Krish Ramadurai
Student spotlight details
Krish Ramadurai’s experience on the MSc in Nanotechnology for Medicine and Health Care led to the publication of his book, Machine Learning-Driven Rational Design in Nanomedicine. He is now continuing his research through a DPhil at the University of Oxford.
'I was a former researcher at Harvard and MIT and am an investment partner at one of the world's top-performing AI funds investing in techbio companies. I applied to the MSc to deepen my technical expertise in nanomedicine, engineering, and computational modelling. I wanted to move beyond strategy and develop rigorous, first-principles scientific capability in modelling biological systems.
'The most defining experience of the MSc was working closely with Professor Banerjee on my dissertation and realising how engineering frameworks could be applied to real therapeutic bottlenecks. We were not just building models in abstraction; we were asking how computational tools could meaningfully solve translational problems. That experience fundamentally shaped how I approach research today.
'What I did not fully anticipate was the complexity of modelling biological systems and the so-called "biological black box" problem. Biological systems are nonlinear, heterogeneous, and high-dimensional. Bridging computational abstraction with biological reality required structured iteration: careful feature engineering, validation strategies, and constant biological grounding. The challenge strengthened my ability to integrate multimodal data and think systematically about uncertainty and model interpretability.
'Coming from a molecular biology background, I initially underestimated how deeply I would need to immerse myself in engineering. Biomedical engineering and nanomedicine require a shift toward systems design, quantitative modelling, and first-principles problem-solving. I quickly learned that fully engaging with the engineering mindset, not merely its biological applications, was essential, and that embracing this shift ultimately strengthened my research and shaped the direction of my DPhil work.
'I am currently a DPhil student at St. Hilda's College in the department of Engineering Science at the Institute of Biomedical Engineering, working in the Multimodal Medical Data Integration & Analysis (MultiMeDIA) Group. I focus on developing multimodal AI models for drug toxicity prediction and on addressing the biological "black box" problem and translatability crisis inherent to drug development. The goal is to integrate molecular data, cellular phenotypes, mechanistic modelling, and high-dimensional biological signals into interpretable systems that can predict toxicity earlier in drug development.'
