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 behavior of adversarial users in both the serverless and server-based federated learning settings. PhD student advised by Salman Avestimehr.

Behafarid Hemmatpour's research interests are in traffic optimization and smart cities. Her expertise lies in statistical physics, complex networks, and modeling mobility patterns. Delving into human mobility and movement behaviors, she now aspire to devise algorithms and systems that tackle real-world challenges through data analysis. PhD student advised by Nikolaous Laoutaris.

Elina Van Kempen's research interests are in privacy and applied cryptography. PhD student advised by Gene Tsudik.

Hari Venugopalan's research interests broadly focus on privacy preserving fraud detection. On the one hand, while analyzing the user's behavior and environment provides strong signals to detect fraud, they can also be abused to invade user privacy. His research focuses on ML and systems that protect user privacy while not compromising other utilities such as fraud detection. PhD student advised by Zubair Shafiq.

Isita Bagayatkar's research interests are in security and privacy, especially for embedded systems. She is currently working on privacy-enhancing technologies using secure hardware and provable security. PhD student advised by Gene Tsudik.

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.

Jad Al Aaraj's research interests are in the areas of IoT privacy and networks. PhD student advised by Athina Markopoulou.

Jonathan Chery's research is about privacy among underrepresented groups. PhD student advised by David Choffnes.

Muhammad Jazlan's research interests are on advanced anti-tracking techniques using LLMs. At the surface level, Muhammad is trying to classify tracking URLs without the use of filter lists, using the LLM itself as a contextual classifier. The end goal is to come up with an end-to-end deployable system for end users PhD student advised by Zubair Shafiq.

Tina Khezresmaeilzadeh's research interests include increasing the privacy and security in Computer Networks and Distributed Cooperative Systems using ML-based algorithms. PhD student advised by Konstantinos Psounis.

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.

Levi Kaplan's research involves studying the fairness of various algorithms and social networks, investigating their propensity for bias, discrimination, and other harms. This is accomplished through black-box auditing, among other techniques. PhD student advised by Alan Mislove.

Mengwei Yang's research interests are about federated learning, IoT, Privacy, and machine learning. PhD student advised by Athina Markopoulou.

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.

Olivia Figueira's research interests are in the areas of network privacy, policy, and machine learning. PhD student advised by Athina Markopoulou and Scott Jordan.

Pavel Frolikov's research interests are in Security and Privacy. He is currently focusing on the Security of low end IoT devices. PhD student advised by Gene Tsudik.

Pouneh Nikkhah Bahrami conducts research on web privacy and security. Specifically, her research involves measuring the prevalence of problems, such as browser fingerprinting and developing automated approaches, using machine learning, to counter them. PhD student advised by Zubair Shafiq.

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.

Renascence Tarafder Prapty's research interests are in the areas of network security, embedded system security, web security and privacy. PhD Student advised by Gene Tsudik.

Rohan Sequeira's research interests are on quantifying trust and uncertainty in machine learning models using various methods of probabilistic logic that explicitly takes epistemic uncertainty into consideration. PhD student advised by Konstantinos Psounis.

Ryan Swift's research interests are on designing safe and trustworthy AI systems. Ryan believes that key components of safe AI systems are explainability, robustness, privacy, and reproducibility. In particular, he believes these systems should be transparent and comprehensible to a regular person; they should not fail or become misaligned in the event of perturbations such as distribution shifts or attacks; they should provide privacy guarantees for users and their data; and they should not require …

Shaoor Munir conducts research on ensuring online privacy and security by targeting new practices being employed by trackers and advertisers. Specifically, his current research revolves around using machine learning algorithms to identify misuse of first party cookies, separate out functional and tracking methods bundled together in script, and evaluating security of future replacements for third party cookies. PhD student advised by Zubair Shafiq.

Shuwen Sun's interests lie in systems and networking, with an emphasis on designing techniques and systems to improve performance, reliability, and security for end device users. His research centers around “enabling” and “auditing” functionality that can be offloaded to edge, cloud, or network provider for end systems. PhD student advised by David Choffnes.

Te Yi Kan's research interests encompass privacy, wireless communication systems, wireless networks, vehicular networking, and edge computing. His current work focuses on designing low-latency privacy-preserving systems for machine learning. PhD student advised by Konstantinos Psounis.

Tianrui Hu's research interests include IoT security and privacy and network measurement. PhD student advised by David Choffnes.

Yash Vekaria's research interests include Security, Privacy and Machine Learning. His focus is towards making our web more secure and private with the use of ML-based techniques. He carries out web-based large-scale Internet measurements to study and improve the dynamics of web. PhD student advised by Zubair Shafiq.

Youngil Kim's research interests are IoT security in general, discovering new vulnerabilities and countermeasures, and providing a way to improve security and privacy in embedded systems. PhD student advised by Gene Tsudik.

Yu Duan’s research interests include data privacy, network science and machine learning. PhD student advised by Athina Markopoulou.

Basileal Imana's research interests broadly lie in studying privacy and algorithmic fairness properties of real-world systems on the Internet. He is currently focused on developing novel methods for auditing the fairness of algorithms used to deliver content on social media platforms without introducing new privacy risks to platforms and users. Postdoc Scholar advised by Aleksandra Korolova.

Daniel Dubois' current research focuses on understand the privacy implications of the Internet of Things.

Javad Dogani's ongoing research pursuits include the development of federated learning models customized to the specific requirements of distributed platforms, such as those employed in edge and fog computing. Javad received his M.Sc. degree in software engineering from Shiraz University in 2012 and completed his Ph.D. in software engineering from the same university in 2023. Before joining IMDEA, he served as a Teaching and Research Assistant at Shiraz University in Iran for nine months, …

Luca Baldesi's research interests are in the area of computer networks, IoT, graph theory, and machine learning. His expertise includes the design and development of communication systems, distributed algorithms, and embedded prototypes. He works closely with Athina Markopoulou.

Piotr Sapiezynski's core work is auditing platforms and their algorithms for fairness and privacy. Together with his collaborators, they investigate systems that are optimized for corporate profit yet drive many aspects of our daily lives. All too often we find these systems have (possibly unintended but often predictable) side effects that bring harm to individuals and the society. He works closely with Alan Mislove.

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 research aims to bridge the gaps between IoT devices' behaviors and users' preferences, informing secure and privacy-respecting designs for …

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.

Devriş İşler is interested in data provenance (e.g., data ownership via watermarking) in data economy and creating new SoA techs by taking advantage of cryptography (e.g., MPC, FHE, SSE). Along the line, he is also doing some works on privacy (e.g., user perceptions, privacy policies). PhD Student advised by Nikolaos Laoutaris.

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.

Shraddha(Shay) is a 3rd year undergraduate student, majoring in Computer Engineering and minoring in Math at UCI. She is interested in studying Auditing Algorithms and Reinforcement Learning within the context of data security and data privacy. Undergraduate student advised by Athina Markopoulou.