Background

There is a particular kind of problem that refuses to stay inside boundaries. It begins as an optimization model, grows into a system of interacting decisions, and eventually reveals itself as something deeply connected to real-world constraints.

These are precisely the problems that motivate me. My master's research focused on the unit commitment problem in power systems, where I developed and implemented hybrid evolutionary algorithms for mixed-integer nonlinear programming and multi-objective security-constrained optimization.

My academic background is rooted in applied mathematics, computer science, power systems and optimization. Through this work, I explored how theoretical rigor meets computational practicality. How models must adapt when confronted with uncertainty, scalability issues, and multiobjective trade-offs. What started as solving structured problems quickly evolved into an interest in systems where multiple optimization paradigms must coexist and inform one another.

I see research not as an isolated pursuit but as an evolving dialogue between methods, disciplines, and perspectives. I am confident that my background, curiosity, and commitment to interdisciplinary problem-solving make me motivated to grow within an environment that challenges conventional thinking and pushes the boundaries of optimization research.