I am a postdoctoral researcher at the Halıcıoğlu Data Science Institute, UC San Diego, working on agentic AI systems for real-world scientific and engineering problems.
My current work focuses on:
- Building agentic frameworks for iterative scientific reasoning, experimentation, and model development
- Developing long-horizon reinforcement learning environments for realistic STEM workflows
- Designing scientific evaluation infrastructure that measures final outcomes, intermediate decisions, trajectories, and computational costs
- Creating interpretable statistical and machine-learning methods for data-intensive scientific research
My background is in experimental particle physics, with research experience across the XENONnT, LEGEND, and KamLAND experiments. My work has involved statistical inference, detector data analysis, signal processing, simulation, and scientific software infrastructure.
I am particularly interested in building open-source tools that make AI agents more reliable, measurable, and useful for scientific discovery.