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Nils Lukas is an Assistant Professor of Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). He leads the Secure, Private, Open and Trustworthy AI lab and joined the university in 2024. His research focuses on trustworthy machine learning systems, including ML security, privacy, and AI safety topics such as content watermarking, differentially private language models, and confidential computing methods.
Prior to MBZUAI, Professor Lukas earned his Ph.D. in Trustworthy Machine Learning from the University of Waterloo in Canada, supported by the David R. Cheriton Scholarship. His dissertation received the Mathematics Doctoral Prize’s Top Honor, and he was a finalist for the Governor General’s Gold Medal in 2024. He also holds an M.Sc. in Privacy-enhancing Technologies and a B.Sc. in Computer Science from RWTH Aachen University in Germany. During his doctoral studies, he completed research internships at Microsoft Research and Borealis AI. Professor Lukas has received additional honors including Waterloo’s 2024 Alumni Gold Medal, a Distinguished Contribution Award at Microsoft MLADS in 2023, and a Spotlight Award at ICLR 2021. He publishes in top venues such as ICLR, USENIX Security, IEEE S&P, NeurIPS, and CVPR, with notable works including papers on adaptive attacks on image watermarks, universal backdoor attacks, PII leakage in language models, and pivotal tuning watermarking for pre-trained image generators. He has also received an Amazon Research Award.
Explore MBZUAI's DP-Fusion, a pioneering differential privacy method from UAE researchers that protects sensitive data in AI inference while preserving quality. Key implications for trustworthy AI.
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