CV

Summary

I aim to build a career at the intersection of optimization, computational physics, and AI, focusing on mathematical modeling, large-scale algorithms, and efficient methods that advance both theory and applications.

Education

Courses Taken

During PhD: Advanced Convex Optimization (E0 350), Pattern Recognition and Neural Networks (E1 213), Detection and Estimation Theory (E1 244), Optimization for Machine Learning and Data Science (E1 260), Signal Processing in Practice (E9 222), Data Analytics (E0 259), Real Analysis (MA 221), Linear and Nonlinear Optimization (E1 251), Random Processes (E2 202), Time-Frequency Analysis (E9 213), Linear Algebra and Its Applications (E0 298), Digital Image Processing (E9 219), Topics in Stochastic Approximation Algorithms (E1 396).

During Bachelor’s: Mathematics I–III, Introduction to Statistical & Probabilistic Methods (Hons.), Advanced Computing Techniques I & II, Non-linear & Optimal Control (Hons.), etc.

Skills

Certifications

Publications

Projects

Volunteering

Test Achievements

Personal Skills