Research Experience
Doctoral Researcher, Dept. of Mathematical Sciences, RPI (May 2020 – Present)
- Designed and analyzed a state-of-the-art optimization algorithm, Damped Proximal Augmented Lagrangian Method (DPALM), to improve convergence speed in nonconvex problems.
- Evaluated complexity and performance of DPALM in applications including bias reduction in machine learning and robustness enhancement.
- Solved dynamic optimal transport problems with real-world applications in generative AI using decentralized optimization techniques.
- Implemented algorithms in Python using MPI and Numpy for distributed computation.
Research Interests
- Constrained Optimization Algorithms
- First-order Methods & Nonconvex Optimization
- Dynamic Optimal Transport Problems
- Distributed Optimization
- Convergence Analysis