The Vector Institute is dedicated to AI, excelling in machine & deep learning research. AI-generated content will be disclosed. FR: @institutvecteur.bsky.social
⛷️ ML Theorist carving equations and mountain trails | 🚴♂️ Biker, Climber, Adventurer | 🧠 Reinforcement Learning: Always seeking higher peaks, steeper walls and better policies.
https://ualberta.ca/~szepesva
Anti-cynic. Towards a weirder future. Reinforcement Learning, Autonomous Vehicles, transportation systems, the works. Asst. Prof at NYU
https://emerge-lab.github.io
https://www.admonymous.co/eugenevinitsky
PhD student in machine learning at TU Wien.
learning theory | graphs
https://maxthiessen.github.io
Researcher in ML and Privacy.
PhD @UofT & @VectorInst. previously Research Intern @Google and @ServiceNowRSRCH
https://mhaghifam.github.io/mahdihaghifam/
Director, Princeton Language and Intelligence. Professor of CS.
full-time ML theory nerd, part-time AI-non enthusiast
Blog: https://argmin.substack.com/
Webpage: https://people.eecs.berkeley.edu/~brecht/
Postdoc researcher at IDEAL Institute in Chicago, hosted by UIC and TTIC.
My research interests are in machine learning theory, data-driven sequential decision-making, and theoretical computer science.
https://www.idanattias.com/
Associate Professor at Princeton
Machine Learning Researcher
I work on AI at OpenAI.
Former VP AI and Distinguished Scientist at Microsoft.
PhD student @UofT and @Vector, Deep Learning Theory
https://www.cs.toronto.edu/~chuning/
ML researcher | PhD candidate @ UofT + Vector Institute
I am interested in parsimonious neural network training and inference.
Principal Researcher in AI/ML/RL Theory @ Microsoft Research NE/NYC. Previously @ MIT, Cornell. http://dylanfoster.net
RL Theory Lecture Notes: https://arxiv.org/abs/2312.16730
Assistant Prof at UWaterloo Statistics and Actuarial Science
Faculty Affiliate at the Vector Institute
https://www.math.uwaterloo.ca/~jnegrea/
Assistant Professor @UWaterloo Statistics and @VectorInst | Prev: Postdoc @Princeton PhD @UofTStatSci
https://mufan-li.github.io/
Research Director, Founding Faculty, Canada CIFAR AI Chair @VectorInst.
Full Prof @UofT - Statistics and Computer Sci. (x-appt) danroy.org
I study assumption-free prediction and decision making under uncertainty, with inference emerging from optimality.
professor of EECS at MIT, currently visiting IAS. working in theoretical computer science namely algorithm design, complexity theory, circuit complexity, etc.
i'll let you know when P != NP is proved (and when it's not)
Econ prof at Harvard. (Mechanism design, market design, behavioral theory.) www.shengwu.li
Assistant Prof of CS at the University of Waterloo, Faculty and Canada CIFAR AI Chair at the Vector Institute. Joining NYU Courant in September 2026. Co-EiC of TMLR. My group is The Salon. Privacy, robustness, machine learning.
http://www.gautamkamath.com
