Research and Academic Experience
My research focuses on the design, analysis, and implementation of optimization algorithms, with applications in machine learning, optimal transport, and distributed computation.
Research Experience
Doctoral Researcher
Department of Mathematical Sciences, Rensselaer Polytechnic Institute
May 2020 – July 2026
- Designed and analyzed the Damped Proximal Augmented Lagrangian Method (DPALM), a state-of-the-art optimization algorithm for constrained nonconvex problems.
- Evaluated the theoretical complexity and computational performance of DPALM in applications involving bias reduction in machine learning and robustness enhancement.
- Developed methods for solving dynamic optimal transport problems with applications in generative artificial intelligence and scientific computing.
- Designed distributed optimization frameworks to improve computational efficiency in terms of both execution time and memory requirements.
- Implemented optimization algorithms in Python using MPI and NumPy for parallel and distributed computation.
Research Interests
Constrained Optimization
First-Order Methods
Nonconvex Optimization
Dynamic Optimal Transport
Distributed Optimization
Convergence Analysis
Machine Learning
Causal Inference