Hao-Lun Hsu

Student

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.

Appointments and Affiliations

  • Student

Contact Information

Research Interests

Decision-making: Reinforcement Learning (RL) and Multi-armed Bandits
Multi-agent: zero-sum game, adversarial learning and network science
Cyber-physical System: robotics, neuromodulation and AR

Awards, Honors, and Distinctions

  • NSF CPS Rising Star. National Science Foundation . 2025
  • NSF-NRT Traineeship in Advancing Surgical Technologies (TAST) Fellow. Duke TAST. 2022
  • Ph.D. Departmental Fellowship. Duke Computer Science. 2022
  • Thank a Teacher Award. Center of Teaching and Learning, Georgia Institute of Technology. 2021

Representative Publications

  • Gazi, Asim H., Michael Chan, Hao-Lun Hsu, J Douglas Bremner, Christopher J. Rozell, and Omer T. Inan. “StressFADS: Learning Latent Autonomic Factors of Stress in the Context of Trauma Recall and Neuromodulation (Accepted).” 2024 IEEE 20th International Conference on Body Sensor Networks (BSN): IEEE, 2024. https://doi.org/10.1109/BSN63547.2024.10780711.
  • Sarikhani, Parisa, Hao-Lun Hsu, Mahmoud Zeydabadinezhad, Yuyu Yao, Mayuresh Kothare, and Babak Mahmoudi. “Reinforcement learning for closed-loop regulation of cardiovascular system with vagus nerve stimulation: a computational study.” Journal of Neural Engineering 21, no. 3 (June 1, 2024): 036027–036027. https://doi.org/10.1088/1741-2552/ad48bb.
  • Jin, T., H. L. Hsu, W. Chang, and P. Xu. “Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs.” In Proceedings of the Aaai Conference on Artificial Intelligence, 38:12956–64, 2024. https://doi.org/10.1609/aaai.v38i11.29193.
  • Hsu, H. L., Q. Gao, and M. Pajic. “ϵ-Neural Thompson Sampling of Deep Brain Stimulation for Parkinson Disease Treatment.” In Proceedings 15th ACM IEEE International Conference on Cyber Physical Systems Iccps 2024, 224–34, 2024. https://doi.org/10.1109/ICCPS61052.2024.00027.
  • Hsu, H. L., H. Meng, S. Luo, J. Dong, V. Tarokh, and M. Pajic. “REFORMA: Robust REinFORceMent Learning via Adaptive Adversary for Drones Flying under Disturbances.” In Proceedings IEEE International Conference on Robotics and Automation, 5169–75, 2024. https://doi.org/10.1109/ICRA57147.2024.10611002.