Shahab Asoodeh

Shahab Asoodeh

I am an Assistant Professor in the Department of Computing and Software at McMaster University, and a Faculty Affiliate at the Vector Institute.

Prior to that, I was a postdoctoral fellow, first in the Knowledge Lab at the University of Chicago, and then in the School of Engineering and Applied Sciences at Harvard University. Even prior to that, I obtained my Ph.D. in Applied Mathematics from Queen’s University, where I also earned an M.Sc. in the same field. Long ago, and farther away, I received an M.Sc. in Electrical Engineering jointly from TU Delft and ETH Zürich.

My main areas of research lie in information theory, statistics, and inference, with a focus on rigorous approaches to data privacy, algorithmic fairness, and trustworthy machine learning. One of my current interests involves developing principled privacy-preserving tools grounded in information-theoretic and statistical principles. Another concerns the intersection of synthetic data generation with rigorous fairness guarantees in decision-making systems.

There is an open Ph.D. position in my lab on topics related to trustworthy machine learning (e.g., privacy, algorithmic fairness, interpretability). If you have strong background in math, probability and statistics, contact me with your CV and transcripts.

Please note that, like many other faculty members, I receive large volume of emails, and as such, I cannot respond to all inquiries.

🗞️ Recent Announcements

Research Group

Current Group Members and Research Advisees:

Past Group Members:

Publications

Selected publications:

An (almost) up-to-date list of publications can be found on Google Scholar.

Teaching

Contact

Office: Information Technology Building,
1280 Main St W,
Office 212,
Hamilton, ON L8S 1C7
Email: asoodehs [@] mcmaster.ca