worrydream.com
dynamicland.org
Technology news and analysis with a focus on founders and startup teams.
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AI safety at Anthropic, on leave from a faculty job at NYU.
Views not employers'.
I think you should join Giving What We Can.
cims.nyu.edu/~sbowman
Reverse engineering neural networks at Anthropic. Previously Distill, OpenAI, Google Brain.Personal account.
What would we need to understand in order to design an amazing future? Ex DeepMind, OpenAI
Human being. Trying to do good. CEO @ Encultured AI. AI Researcher @ UC Berkeley. Listed bday is approximate ;)
Chief Scientist at the UK AI Security Institute (AISI). Previously DeepMind, OpenAI, Google Brain, etc.
PhD student at the University of Pennsylvania. Prev, intern at MSR, currently at Meta FAIR. Interested in reliable and replicable reinforcement learning, robotics and knowledge discovery: https://marcelhussing.github.io/
All posts are my own.
Professor at Penn, Amazon Scholar at AWS. Interested in machine learning, uncertainty quantification, game theory, privacy, fairness, and most of the intersections therein
cs phd @upenn advised by Michael Kearns, Aaron Roth, and Duncan Watts| previously @stanford | she/her
https://psamathe50.github.io/sikatasengupta/
Associate professor at U of Toronto. Computer science and math research: (differentially) private data analysis, geometry, discrepancy, optimization.
Associate Professor of Computer Science at Northeastern University in Boston. Dad. Imposter.
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
Assistant prof at JHU CS. Interested in theory of ML, privacy, cryptography. All cat pictures my own and do not represent the cats of my employer
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
wharton stats phd — ml theory, ml for science
prev: comp neuro, data, physics
working with Edgar Dobriban and Konrad Körding
also some sports (esp. philly! go birds)
PhD student at University of Alberta. Interested in reinforcement learning, imitation learning, machine learning theory, and robotics
https://chanb.github.io/
