Regular biography
Reza Shokri is a Dean's Chair Associate Professor of Computer Science at the National University of Singapore. His research focuses on data privacy and trustworthy machine learning. He has received several awards, including the Asian Young Scientist Fellowship 2023, Intel's 2023 Outstanding Researcher Award, and the IEEE Security and Privacy Test-of-Time Award 2021. His work includes analyzing fairness in machine learning and developing methods to mitigate data leakage in machine learning models. He is also affiliated with the Data Privacy and Trustworthy Machine Learning Lab.
Scholar-generated biography
Reza Shokri is a researcher focused on Data Privacy, Trustworthy Machine Learning, and Computer Security. His work explores privacy risks in machine learning models, including membership inference attacks, privacy-preserving deep learning, and location privacy. He has investigated passive and active white-box inference attacks against centralized and federated learning systems. Additionally, he has examined privacy implications of language models, model explanations, and image obfuscation techniques. His research emphasizes developing methods to protect data privacy while enabling secure and reliable machine learning systems. Shokri's contributions include proposing strategies for location privacy, privacy-preserving data synthesis, and robust collaborative learning frameworks.