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
Ahmed Elkordy’s research interest include privacy preserving, secure and efficient distributed machine learning at the edge. Specifically, Elkordy has been working towards filling the gap between the algorithmic advance of federated learning (FL) with secure model aggregation and its theoretical guarantees. He also has been working in developing efficient algorithms that ensure security against malicious…Continue Reading Ahmed Elkordy
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
Ismat Jarin’s research interests include Privacy and Machine Learning, specifically, designing defense mechanisms to secure Machine Learning as a Service (MLaaS) systems. Additionally, she is interested in Differential Privacy, Federated Learning, and Adversarial Machine learning. PhD student advised by Athina Markopoulou….Continue Reading Ismat Jarin
Tianyue Chu‘s research interests include Machine Learning and GNNs. Her primary goal is to employ ML-based approaches to prevent misinformation from spreading on the internet. PhD Student advised by Nikolaos Laoutaris….Continue Reading Tianyue chu