Siddharth Mitra

I am a PhD student at Yale University in the Department of Computer Science where I am lucky to be advised by Andre Wibisono.

My research focuses on the design and analysis of algorithms for sampling and optimization.

Prior to this, I was an undergraduate and masters student at the Chennai Mathematical Institute as well as a visiting student at the Indian Institute of Science, Bangalore. During this time, I worked with Aditya Gopalan, Himanshu Tyagi, and KV Subrahmanyam.

I can be reached at siddharth.mitra <at> yale <dot> edu.

My Google Scholar.

Research

Authors are listed in alphabetical order, unless denoted by (*).

Accelerated Convex Optimization via Hamiltonian Dynamics with Deterministic Integration Time
Xiuyuan Wang (*), Vishwak Srinivasan (*), Qiang Fu, Siddharth Mitra, Ashia Wilson, and Andre Wibisono
Conference on Learning Theory (COLT), 2026.

Tail-Sensitive KL and Rényi Convergence of Unadjusted Hamiltonian Monte Carlo via One-Shot Couplings
Nawaf Bou-Rabee, Siddharth Mitra, and Andre Wibisono
Preliminary version at DynaFront 2025.
[arXiv]

Characterizing Dependence of Samples along the Langevin Dynamics and Algorithms via Contraction of Φ-Mutual Information
Jiaming Liang, Siddharth Mitra, and Andre Wibisono
IEEE Transactions on Information Theory, 2026.
[IEEE-IT]

On the Convergence of Min-Max Langevin Dynamics and Algorithm
Yang Cai, Siddharth Mitra, Xiuyuan Wang, and Andre Wibisono
Conference on Learning Theory (COLT), 2025.
[arXiv] [COLT 2025]

Characterizing Dependence of Samples along the Langevin Dynamics and Algorithms via Contraction of Φ-Mutual Information
Jiaming Liang, Siddharth Mitra, and Andre Wibisono
Conference on Learning Theory (COLT), 2025.
[arXiv] [COLT 2025 (Extended Abstract)]

Fast Convergence of Φ-Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler
Siddharth Mitra and Andre Wibisono
International Conference on Algorithmic Learning Theory (ALT), 2025.
[arXiv] [ALT 2025]

Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning
Amin Karbasi, Nikki Kuang, Yian Ma, and Siddharth Mitra
International Conference on Machine Learning (ICML), 2023.
[arXiv] [ICML 2023]

Submodular + Concave
Siddharth Mitra (*), Moran Feldman, and Amin Karbasi
Neural Information Processing Systems (NeurIPS), 2021.
[arXiv] [NeurIPS 2021]

On Adaptivity in Information-constrained Online Learning
Siddharth Mitra (*) and Aditya Gopalan
AAAI Conference on Artificial Intelligence (AAAI), 2020.
Preliminary version at OPT 2019.
[arXiv] [AAAI 2020]