About me

Welcome! I’m Nidhish Sagar, currently pursuing my PhD at the University of Cambridge. I recently graduated with a masters at MIT, specializing in Electrical Engineering & Computer Science. My research focus is on leveraging AI for Science, with particular interests in physics-informed machine learning, hybrid modeling, and multimodal techniques for studying energy systems.

Currently, I work on building AI models to understand fundamental mechanisms behind battery degradation. I’ve also published research on how machine learning can solve challenges in industrial chemical processes and materials science. Based on the courses I have taken at MIT, I’ve developed a keen interest in applying AI to discover insights into scientific phenomena whose data have complex mathematical relationships.

Previously, my research has spanned diverse topics such as:

• Machine-learned interatomic potentials for disordered rocksalts.
• Functionalization of 2D materials for hydrogen evolution reactions.

With a strong technical foundation, I enjoy working at the intersection of machine learning and scientific domains, exploring how data and algorithms can transform our understanding of complex systems. My efforts have resulted in peer-reviewed publications and international conference presentations (most recently at NeurIPS 2024).

Beyond academics, I’m deeply passionate about teaching and giving back to the community. Beside research, I was a tutor at MIT’s ESOL program, teaching English to non-native staff at MIT.

I am into long-distance running, having won medals in university athletics.

When I’m not working on my projects, you can find me experimenting with coding challenges, exploring new AI frameworks, or enjoying a game of chess. I aim to create a positive impact wherever I go, and am a big believer of working in a team.