Scholar
Kavosh Asadi
Google Scholar ID: -2qyBJEAAAAJ
Meta
Citations & Impact
Citations
3,027
H-index
15
i10-index
19
Publications
20
Co-authors
20
list available
Publications
Resume (English only)
Academic Achievements
- Published over a dozen papers at top-tier AI conferences including NeurIPS, ICML, ICLR, AAAI, and ACL
- ICML 2024: Paper on learning the target network in function space accepted
- ICLR 2024: Paper on foundation models for continual learning accepted
- NeurIPS 2023: Two papers accepted
- RLC (first Reinforcement Learning Conference): Paper on fairness in RL accepted
- NeurIPS 2022: Two papers accepted
- AAAI 2021: Two papers accepted
- NeurIPS 2021: One paper accepted
- AISTATS 2022: One paper accepted
- Co-authored the RL chapter in the D2L (Dive into Deep Learning) book
Research Experience
- 2025–Present: Senior Scientist at Meta’s RL team
- 2020–2025: Scientist at Amazon (Senior from 2024)
- Gave a talk at Seattle Mind and Machines meetup (UW)
- Gave a talk at Amazon’s RL reading group
- Guest lecturer for Harvard’s ML class
Background
- AI scientist aiming to understand the computational principles underlying intelligence
- Focuses on agents that interact with sequential environments and improve behavior through trial and error—i.e., the reinforcement learning problem
- Academically interested in the optimization problem in value function learning
- Applies research to developing assistive AI agents that interact with humans and learn from feedback
- Aspires to build AI agents that co-exist with humans and help them live their best lives
Miscellany
- Moved from Oahu, Hawaii to Seattle, WA
- Moved from SF Bay Area to work remotely from Hawaii
- Moved from Providence, RI to SF Bay Area
- Currently based in the Bay Area working at Meta
- Open to connecting with AI scientists, engineers, and students via email (firstname@alumni.brown.edu)
