An engineer’s perspective. A researcher’s curiosity.

Starting with systems.

My background is in Industrial Engineering, where I became interested in how complex systems can be understood, modeled, and improved. That perspective still shapes how I approach machine learning and software: what is the actual problem, what are the constraints, and what would make the solution useful?

I went on to complete an M.Sc. in Data Science and Big Data at Yıldız Technical University, where my thesis explored deep learning and computer vision for boxing action recognition and next-action prediction. My academic work also includes research on neural approaches to tour demand forecasting.

Moving between ideas and implementation.

Professionally, my work spans conversational AI, retrieval-augmented generation, AI agents, production sequencing, forecasting, and computer vision. I’m interested in the engineering decisions that connect a model or algorithm to the system around it.

Alongside this work, I build independent software. Shopivision, Geodense, MindMuscle AI, and Pebble Route explore different problems, but each gives me a way to work across product thinking, AI, data, and implementation.

Keeping the questions open.

I want to continue working internationally in advanced AI engineering, pursue doctoral research, and develop independent scientific experiments. Robotics, control systems, physics, and biomechanics are areas I’m particularly curious about.

Beyond the screen.

Strength training, kickboxing, and martial arts are part of my life outside engineering. I also enjoy animation and scientific exploration — different ways to study movement, structure, and how things work.