Hao-Lun Hsu

Hao-Lun (Howard) Hsu is a Computer Science Ph.D. student at Duke University advised by Professor Miroslav Pajic. His research concerns provably and practical decision-making (e.g., Reinforcement Learning, Multi-armed Bandits), including robustness and safety with applications of robotics and neuromodulation.

Current Appointments & Affiliations

Student Computer Science, Trinity College of Arts & Sciences

Recent Publications

StressFADS: Learning Latent Autonomic Factors of Stress in the Context of Trauma Recall and Neuromodulation

Conference · October 15, 2024 Physiological markers of stress and neuromodulation (e.g., heart rate variability) are often inconsistent when it comes to quantifying changes in autonomic nervous system function. This inconsistency is explained by the autonomic nervous system's output va ... Full text Link to item Cite

Reinforcement learning for closed-loop regulation of cardiovascular system with vagus nerve stimulation: a computational study

Journal Article Journal of Neural Engineering · June 1, 2024 AbstractObjective. Vagus nerve stimulation (VNS) is being investigated as a potential therapy for cardiovascular diseases including heart failure, cardiac arrhyt ... Full text Cite

Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs

Conference Proceedings of the AAAI Conference on Artificial Intelligence · March 25, 2024 We study the multi-agent multi-armed bandit (MAMAB) problem, where agents are factored into overlapping groups. Each group represents a hyperedge, forming a hypergraph over the agents. At each round of interaction, the learner pulls a joint arm (composed o ... Full text Cite

View All Publications

External Links

Google Scholar Personal Website