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PROFESSORS IN DIFFERENTIAL PRIVACY

Showing page 1 of 1 — 14 professors available publicly

Vitaly Shmatikov

Vitaly Shmatikov

Privacy Enhancing Technologies (PET) Security and Privacy in Machine Learning Adversarial Machine Learning

Vitaly Shmatikov is a professor of computer science at Cornell Tech and the Cornell Ann S. Bowers College of Computing and Information Science. Before Cornell, he worked at the University of Texas at Austin and SRI International. His research areas include digital privacy, comput...

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Adam Smith

Adam Smith

Data Privacy Cryptographic Protocols Differential Privacy

Adam Smith is a Professor of Computer Science and Engineering at Boston University. His research interests lie in data privacy and cryptography, and their connections to machine learning, statistics, information theory, and quantum computing. He obtained his Ph.D. from MIT in 200...

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Kobbi Nissim

Kobbi Nissim

cryptography differential privacy privacy law and policy

I am a Professor at the Department of Computer Science, Georgetown University and an Affiliate Professor at Georgetown Law. Prior to joining Georgetown, I was at the Department of Computer Science, Ben-Gurion University. From 2012 to 2017 I visited the Center for Research in Comp...

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Daniel Kifer

Daniel Kifer

Differential Privacy Pufferfish Privacy Framework L-diversity

Daniel Kifer is a Professor in the Department of Computer Science and Engineering at Pennsylvania State University, where he serves as the Director of the Center for Machine Learning and Applications (CMLA). His research is focused on the intersection of Statistical Privacy, Mach...

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Sewoong Oh

Sewoong Oh

differential privacy secure machine learning robust machine learning

Sewoong Oh is a Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Previous to joining University of Washington in 2019, he was at the department of Industrial and Enterprise Systems Engineering at University of Illinois at Ur...

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Jonathan Ullman

Jonathan Ullman

Differential Privacy Statistical Validity in Privacy Robustness in Machine Learning

Jonathan Ullman is an associate professor in the Khoury College of Computer Sciences at Northeastern University, based in Boston. Ullman's research centers on the foundations of privacy for machine learning and statistics, namely differential privacy and its surprising interpl...

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Tianhao Wang

Tianhao Wang

differential privacy machine learning privacy privacy-preserving algorithms

About me I am an assistant professor at the University of Virginia. I got my PhD from Purdue University and my Bachelor’s degree from Fudan University. I work on differential privacy and machine learning privacy, focusing on designing algorithms that work in practice.

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Erman Ayday

Erman Ayday

Genomic Data Privacy Differential Privacy Secure Data Analytics

Erman Ayday, Ph.D., is an Associate Professor in the Department of Computer and Data Sciences at the Case School of Engineering, Case Western Reserve University. He earned his Ph.D. (2011) and M.S. (2007) in Electrical and Computer Engineering from the Georgia Institute of Techno...

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Yuan Hong

Yuan Hong

differential privacy secure computation applied cryptography

Dr. Yuan Hong is a Collins Aerospace Endowed Associate Professor in the School of Computing at University of Connecticut (UConn) and affiliated with the Connecticut Advanced Computing Center (CACC). Prior to joining UConn, he was an Assistant Professor in Computer Science and Cyb...

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Depeng Xu

Depeng Xu

differential privacy algorithmic fairness ethical AI

Dr. Depeng Xu is an Assistant Professor in the Department of Software & Information Systems and the School of Data Science at UNC Charlotte. His research focuses on data mining and machine learning, specifically differential privacy, algorithmic fairness, and ethical AI

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Lydia Zakynthinou

Lydia Zakynthinou

Differential Privacy Privacy-Preserving Machine Learning Robustness in Learning Algorithms

Lydia Zakynthinou is an assistant professor in the Department of Computer Science and a member of the Johns Hopkins Data Science and AI Institute. She works on the theoretical foundations of trustworthy and reliable machine learning and statistics. Her research focuses on deve...

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Gavin Brown

Gavin Brown

Differential Privacy Machine Learning Model Memorization Privacy-Preserving Statistical Algorithms

I am an assistant professor at the University of Wisconsin–Madison in the Department of Computer Sciences. Prior to that, I was a postdoc at the University of Washington with Sewoong Oh. I completed my PhD at Boston University, where I was advised by Adam Smith. I work on ma...

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Meisam Mohammady

Meisam Mohammady

Differential Privacy Adversarial Robustness in Machine Learning Fairness in Machine Learning

Dr. Meisam Mohammady is an Assistant Professor in the Department of Computer Science at Iowa State University (ISU), where his research focuses on developing responsible Machine Learning methods that are privacy-preserving, adversarially robust, and fair, leveraging tools such as...

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Emily (Shuya) Feng

Emily (Shuya) Feng

Privacy-Preserving Machine Learning Differential Privacy Large Language Model Security

Emily (Shuya) Feng is an Assistant Professor in the Department of Computer Science at the University of Alabama at Birmingham, starting in August 2025. Dr. Feng's research addresses fundamental challenges in AI security and privacy, encompassing privacy-preserving machine lea...

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