جستجوی استاد راهنمای دانشگاهی

Marten van Dijkمشاهده پروفایل

استاد

• Computer Security
• Cryptography
• Secure Processor Design
• +۷ مورد دیگر

Dr. Marten van Dijk is a Full Professor in the Computer Security department at Vrije Universiteit Amsterdam (VU) since 2022 and a Group Leader for Computer Security at CWI since 2020. He also holds a Gratis Full Research Professor position at the University of Connecticut's ECE Department since 2020. Previously, he served as Associate and Full Professor at the University of Connecticut and held research roles at MIT CSAIL, RSA Laboratories, and Philips Research. PhD in Mathematics (1997, Eindhoven University of Technology) M.S. in Mathematics (Cum Laude, 1993) M.S. in Computer Science (Cum Laude, 1991) His research focuses on foundational computer security problems using cryptographic principles, including secure processor design, oblivious computation, and privacy-preserving machine learning. Notable contributions span Physical Unclonable Functions (PUFs), Aegis secure processor architecture, and oblivious RAM protocols. 15+ publications in 2023-2025 address topics like PUF cryptanalysis, differential privacy in federated learning, and Byzantine fault tolerance Key journals: IEEE Transactions on Computers, Journal of Cryptology, ACM CCS Conference Award highlights include: IEEE Fellow (2022) for secure processor design and encrypted computation IEEE Technical Achievement Award (2023) Intel Test of Time Award (2022) ACM CCS Best Paper (2013) A. Richard Newton Technical Impact Award (2015) His technical leadership spans hardware security (blu-ray error correction codes), cryptographic protocol design, and machine learning privacy frameworks. Current projects focus on secure processors with hardware-enforced isolation and differential privacy optimization.

• Criminal Law
• Criminal Procedure
• EU Criminal Law
• +۴ مورد دیگر

Willem (Pim) Geelhoed serves as Associate Professor of Criminal Law and Criminal Procedure at the University of Groningen's Faculty of Law, Department of Criminal Law and Criminology. He also holds the position of Academic Director (ad interim) for the Global Criminal Law LLM programme and acts as an ad hoc judge at the Court of Appeal of Arnhem-Leeuwarden. His research expertise centers on the Europeanization of Criminal Law, comparative criminal law and procedure within Europe, and specialized topics in organized and financial crimes. Geelhoed approaches these subjects through multiple theoretical perspectives, examining how EU law influences national criminal justice systems. Geelhoed maintains significant professional engagement through his membership in the Meijers Committee (an expert body on European immigration, refugee and criminal law), the Steering Committee of the International Association for the Study of Organised Crime, and as national rapporteur on corporate criminal liability for the European Law Institute. His publication record shows consistent output in EU criminal law, mutual legal assistance, and evidence procedures, with recent focus on EncroChat jurisprudence and international cooperation during emergencies. His teaching portfolio includes courses on Organized and Financial Crime, Seminar Judicial Cooperation in Criminal Matters, International and European Criminal Law, and the Studentenrechtbank. He also contributes to Wolters Kluwer commentaries and serves on the Faculty of Law Board of Examiners.

Sandjai Bhulaiمشاهده پروفایل

پژوهشگر

• Machine Learning
• Artificial Intelligence
• Optimization
• +۴ مورد دیگر

Dr. Sandjai Bhulai is a Researcher at Centrum Wiskunde & Informatica (CWI) in Amsterdam, The Netherlands, and affiliated with Vrije Universiteit Amsterdam. He works in the Stochastics department within the Faculty of Science, focusing on applying machine learning and optimization techniques to solve complex real-world problems across diverse domains including telecommunications, mental health crisis intervention, and operations research. His research spans multiple critical areas of applied mathematics and computer science: Development of novel machine learning evaluation frameworks (Dutch Draw, Dutch Scaler) Optimization algorithms for facility location and supply chain problems Telecommunications signal processing using deep learning Mental health applications, particularly suicide prevention helpline analysis Natural language processing for conversation analysis in crisis intervention Dr. Bhulai's recent work demonstrates exceptional interdisciplinary impact. His Dutch Draw framework provides a universal baseline for binary classification problems that has been adopted across multiple research communities. His mental health research has directly influenced suicide prevention practices through machine learning analysis of helpline conversations, identifying specific counselor interventions that improve outcomes. In telecommunications, he's developed neural network approaches that simultaneously handle multiple modulation schemes, improving efficiency in wireless communications. His scientific contributions appear in leading venues including: Computers and Operations Research Journal of Classification IEEE Open Journal of the Communications Society JMIR Mental Health Journal of Applied Probability Dr. Bhulai maintains strong collaborative relationships with researchers across institutions, particularly with Rob van der Mei at CWI. He has secured funding for impactful projects including the collaboration between Stichting 113 Suicide Prevention and CWI, which applies machine learning to improve crisis intervention services. His work exemplifies how theoretical advances in machine learning can address critical societal challenges.

