I received my PhD in Physics in Summer 2025, which I pursued at TU Dresden and Stanford University, fortunate to have been advised by Karl Leo and Alberto Salleo. My research focused on semiconductor thermodynamics, specifically for carbon-based transistors in unconventional computing. I derived theoretical predictions and validated them experimentally, developed fitting algorithms for a quantum-mechanical model from detector data, and built a PyTorch tensor framework that, for the first time, unifies equilibrium and non-equilibrium data. I am very grateful to have received the Best PhD Thesis Award in November 2025 for this work.

During my undergraduate studies, I specialized in molecular-dynamics simulations and worked on neural interfaces with Tsuyoshi Sekitani in Osaka, Japan. I also completed a second Master’s degree in Economics during the early years of my PhD, which was a goal I had long set for myself. I see economics as the most powerful framework for understanding human behavior, and it is no coincidence that physics is reflected throughout. Nature is self-similar across scales.

I currently work on improving transformer models through thermodynamics and optimal transport.

Some projects I worked on recently (more here)

• Semantic Phonons: Lattice Vibrations in AI Internals
• Diffusion geometry for LLM activations
• Lattice gas, hopfield networks, and transformer attention
• Dendrite networks with cellular automata

Some papers from my PhD (more here)

• Statistical mechanics for organic mixed conductors: phase transitions in a lattice gas; arXiv:2512.20727, under review (2025)
• Electron–ion coupling breaks energy symmetry in bistable organic electrochemical transistors; Nature Communications Materials (2025)
• Bistable organic electrochemical transistors: enthalpy vs. entropy; Nature Communications (2024)

And here are some books that shaped my thinking.