Aavash Subedi

I am a first year PhD student at the University of Oxford within the Intelligent Earth CDT. I am currently working at the intersection of machine learning and the environmental sciences with the aim of mitigating the effects of climate change. In my previous life, I compleleted a masters in Physics at the University of Manchester working on combinatorial optimisers and graph neural networks applied to the upcoming Square Kilometer Array, supervised by Professor Anna Scaife.

My interest spans across different areas of deep learning, with the aims of, improving models inspired by problems rooted in the natural sciences and applying these to mitigigate the effects of climate change either by improving weather predictions or by discovering new materials.

Throughout my degree, I have been fortunate to work on many interesting machine learning problems. I completed an internship with Dr Dorina Thanou (summer 2023) at EPFL working on GNNs for digital histopathology. Prior to this I worked as a research intern with Professor Yee Whye Teh (summer 2022) at the University of Oxford on Equivariance for the drug discovery pipeline.

I have also applied various deep learning tools to cloud & solar power forecasting and represented my university in the two iterations of ClimateHack. Please see here for my CV (08/03/2024).