Research Interests

Current Research Interests

1. Theory of Optimization (Convex , Non-Convex, and Distributed).

2. SGD Generalisation via SDEs and Markov process Theory.

3. Explicit and Implicit Bias in Optimization Algorithm.

4. Sampling from General Distributions (Heavy-tailed, Multimodal, and Discrete) and Optimization.

5. Statistical Learning beyond the Standard Models and Assumptions (Non-iid data, Heavy-tailed Noise, and Distribution Shift).

6. Learning under resource constraints (Active Learning, and Coresets).

7. Reinforcement learning and Optimization.

8. Machine learning for healthcare applications.

Past Research Works

1. Convex optimization theory.

2. Kernel Methods.

3. Learning with distributions.

4. Non-parametric methods.

5. Computer vision