I am a 2nd year DPhil student in the Department of Statistics funded by the Engineering and Physical Sciences Research Council (EPSRC). I am currently researching the impact of structural data drift on deep leaning scoring functions, algorithms that predict a binding affinity between a protein and a small chemical compound or drug. I have a strong interest in the role of protein flexibility in small molecule drug design and wish to incorporate this information into biological models of drug binding. I have an integrated undergraduate masters degree in Biochemistry from the University of Oxford (2021).

Small molecule drug design Deep learning approaches to predicting protein-drug dynamics Structural deep learning prediction tools and how they help inform us of protein dynamics

Hi! I'm Ollie, a SABS PhD student funded by the EPSRC. Previously, I completed my MBiochem here at Oxford, and now work on applying ML to therapeutic antibody discovery.

Deep learning for therapeutic antibody optimisation

I'm a first year DPhil student, co-supervised by Yee Whye Teh and Jakob Foerster. Before Oxford, I was a Software Engineer at Meta for over 3 years. I completed my Bachelor and Masters in Computing at Imperial College London.

I am interested in improving the generalizability and robustness of ML models. Particularly, I'm interested in structural causal models, latent variable models and causal structure learning.

I am particularly interested in causal inference, uncertainty quantification, and enhancing the robustness of machine learning methods, especially for policy learning, evaluation, and healthcare applications. Before joining the StatML CDT, I worked as an AI Applied Scientist at Microsoft New England Research Center, where I gained two years of experience addressing real-world challenges. I hold a master's degree in Computational and Mathematical Engineering from Stanford University. My passion for causal inference drives my commitment to developing statistical and machine learning solutions that are both rigorous and applicable in critical domains like healthcare.

• Causal Inference
• Robust Statistics
• Uncertainty Quantification

I am a second year DPhil student under the supervision of Professor Christina Goldschmidt. I previously completed my BSc in Honours Mathematics, and MSc in Mathematics and Statistics, at McGill University.

Topics in random graphs and trees, mixing times of Markov chains, and interacting particle systems.