Colloquium Spring 2022

Past Events

• JUN 24
  12PM, Online
  Statistical models for large-scale genomic data
  Sriram Sankararaman
• APR 19
  2PM, 60 Fifth Avenue 150
  On the Benefits of Convolutional Models: a Kernel Perspective
  Alberto Bietti, NYU Center for Data Science
• APR 8
  11AM, 60 Fifth Avenue 150
  TBA
  Suguman Bansal, University of Pennsylvania
• APR 7
  11:30AM, 60 Fifth Avenue 150
  Machine Learning Parallelization Could Be Automated, Performant, and Easy-to-use.
  Hao Zhang, University of California, Berkeley
• APR 6
  11AM, 370 Jay St
  Principled Algorithm Design in the Era of Deep Learning
  Surbhi Goel, Microsoft Research
• APR 5
  2PM, 60 Fifth Avenue 150
  Learning-Based Program Synthesis: Learning for Program Synthesis and Program Synthesis for Learning
  Xinyun Chen, UC Berkeley
• APR 4
  2PM, 60 Fifth Avenue 150
  Optimal Parallel Optimization Algorithms for Machine Learning
  Blake Woodworth, Inria
• APR 1
  11AM, 60 Fifth Avenue 150
  Verifying Concurrent, Crash-Safe Systems
  Joseph Tassarotti, Boston College
• MAR 31
  11:30AM, 60 Fifth Avenue 150
  Learning Structured World Models From and For Physical Interactions
  Yunzhu Li, MIT
• MAR 30
  2PM, 60 Fifth Avenue 150
  Automated Analysis and Implementation for Modern Networks
  Mina Tahmasbi Arashloo, Cornell University
• MAR 30
  12PM, Online
  Perceiving the World in 2D and 3D
  Georgia Gkioxari, Meta AI
• MAR 29
  2PM, 60 Fifth Avenue 150
  Towards Scalable Representation Learning for Visual Recognition
  Saining Xie, Facebook AI Research
• MAR 29
  11AM, 370 Jay St
  Learning 3D representations with minimal supervision
  Yue Wang, MIT
• MAR 28
  2PM, 60 Fifth Avenue 150
  Optimizing CPU Efficiency and Tail Latency in Datacenters
  Amy Ousterhout, UC Berkeley
• MAR 24
  2PM, 60 Fifth Avenue 150
  Optimization-in-the-loop AI for energy and climate
  Priya Donti, Carnegie Mellon University
• MAR 23
  2PM, 60 Fifth Avenue 150
  Trustworthy Deep Learning: methods, systems and theory
  Matthew Mirman, ETH Zürich
• MAR 21
  2PM, 60 Fifth Avenue 150
  Euclidean Deep Learning Models for 3D Structures and Interactions of Molecules
  Octavian Ganea, MIT
• MAR 11
  11AM, 60 Fifth Avenue 150
  How to handle Biased Data and Multiple Agents in Machine Learning?
  Manolis Zampetakis, University of California, Berkeley
• MAR 9
  2PM, 60 Fifth Avenue 150
  An algorithmic safety view of learning in healthcare
  Shalmali Joshi, Harvard University
• MAR 7
  2PM, 60 Fifth Avenue 150
  Foundations of Cryptographic Proof Systems
  Alex Lombardi, MIT
• MAR 4
  11AM, 60 Fifth Avenue 150
  Formal verification of a concurrent file system
  Tej Chajed, MIT
• MAR 2
  2PM, 60 Fifth Avenue 150
  Making Data Part of Data Structure Design
  Brian Hentschel, Harvard University
• FEB 28
  2PM, 60 Fifth Avenue 150
  Addressing regulatory challenges for AI in healthcare: Building a safe and effective machine learning life cycle
  Adarsh Subbaswamy, Johns Hopkins University
• FEB 22
  11AM, 60 Fifth Avenue 150
  Leveraging over-provisioned cloud networks for next-generation services
  Rachee Singh, Microsoft Azure for Operators