About me

I build optimisation and simulation software in Python, and agentic AI tooling that has helped engineering teams work more efficiently.

Since December 2025 I have been a Digital Twin Engineer at Gradyent, whose digital-twin platform recommends the optimal operation of industrial and district-heating networks. I work on its optimisation software and build AI tooling. In this role, I helped deliver over 3x faster compute and ~97% lower peak memory for a live optimisation service, and built a multi-agent development harness that most of the development team now uses as its standard way of working.

I come from a background in data-driven modelling and simulation of complex physical systems: a PhD in computational materials science at Shanghai Jiao Tong University, then research in computational techniques at IIT Gandhinagar and TU Eindhoven. At TU Eindhoven I worked with IBM Research in an EU consortium project, led its device modelling and simulation work package and released open-source scientific software.

On this site you will find my experience, selected research, publications, talks, teaching, awards and contact details. My open-source code is on GitHub.

Outside work, I enjoy swimming and going to the gym.