Welcome! My name is Judah Goldfeder, and I am a Phd student in the Creative Machines Lab at Columbia University, where I am fortunate to be advised by Hod Lipson, and to be a part of the AI Institute in Dynamic Systems, generously funded by the NSF. I am also a Student Researcher at Google AI, and a Research Consultant for Dicta.

Research Interests

I am interested in most aspects of Artificial Intelligence, but some of the topics that interest me most are Reinforcement Learning, Algorithmic Game Theory, Multi-agent AI, Unsupervised Representation Learning, Multi-Task Learning and Geometric Learning. While we are quite far away from any form of AGI, I think these topics are all leading in that direction, which is part of why I find them so exciting.

My work has mostly focused on the following areas:

1. Deep Learning and Neural Network Theory
2. Computer Vision
3. Reinforcement Learning
4. AI for Scientific Discovery
5. AI for Sustainability
6. Robotics
7. Network Science
8. NLP for Low Resource Languages

Experience

Previously, I was a Machine Learning Intern at Facebook AI Research, where I worked on applying Transformers to Graph Neural Networks at scale. I was also a Machine Learning intern at Twitter, where I worked on improving production ads models. Before that, I was a Machine Learning intern at Google AI, where I worked on applying Reinforcement Learning to improve HVAC systems. I also interned at Learn Ventures, an innovative education startup, where I worked on Reinforcement Learning as well as protein folding. I also was a research intern at Bar Ilan University, where I worked with Hillel Kugler on using formal verification to predict gene interaction in cells.