My research focuses on developing theory and algorithms for challenging optimization problems in data science and machine learning. Our perspective differs from the traditional black-box system design which considers modeling and solving an optimization problem as separate subjects. Instead, we benefit from an end-to-end view of problem models and computational methods for solving them, which presents new opportunities and trade-offs for designing novel algorithms with theoretical and practical impact.
I completed my PhD at Ecole Polytechnique Federale de Lausanne (EPFL) in Computer and Communication Sciences (EDIC) under the supervision of Prof. Volkan Cevher, and my postdoctoral fellowship at Massachusetts Institute of Technology (MIT) in the Laboratory for Information and Decision Systems (LIDS) hosted by Prof. Suvrit Sra. My PhD dissertation entitled “Scalable Convex Optimization Methods for Semidefinite Programming” was honored with a Thesis Distinction by the EDIC program committee. I received my double-major BSc degrees in Electrical and Electronics Engineering and in Physics from the Middle East Technical University in Turkey.