My research focuses on the application of AI and machine learning in optimization algorithms, deep learning, and natural language processing. I am particularly interested in the theoretical foundations of AI and developing novel algorithms that are both computationally efficient and explainable.
My work in computational mathematics focuses on solving large-scale optimization problems in high-dimensional spaces, including using techniques like Bayesian optimization and probabilistic modeling for computational efficiency.
I am interested in applying data science techniques to large datasets to uncover patterns and insights. My focus is on developing scalable algorithms for data cleaning, analysis, and visualization to support decision-making processes in scientific research and industry.