Vicente Alarcon-Aquinoمشاهده پروفایل

استاد

• Cybersecurity
• Network Monitoring
• Anomaly Detection
• +۷ مورد دیگر

Dr. Vicente Alarcon-Aquino is a Professor in the Department of Computing, Electronics, and Mechatronics at Universidad de las Americas Puebla (UDLAP), Mexico. He received his Ph.D. and D.I.C. degrees in Electrical and Electronic Engineering from Imperial College London in 2003. He previously served as department head from October 2012 to June 2018 and spent a research stay at King's College London in 2017. Dr. Alarcon-Aquino is a Senior Member of IEEE, a Level I member of the Mexican National System of Researchers (SNI), and a Fellow of the Mexican Academy of Sciences. His educational background includes: Ph.D. and D.I.C. in Electrical and Electronic Engineering, Imperial College London, UK (2003) Dr. Alarcon-Aquino's research focuses on cybersecurity, network monitoring, anomaly detection, wavelet analysis, and machine learning. His work spans theoretical foundations to practical applications in network security, with significant contributions to intrusion detection systems, cryptographic techniques, and machine learning approaches for security applications. He has developed innovative methods combining wavelet transforms with neural networks for various security and signal processing applications. His scholarly contributions include over 180 research articles in refereed journals and conference proceedings, a book on MPLS networks, and numerous citations. As an editor, he serves as Associate Editor for IEEE Access Journal and as Academic & Section Editor for PeerJ Computer Science, focusing on Security & Privacy. Notable professional recognitions include: Senior Member of IEEE Mexican National System of Researchers (SNI Level I) Member of the Mexican Academy of Sciences Dr. Alarcon-Aquino has supervised over 70 theses, including 8 Ph.D. dissertations, 15 Master's theses, and more than 37 Bachelor's theses. His supervision spans topics including network intrusion detection, information security, encryption algorithms, wavelet-based signal processing, neural networks, EEG signal processing, and biometric cryptosystems. He has hosted international research students from institutions including the Polytechnic University of Madrid and Kiel University of Applied Sciences. His research group at UDLAP focuses on developing advanced security solutions for modern network environments, with particular emphasis on applying machine learning techniques to cybersecurity challenges. Current projects include blockchain-based security solutions, federated learning approaches for intrusion detection, and advanced anomaly detection systems for IoT environments.

Stefania Milanمشاهده پروفایل

استاد

• Critical Data Studies
• Political participation and technology
• Data activism
• +۵ مورد دیگر

Stefania Milan is Professor of Critical Data Studies at the University of Amsterdam, working at the intersection of political participation, technology, and governance with emphasis on infrastructure and agency. She is affiliated with the Florence School of Transnational Governance at the European University Institute and the Berkman Klein Center for Internet & Society at Harvard University. Her research focuses on critical data studies, data activism, and the politics of digital infrastructure. Milan examines how datafication transforms political participation and civil society engagement, exploring concepts like data activism , cloud protesting , and digital civil disobedience . Her work bridges Science and Technology Studies with Social Movement Studies to understand the evolving relationship between citizens, data, and power. Analysis of Milan's publications reveals consistent engagement with how datafication reshapes political agency, particularly through grassroots data practices. Her research spans theoretical frameworks for understanding data activism, empirical studies of digital protest, and critical examinations of internet architecture and human rights. Key trends include the emergence of alternative epistemologies around data, the politics of visibility in digital spaces, and the tension between data as stakes versus data as repertoires in political struggle. ERC Starting Grant (StG-2014_639379 DATACTIVE) for the DATACTIVE research project Milan leads the DATACTIVE research project and collective, which explores the politics of big data broadly defined, examining massive data collection, privacy, surveillance, social movements, internet activism, and internet infrastructure governance. She has also contributed to several significant research initiatives including the Big Data from the South Initiative, the IN-SIGHT.it project on citizenship and standard-setting in digital networks, and the e-LADDA project on Early Language Development in the Digital Age. The DATACTIVE project, based at the Department of Media Studies at the University of Amsterdam, investigates how civil society engages with datafication through both affirmative practices and resistance tactics. Milan's research collective examines how activists leverage technical properties of social media platforms and develop alternative data practices that challenge dominant data regimes.