Bijan Mazaheri

Overview

Professor Bijan Mazaheri's work focuses on issues that arise when synthesizing information from multiple datasets, modalities, and batches into machine learning and AI models. How can we integrate causal knowledge into statistical models? How can we effectively navigate tradeoffs between data diversity and causality? How can we detect AI-generated or adversarially manipulated data? How can we quantify human performance in highly variable environments? To answer these questions, Bijan uses tools from theoretical computer science and statistics, including sample complexity, mixture models, and causal inference. His work is directly inspired by applications in information security, biology, and human health. Bijan is also an internationally-competitive distance runner and enjoys applying his research to sports analytics.

Research Interests

Causal inference; data integration; mixture models; machine learning; biological datasets

Education

• BA, Physics and Computer Science, Williams College 2016
• PhD, Computing and Mathematical Sciences, California Institute of Technology 2023

Awards

• NSF Graduate Research Fellowship
• Amazon AI4Science Fellowship
• Eric and Wendy Schmidt Center Postdoctoral Fellow
• Herchel Smith Fellowship

Professional Activities

• Creator, LACCTiC
• Postdoctoral Fellow, Eric and Wendy Schmidt Center of the Broad Institute of MIT and Harvard