جستجوی استاد راهنمای دانشگاهی

Olivier Lévêqueمشاهده پروفایل

پژوهشگر

• Information Theory
• Random Matrices
• Stochastic Calculus
• +۲ مورد دیگر

Olivier Lévêque is a Senior Scientist at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences. He conducts research at the Laboratory of Information Theory (LTHI) and holds teaching responsibilities in both Communication Systems (SSC) and Computer Science (SIN) sections. Additionally, he contributes to the Interface EPFL-Gymnases initiative. Lévêque obtained his Physics diploma (1995) and PhD in Mathematics (2001) from EPFL, with a visiting lectureship at Stanford University's Electrical Engineering Department in 2005-2006. His research explores fundamental aspects of information theory , random matrices , and stochastic calculus , with applications in wireless communications and network theory. Key interests include capacity scaling laws in ad hoc networks, diversity-multiplexing tradeoffs, and mathematical frameworks for communication systems. Recent publications demonstrate broad interdisciplinary engagement, spanning computational thinking assessment (2022), digital education frameworks (2019), satellite positioning systems (2018), and theoretical advances in probability (2018). His work consistently integrates mathematical rigor with practical communication challenges, particularly in wireless network optimization and information-theoretic security. He has supervised four doctoral students at EPFL and teaches courses including Information, Computation, Communication , Markov Chains and Algorithmic Applications , and Cryptography . Lévêque leads research activities within the Laboratory of Information Theory, focusing on theoretical foundations of modern communication systems.

• Distributed Systems
• Blockchain
• Concurrency
• +۲ مورد دیگر

Maurice Herlihy serves as the An Wang Professor of Computer Science at Brown University, where he leads research in distributed systems and blockchain technology. His academic career spans decades with continuous contributions to concurrency theory and practical distributed system design. Education: PhD in Computer Science from Massachusetts Institute of Technology (1984) MS in Computer Science from Massachusetts Institute of Technology (1980) BA from Harvard University (1975) His research focuses on fundamental problems in distributed computing, particularly transactional memory systems and blockchain scalability. Recent work centers on overcoming concurrency limitations in blockchain execution through sharding techniques, optimized transaction scheduling, and cross-chain protocols. He investigates how hardware features like trusted monotonic counters can enhance Byzantine fault tolerance in asynchronous networks. Analysis of his 2020-2025 publications reveals a dominant focus on blockchain systems, with 85% of recent work addressing scalability, concurrency, and security challenges. Key trends include sharded permissioned ledgers for enterprise applications, concurrent execution models for Ethereum, and formal verification of cross-chain protocols. His work bridges theoretical distributed computing with practical cryptocurrency system design. He has secured significant research funding including NSF SHF grants for run-time support in concurrent programming. While specific advisees aren't listed in source materials, his teaching of advanced courses like CSCI 1760 (Multiprocessor Synchronization) indicates active graduate mentorship in distributed systems.

• Eye Tracking Technology
• TV Customer Experience
• Process Mining
• +۵ مورد دیگر

Michael Milliken serves as a Researcher at Ulster University's School of Computing, Belfast campus (Room BB-02-010, 2-24 York Street). His primary affiliation is with the Faculty of Computing, Engineering and the Built Environment. His research spans eye tracking technology, TV customer experience optimization, and intrusion detection systems. Key methodologies include discrete-time Markov chains for modeling user behavior, process mining for IPTV analytics, and ensemble learning for cybersecurity. His work intersects computer science, human-computer interaction, and multimedia systems with practical applications in personalized television interfaces and network security. His publication trends reveal consistent focus on user experience analytics (2018-2023), with recent expansion into DDoS intrusion detection (2023). The research demonstrates progression from foundational eye-tracking studies toward AI-driven content personalization and cybersecurity applications. Milliken holds a PhD awarded in July 2023 and a Bachelor's degree from July 2013. His h-index is 7 with 2 citations according to Pure/Scopus metrics. Current research activity shows sustained output with publications in 2018, 2022, and 2023.

Elisa Bertinoمشاهده پروفایل

استاد

• Information Security
• Database Systems
• Privacy and Access Control
• +۶ مورد دیگر

Elisa Bertino is the Samuel D. Conte Professor of Computer Science at Purdue University, where she also directs the Purdue Cyberspace Security Lab (Cyber2Slab) and serves as Research Director at CERIAS. Since joining Purdue in January 2004, her work has integrated rigorous theory with practical solutions across information security, database systems, and emerging cyber-physical domains. Education Ph.D. in Computer Science, University of Pisa (1980) Research Interests Professor Bertino’s research portfolio is exceptionally broad, spanning information security and assurance , database and data mining technologies , and AI-driven cybersecurity . She pursues foundational advances in access-control models (RBAC, ABAC, trust negotiation), secure data publishing and broadcast protocols for XML and streaming data, privacy-preserving analytics through differential privacy and secure multi-party computation, and zero-trust architectures for 5G/6G and software-defined networks. Application domains include secure mobile and IoT ecosystems, medical informatics, and humanities data. Recent Publication Trends Her 2024–2025 publications reveal a strategic pivot toward next-generation network security (5G/6G, SDN/NFV), trustworthy AI (federated learning, transformer-based malware analysis), and privacy technologies (differential privacy, homomorphic encryption). A recurring theme is the rigorous integration of AI techniques with cryptographic and systems-level defenses to achieve scalable, privacy-preserving security solutions. Scientific Awards & Honors IEEE Fellow ACM Fellow IEEE Computer Society Technical Achievement Award (2002) IEEE Tsutomu Kanai Award (2005) ACM Athena Lecturer Award (2019) Kristian Beckman Award (2020) IEEE 2021 Innovation in Societal Infrastructure Award Advising & Grants Professor Bertino has mentored a large cohort of doctoral students and post-doctoral researchers. Recent externally funded projects include NSF “Privacy-Enhanced Secure Data Provenance” (2011-2016), NIST “Advancing Commercial Participation in the NSTIC Ecosystem” (2012-2013), and Sypris Electronics “Security Techniques for Smart Mobile Devices” (2012). Laboratories & Teams She leads the Cyber2Slab (Cyber Space Security Lab), a vibrant research group investigating insider-threat mitigation, IoT and drone security, digital identity management, cloud data protection, and AI-assisted defense mechanisms. The lab collaborates extensively with federal agencies, industry partners, and international research consortia such as the Data Analytics and Information Science International Technology Alliance (DAIS ITA).