Sridhar Mahadevan
Research Professor
Director, Adobe Research
Co-Director, Autonomous Learning Laboratory
Research Interests
Artificial Intelligence
Applied Category Theory
Machine Learning
CONTACT INFO:
firstname.i.lastname AT gmail
Administrative Assistant: Sarah Byrne
I am currently a Research Professor at the Manning College of Information and Computer Sciences, and a Director at Adobe Research in the San Francisco Bay Area. At Adobe, I lead a team of interdisciplinary researchers in generative AI, machine learning, causal inference, graph data mining, statistics, and theoretical CS. My current research involves developing a new framework for universal AI, which applies category theory to artificial general intelligence (AGI).
Selected Preprints and Invited Talks
Sridhar Mahadevan, Universal Causality, Entropy, vol. 25, Number 4, March 2023. (also published as part of a special issue on Causal Inference for Heterogeneous Data and Information Theory in book format freely downloadable at https://www.mdpi.com/books/book/7572)
Sridhar Mahadevan, Universal Representations for AI, Invited Talk, Department of Computer Science, Oregon State University, September 23rd, 2022
Sridhar Mahadevan, Unifying Causal Inference and Reinforcement Learning using Higher-order Category Theory, Arxiv, September 2022
Sridhar Mahadevan, Categoroids: Universal Conditional Independence, Arxiv, July 2022
Sridhar Mahadevan, Universal Decision Models , Invited Talk, Indian Institute of Science, October 23rd, 2021
Sridhar Mahadevan, Universal Decision Models, Arxiv, 2021
Sridhar Mahadevan, Causal Homotopy, Arxiv, 2021.
