Contact:

About:

My research interests are broadly in algorithms, TCS, and data science, including:

• distributed gossip algorithms and population protocols
• differential privacy
• learning theory

News:

For the Winter/Spring 2023 semester, I will be a visitor at IST Austria working with Dan Alistarh.

In Summer 2022, I interned with the privacy-preserving machine learning research group at Meta in NYC, where I collaborated with Sen Yuan and Huanyu Zhang.

Publications:

• 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
  January 2023 -- to appear at PODC 2023
  [ArXiv]
• John Lazarsfeld, Aaron Johnson, and Emmanuel Adeniran
  Differentially Private Maximal Information Coefficients
  ICML 2022
  [ArXiv] [Proceedings]
• 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]
• Talley Amir, James Aspnes, and John Lazarsfeld
  Approximate Majority With Catalytic Inputs
  OPODIS 2020
  [ArXiv] [Proceedings]
• John Lazarsfeld, Jonathan Rodríguez, 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:

• Yale CPSC 565: Distributed Algorithms
  Graduate Teaching Fellow
  Fall 2023
• Yale CPSC 365: Introduction to Algorithms
  Graduate Teaching Fellow
  Spring 2022, Spring 2021
• Yale CPSC 202: Mathematical Tools for Computer Science
  Graduate Teaching Fellow
  Fall 2021, Fall 2020
• Tufts COMP 160: Introduction to Algorithms
  Graduate Teaching Assistant
  Spring 2019; Summer 2019

Other: