Meet the Fellows Welcome Event

Feb 11, 2022

Friday, February 11th, 2022
10:00 am – 10:10 am		Efficient Universal Estimators For Symmetric Property Estimation Kirankumar Shiragur (Stanford University)
10:10 am – 10:20 am		Mechanism Design Via Machine Learning: Overfitting, Incentives, and Privacy Ellen Vitercik (UC Berkeley)
10:20 am – 10:30 am		Fair And Reliable Machine Learning For High-Stakes Applications:approaches Using Information Theory Sanghamitra Dutta (JP Morgan)
10:30 am – 10:40 am		Information, Learning, And Incentive Design For Societal Networks Manxi Wu (UC Berkeley)
10:50 am – 11:20 am		Break
11:20 am – 11:30 am		Causal Inference And Data-Driven Decision-Making Angela Zhou (UC Berkeley)
11:30 am – 11:40 am		Stabilizing Q-Learning With Linear Architectures For Provable Efficient Learning Andrea Zanette (UC Berkeley)
11:40 am – 11:50 am		Causal Inference With Corrupted Data: Measurement Error, Missing Values, Discretization, And Differential Privacy Rahul Singh (MIT)
12:00 pm – 1:30 pm		Lunch
1:30 pm – 1:40 pm		Choosing Between Dags Can Be Hard Richard Guo (University of Cambridge)
1:40 pm – 1:50 pm		Fundamental Limits Of Learning In Data-Driven Problems Yanjun Han (Simons Institute)
1:50 pm – 2:00 pm		Algorithmic Advances For The Design And Analysis Of Randomized Control Trials Christopher Harshaw (Yale)
2:00 pm – 2:10 pm		Multi-Agent Reinforcement Learning In Stochastic Games: From Alphago To Robust Control Kaiqing Zhang (MIT)
2:20 pm – 2:40 pm		Break
2:40 pm – 2:50 pm		Learning In The Presence Of Strategic Agents: Dynamics, Equilibria, And Convergence Eric Mazumdar (Caltech)
2:50 pm – 3:00 pm		Causal Inference For Socio-Economic & Engineering Systems Anish Agarwal (MIT EECS)
3:00 pm – 3:10 pm		Teamwork Makes The Von Neumann Work: Two Team Zero Sum Games Emmanouil Vlatakis (Columbia University)
3:10 pm – 3:20 pm		Nonparametric Density Estimation and Convergence of GANs under Besov IPMs Ananya Uppal (University of Texas Austin)
3:20 pm – 4:20 pm		Reception