I am a Computer Science Ph.D. student at Berkeley Artificial Intelligence Research where I am advised by Stuart Russell. Before that, I was a Machine Learning research scientist at Uber ATG. I completed my BS at MIT where I did research with the Flavell, Cocosci and MIT-IBM Watson AI labs.
My research is supported by the Hertz Fellowship.
Interests
- Exploration and intrinsic motivation
- Open-ended continual learning
- Meta-learning
- Hierarchical reinforcement learning
Education
PhD in Computer Science, 2026 (expected)
UC Berkeley
BS in Math with Computer Science, 2018
Massachusetts Institute of Technology
Recent Publications
(2023).
What can AI Learn from Human Exploration? Intrinsically-Motivated Humans and Agents in Open-World Exploration.
Intrinsically Motivated Open-Ended Learning Workshop (Spotlight), NeurIPS 2023.
(2022).
Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement.
ICLR 2023.
(2021).
A Neural Circuit for Flexible Control of Persistent Behavioral States.
eLife 10.
(2021).
Multixnet: Multiclass Multistage Multimodal Motion Prediction.
In 2021 IEEE Intelligent Vehicles Symposium (IV).
(2019).
Analyzing Sketches Around the World with sketch-rnn.
Analytics Vidhya, results selected for display at the AI Art Gallery at NeurIPS 2020.
Contact
Undergrads looking for research experience click here.
- dayan at berkeley dot edu