Scholar
Udari Madhushani Sehwag
Google Scholar ID: sN7grTMAAAAJ
Research Scientist, Scale AI
Citations & Impact
Citations
528
H-index
12
i10-index
13
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Paper on 'A Heterogeneous Agent Model of Mortgage Servicing: An Income-based Relief Analysis' at AIFinSi workshop, AAAI 2024, February 2024
- Paper on 'O3D: Offline Data-driven Discovery and Distillation for Sequential Decision-Making with Large Language Models' at FMDM workshop, NeurIPS 2023, December 2023
- Defended PhD, July 2023
- Paper on 'Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas' at ALA workshop, AAMAS 2023, May 2023
- Presented 'On Using Hamiltonian Monte Carlo Sampling for Reinforcement Learning' at CDC 2022, December 2022
- Organized a PNAS special issue symposium on 'Collective Artificial Intelligence and Evolutionary Dynamics', December 2022
- Finished summer internship (Research Scientist Intern: Game Theory and Multi-agent team) at Deepmind, September 2022
- Paper on 'A Regret Minimization Approach to Multi-Agent Control' at ICML 2022, July 2022
- Paper on 'Provably Efficient Multi-Agent Reinforcement Learning with Fully Decentralized Communication' at ACC 2022, June 2021
- Presented 'One More Step Towards Reality: Cooperative Bandits with Imperfect Communication' at NeurIPS 2021, December 2021
- Finished summer internship (Research Scientist Intern: FAIR labs) at Meta AI Research, August 2021
- Presented 'Distributed Bandits: Probabilistic Communication on d-regular Graphs' and 'Cost-effective Communication Strategies for Distributed Learning Systems' at ECC 2021, June 2021
- Presented 'Heterogeneous Explore-Exploit Strategies on Multi-Star Networks' at ACC 2021, May 2021
- Presented 'It Doesn't Get Better and Here's Why: A Fundamental Drawback in Natural Extensions of UCB to Multi-agent Bandits' at ICBINB workshop, NeurIPS 2020, December 2020
- Paper 'Heterogeneous Explore-Exploit Strategies on Multi-Star Networks' accepted to IEEE Control Systems Letters, November 2020
- Received Britt and Eli Harari Fellowship from the Department of Mechanical and Aerospace Engineering, Princeton University, September 2020
- Finished summer internship (Graduate Intern: AI/Deep Learning for Predictive Analytics) at Siemens, August 2020
- Presented 'A Dynamic Observation Strategy for Multi-agent Multi-armed Bandit Problem' at ECC 2020, May 2020
- Presented 'Distributed Learning: Sequential Decision Making in Resource-Constrained Environments' at PML4DC workshop, ICLR 2020, April 2020
- Received Larisse Rosentweig Klein Memorial Award from the Department of Mechanical and Aerospace Engineering, Princeton University, September 2019
Research Experience
- Visiting Researcher, Stanford University, August 2023 - Present
- Research Scientist, JPMorgan AI Research, July 2023 - April 2025
- Graduate Student, Princeton University, September 2017 - May 2023
- Research Scientist Intern, Deepmind, May 2022 - September 2022
- Research Scientist Intern, FAIR, May 2021 - August 2021
- Summer Research Intern, Siemens, May 2020 - August 2020
Education
- PhD from Princeton University (2017-2023), advised by Prof. Naomi Leonard; Undergraduate from University of Peradeniya, Sri Lanka.
Background
- Research interests include enhancing the capabilities of AI agents, frontier safety, and scalable oversight. Focuses on developing capable and aligned AI agents safely and responsibly.
Co-authors