I am a PhD candidate in Computer Science at the University of Arizona, co-advised by Kwang-Sung Jun and Chicheng Zhang. My research centers on sequential decision-making, including bandit algorithms, partial monitoring, and reinforcement learning, with applications to recommender systems; I am also interested in leveraging these theoretical tools to fine-tune and improve large language models. I received my B.Sc. in Electronics and Telecommunication Engineering from the University of Moratuwa. During my undergraduate studies, I completed a summer research internship at Nanyang Technological University under the supervision of Guohua Wang, where I worked on blind channel equalization in the presence of co-channel interference.
Most recent publications on
Google Scholar.
‡ indicates equal contribution.
Fixing the Loose Brake: Exponential-Tailed Stopping Time in Best Arm Identification
Kapilan Balagopalan‡, Tuan Ngo Nguyen‡, Yao Zhao‡, Kwang-Sung Jun
ICML'25: International Conference on Machine Learning. 2025.
Minimum Empirical Divergence for Sub-Gaussian Linear Bandits
Kapilan Balagopalan, Kwang-Sung Jun
AISTATS'25: International Conference on Artificial Intelligence and Statistics. 2025.
Blind Equalization in the Presence of Co-channel Interference Based on Higher-Order Statistics
Guohua Wang, Kapilan Balagopalan, Sirajudeen Gulam Razul, Shang-Kee Ting, Chong Meng Samson See
Circuits, Systems, and Signal Processing. 2018.
Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors
Kapilan Balagopalan‡, Yinan Li‡, Yao Zhao, Tuan Ngo Nguyen, Anton Daitche, Houssam Nassif, Kwang-Sung Jun
(under review) ICML'26: International Conference on Machine Learning. 2026.
Full Resume in PDF.