Amitis Shidani

Amitis Shidani is a DPhil in Statistics student at the Department of Statistics, University of Oxford, supervised by Prof. Arnaud Doucet and Prof. George Deligiannidis. She is broadly interested in Applied Statistics and Machine Learning, with a focus on Sequential Decision-Making, Bandit Learning, and the integration of optimization, robust statistics, fairness, and causal inference for real-world applications.

• Education: Bachelor’s in Electrical Engineering and Computer Science (double major) from Sharif University of Technology, where she worked on Causal Inference in Computational Genomics with Babak Khalaj.
• Professional Background: Lead data scientist at CafeBazaar (Iranian Android app-store with 40M+ users) for two years prior to Oxford.

Her research interests span Sequential Decision-Making, Game Theory, Optimization, Robust Statistics, Conformal Prediction, and Causal Inference. She is affiliated with the Computational Statistics and Machine Learning and Statistical Theory and Methodology research groups.

Recent publications highlight her work in diverse areas, including martingale concentration inequalities, AI deployment in healthcare, transformer architectures, and theoretical machine learning. Her office is located at G.01, and she uses she/her pronouns.