiv]
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Talley Amir, James Aspnes, Petra Berenbrink, Felix Biermeier, Christopher Hahn,
Dominik Kaaser, and John Lazarsfeld
Fast Convergence of k-Opinion Undecided State Dynamics in the
Population Protocol Model
PODC 2023
[ArXiv]
[Proceedings]
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John Lazarsfeld, Aaron Johnson, and Emmanuel Adeniran
Differentially Private Maximal Information Coefficients
ICML 2022
[ArXiv]
[Proceedings]
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John Lazarsfeld and Aaron Johnson
Consistency of the Maximal Information Coefficient Estimator
July 2021 -- corrects an error in previous work of Reshef et al. (JMLR, 2016)
[ArXiv]
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Talley Amir, James Aspnes, and John Lazarsfeld
Approximate Majority With Catalytic Inputs
OPODIS 2020
[ArXiv]
[Proceedings]
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John Lazarsfeld, Jonathan RodrÃguez, Mert Erden, Yuelin Liu, and Lenore Cowen
Majority Vote Cascading: A Semi-Supervised Framework for Improving
Protein Function Prediction
ACM BCB 2019 -
Companion poster named Best Poster
[Conf. Proceedings]
[Code and Data]
Teaching:
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Yale CPSC 569: Randomized Algorithms
Graduate Teaching Fellow
Spring 2024
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Yale CPSC 565: Distributed Algorithms
Graduate Teaching Fellow
Fall 2023, Fall 2022
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Yale CPSC 365: Introduction to Algorithms
Graduate Teaching Fellow
Spring 2022, Spring 2021
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Yale CPSC 202: Mathematical Tools for Computer Science
Graduate Teaching Fellow
Fall 2021, Fall 2020
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Tufts COMP 160: Introduction to Algorithms
Graduate Teaching Assistant
Spring 2019; Summer 2019
Other:
Member of Yale CS Graduate Student Advisory Council (2022-2024)
Graduate Student Representative on Yale CS Climate & Diversity Committee (2020-2021)
Yale Franklin College Graduate Affiliate (2020-2024)
Last Updated: September 2024