mathias lécuyer

CS PhD student @ Columbia University

Overview

Mathias Lecuyer
I am a CS PhD candidate at Columbia under the supervision of Roxana Geambasu, Augustin Chaintreau, and Daniel Hsu. My research interests span broad areas of computer science, including systems, privacy, security, statistics, causal inference, and machine learning. My ongoing work focuses on enabling the promises of ML driven ecosystems without imposing undue risks to individuals. I also spend time rock climbing, and love to read on topics ranging from econ to history and ecology.

Research

I am on the academic job market this year. Here are my application materials:

My research addresses the new system challenges and opportunities introduced by the data and artificial intelligence revolutions. While data-driven systems can yield social and economic benefits, they also open new security and privacy threats, and their opacity can undermine users’ trust. To address these challenges, I design, implement, and evaluate rigorous, theory-backed systems that are both practical and provide provable guarantees of security, privacy, and statistical soundness. To provide these guarantees, my system designs leverage theory from statistics, machine learning, causal inference, and differential privacy. I am fortunate to work with multiple great collaborators including Riley Spahn, Vaggelis Atlidakis, and Brian Goodchild from Columbia, and Siddhartha Sen, Amit Sharma, and Alex Slivkins from MSR.

Projects

Recent talks

Publications