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 | | | Sequential Decision Learning for Social Good and Fairness |  | LI Dexun PhD Candidate
School of Computing and Information Systems
Singapore Management University
| Research Area Dissertation Committee Research Advisor Dissertation Committee Member External Member - Arunesh SINHA, Assistant Professor, Department of Management Science & Information Systems, Rutgers Business School, Rutgers University
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| | Date 12 July 2024 (Friday) | Time 8:00am – 9:00am | Venue Meeting room 5.1, Level 5
School of Computing and Information Systems 1, Singapore Management University, 80 Stamford Road Singapore 178902 | Please register by 11 July 2024. We look forward to seeing you at this research seminar. 
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| | ABOUT THE TALK This thesis tackles fair sequential decision learning in AI for social good, focusing on Restless Multi-Armed Bandits (RMAB) and Reinforcement Learning (RL). The study primarily addresses the challenges of resource constraints, proposing scalable algorithms for fair resource allocation in public health interventions, efficient learning for influence maximization in social networks, and a hierarchical framework to reduce training costs while ensuring fairness and effectiveness in resource-limited environments. | | | ABOUT THE SPEAKER Dexun LI is a Ph.D. candidate in Computer Science, supervised by Prof. Pradeep VARAKANTHAM. His research interests include Reinforcement Learning and Optimization, with a current focus on unsupervised environment design, RLHF, and LLMs. |
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