Adhi grew up in West Yorkshire and studied Engineering at the University of Cambridge, specializing in Information and Computer Engineering. During his degree, he interned at startups working on applied computer vision and deep learning, and at Caltech, where he was funded by the Summer Undergraduate Research Fellowship to study the fairness, synthetic data, and code generation properties of foundation models. In his Master’s, Adhi focused on probabilistic machine learning and deep learning, and for his thesis, he explored the certification of Bayesian Neural Networks, integrating concepts from formal verification.
At StatML, he is eager to delve into probabilistic approaches and generative modelling to address key challenges in large models, such as data efficiency, uncertainty quantification, and model robustness. He is particularly drawn to AI4Science, with a focus on biological applications. Outside of his research, Adhi enjoys playing cricket, weightlifting, building (/programming) things, and traveling.
