Reza SHOKRI
Dean's Chair Associate Professor- PhD. (Computer Science, EPFL)
Reza Shokri is a Dean's Chair Associate Professor of Computer Science at NUS. His research focuses on data privacy and trustworthy machine learning. He is a recipient of the Asian Young Scientist Fellowship 2023, Intel's 2023 Outstanding Researcher Award, the IEEE Security and Privacy Test-of-Time Award 2021, and the Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies in 2018 for his work on the quantitative analysis of data privacy, as well as the Best Paper Award at the ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2023 for his work on analysing fairness in machine learning. He has also received the VMware Early Career Faculty Award 2021, the NUS Presidential Young Professorship (2018–2023), and faculty research awards from Meta (2021), Google (2021), Intel (2021), and NUS (2019). He was a Visiting Research Professor at Microsoft in 2023–2024. He obtained his Ph.D. from EPFL.
RESEARCH AREAS
RESEARCH INTERESTS
Data Privacy
Trustworthy Machine Learning
RESEARCH PROJECTS
Analytical Framework to Quantify Information Leakage and Memorization in Machine Learning
Machine learning models can "memorize" specific data points from their training data, impacting their predictions and potentially leaking sensitive information. This project aims to understand how this memorization affects models and develop methods to mitigate it.
RESEARCH GROUPS
Data Privacy and Trustworthy Machine Learning Lab
TEACHING INNOVATIONS
SELECTED PUBLICATIONS
AWARDS & HONOURS
Asian Young Scientist Fellowship 2023
Intel's 2023 Outstanding Researcher Award
Best Paper Award at ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2023
NUS School of Computing Faculty Teaching Excellence Award 2023
IEEE Security and Privacy (S&P) Test-of-Time Award 2021 (Quantifying Location Privacy)
Facebook (Meta) Faculty Research Award 2021 (Auditing Data Privacy in Machine Learning)
VMWare Early Career Faculty Award 2021 (Data Privacy and Trustworthy Machine Learning)
Intel Faculty Research Award 2021 (Privacy-Preserving Federated Learning - Private AI Research Institute)
Runner-up for the annual PET Award for Outstanding Research in Privacy Enhancing Technologies 2012 (Quantifying Location Privacy)
NUS Early Career Research Award 2019 (Trustworthy Machine Learning for High-Dimensional Models)
NUS Presidential Young Professorship 2019 (Privacy in Machine Learning)
The Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies 2018 (Privacy Risks of Machine Learning Models)
COURSES TAUGHT
CS6208
Advanced Topics in Artificial Intelligence