Alexandr Tolstokorov‘s research interests lie broadly along distributed and decentralized machine learning, the data economy, data valuation and the ways to ensure privacy and transparency in such systems. His current work is in exploring the role of data valuation and the cost associated with it in federated data marketplaces. PhD Student advised by Nikolaos Laoutaris….Continue Reading Alexandr Goultiaev Tolstokorov
Raj Oak‘s research interest lie at the intersection of machine learning and internet security. His current work focuses on understanding how underground incentivized review services work, how they evade detection and whether machine learning can help detect such reviews. Additionally, he is also examining click fraud and how malicious JavaScript libraries can cause click hijacking….Continue Reading Rajvardhan Oak
Tu Le‘s research interests broadly include interdisciplinary research in Security and Privacy, Internet of Things (IoT), and Human-Computer Interaction with applications to Urban Systems and Public Policy. He has worked on several topics such as the security and privacy of voice-controlled devices, privacy protection for non-experts, and privacy preferences for smart building data collections. His…Continue Reading Tu Le
Namo Asavisanu’s research interests are in the security and privacy aspects of distributed mobile systems (e.g., cooperative autonomous vehicles) and the privacy implications of consumer data brokers (as well as interesting ways to outsmart them!). PhD student advised by Konstantinos Psounis….Continue Reading Namo Asavisanu
Yahya Ezzeldin’s research interest are on problems related to privacy and fairness in federated learning. His current work is on developing algorithms that allow for fair training in federated learning while still maintaining privacy guarantees to the system clients. He works closely with Salman Avestimehr….Continue Reading Yahya Ezzeldin