Michelle Seng Ah Lee is a Ph.D. candidate at the Dept. of Computer Science & Technology in the Compliant and Accountable Systems group, supervised by Jat Singh and Jon Crowcroft. Her research focuses on fairness in machine learning algorithms and their trade-offs on aggregate and individual levels. She is also interested in the regulatory and ethical considerations of bias and discrimination in artificial intelligence (AI).
Michelle received her MSc in Social Data Science at the Oxford Internet Institute and a Research Assistant at the Digital Ethics Lab, supervised by Professor Luciano Floridi. She completed her undergraduate degree at Stanford University, where she studied Political Science and Symbolic Systems with a concentration on Decision-Making and Rationality.
Outside of Oxford, Michelle is a part-time Manager in Risk Analytics at Deloitte UK, specialising in the design, build, and sale of AI-driven risk management solutions for clients across industries. She is also the technical lead in designing the enterprise AI risk framework and controls library for financial services. She is a recurring guest lecturer at Imperial College on “Machine Learning for Credit Evaluation” and a frequent conference speaker. In addition, Michelle is an active volunteer at DataKind, helping charities leverage data science for greater impact.