جست‌وجوی استاد و پژوهشگر

John Clarkمشاهده پروفایل

استاد

• Cybersecurity
• Software Engineering
• Artificial Intelligence
• +۵ مورد دیگر

John Clark is a Professor of Computer and Information Security at the University of Sheffield since 2017 and Director of the Siemens Digital MINE. Previously, he held roles as Professor of Critical Systems at the University of York (1992–2017) and worked at Logica in security R&D. He studied Mathematics and Applied Statistics at the University of Oxford. His research focuses on cybersecurity, software engineering, and AI applications, particularly in threat modeling, intrusion detection, quantum cryptanalysis, and secure autonomous systems. Clark leads the Security of Advanced Systems research group and has secured grants totaling over £36 million. Notable projects include the EPSRC-funded DAASE (2012–2019) and the Active Building Centre (2018–2022). His work on phishing detection (e.g., analyzing user behavior) and malware analysis has been widely recognized. He has been awarded the Royal Society Wolfson Merit Award (2013), GEECO medals (2005, 2013), and multiple best-paper prizes. Clark’s research spans theoretical and applied domains, including evolutionary computation for cryptanalysis, robotic system security, and smart grid protection. His labs explore areas like digital twin authentication and privacy-aware energy theft detection. He has supervised numerous grants and maintains active collaborations with industry and academia.

• Blockchain Technology
• Internet of Things (IoT)
• Cybersecurity
• +۲ مورد دیگر

Dr. Volkan Dedeoglu is an active researcher at Queensland University of Technology (QUT), specializing in blockchain technology and IoT systems within the School of Computer Science. His work focuses on developing privacy-preserving frameworks and trust architectures for distributed systems. Research Focus: Blockchain applications in IoT and cyber-physical systems Privacy-preserving data sharing and threat intelligence Decentralized trust and reputation management Secure data aggregation and marketplace frameworks His recent work explores cutting-edge applications like CypherChain for privacy-preserving data aggregation in blockchain-based demand response programs and Priv-Share for differential privacy in cyber threat intelligence sharing. These publications demonstrate a consistent focus on bridging theoretical blockchain innovations with practical cybersecurity challenges in IoT ecosystems. Collaborative Research: Dr. Dedeoglu frequently collaborates with QUT colleagues including Raja Jurdak, Salil Kanhere, and Sidra Malik, indicating active participation in QUT's distributed systems and cybersecurity research groups.

Arpan Gujaratiمشاهده پروفایل

عضو هیئت علمی

• Real-Time Systems
• Distributed Systems
• Cyber-Physical Systems
• +۷ مورد دیگر

Arpan Gujarati is a Sessional Lecturer in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Systopia Lab. He teaches graduate and undergraduate courses such as CPSC 538G (Distributed Systems), CPSC 416 (Operating Systems), and CPEN 432 (Real-Time System Design). He holds a PhD from the Max Planck Institute for Software Systems and TU Kaiserslautern, where he was supervised by Björn B. Brandenburg. PhD: Max Planck Institute for Software Systems & TU Kaiserslautern (2020) Undergraduate: Birla Institute of Technology and Science (BITS Pilani) Postdoctoral Researcher: MPI-SWS Research Associate: UBC Software Development Engineer: Citrix R&D, India His research focuses on real-time and distributed systems, with applications in cyber-physical systems, fault tolerance, and machine learning reliability. He investigates scheduling algorithms, reliability analysis, and the integration of learning-enabled components into safety-critical systems. His work combines theoretical analysis with practical system implementations, often involving real-world testbeds and open-source tools. His recent publications span top-tier venues including RTSS, OSDI, ECRTS, DSN, and Middleware, with a strong emphasis on performance predictability, resilience of ML systems, and real-time communication. His work frequently addresses challenges in timing guarantees, fault tolerance, and system reliability in both cloud and embedded environments. SIGBED Paul Caspi Memorial Dissertation Award Best Paper Award at RTSS 2022 Distinguished Artifact Award at OSDI 2020 Best Student Paper Award at Middleware 2017 Outstanding Paper Award at RTCSA 2025 He advises several PhD students and undergraduate researchers at UBC, including Heng Zhao, Aida Aminian, Zainab Saeed Wattoo, and Philip Schowitz. He has led multiple research projects involving robotic arms, NVIDIA Holoscan, FreeRTOS, and distributed key-value stores. His lab work emphasizes reproducibility, open datasets, and practical system building. He has served on program committees for RTSS, RTAS, ECRTS, and Middleware, and contributes to journals such as Real-Time Systems and JSys.

Hafizul Asadمشاهده پروفایل

مدرس

• Formal Verification
• Hybrid Systems
• Intrusion Detection Systems
• +۵ مورد دیگر

Dr. Hafizul Asad serves as a Lecturer in Dependability at City St George's, University of London, leveraging his PhD in Electrical Engineering (City University of London, 2016) and MS in Aerospace Engineering (University of Belgrade, 2008) to advance cybersecurity and formal verification research. His expertise bridges critical infrastructure protection and cyber-physical systems security, with significant contributions to IoT/IIoT security frameworks. His educational journey includes: PhD in Electrical Engineering, City, University of London (2012-2016) MS in Aerospace Engineering, University of Belgrade, Serbia (2007-2008) BSc in Electrical and Electronics Engineering, University of Engineering and Technology Peshawar, Pakistan (1999-2003) Asad's research centers on formal verification of hybrid systems and verifiable intrusion detection mechanisms for interconnected environments. He pioneers provably robust security architectures for IoT/IIoT systems, emphasizing mathematical verification to ensure system resilience against cyber threats. His work integrates diversity principles to create defense-in-depth strategies for critical infrastructure, with recent focus on wind turbine cyber-safety and industrial control system protection. Analysis of his 15 most recent publications (2014-2025) reveals an evolution from aerospace applications and analog circuit verification toward cutting-edge cybersecurity for cyber-physical systems. His 2023-2025 work demonstrates increasing specialization in IoT security and formal methods, while maintaining foundational contributions to diversity-based security architectures established in his 2015-2018 research. No scientific awards or prizes are documented in the provided materials, though he maintains professional standing as a British Computer Society member and Higher Education Academy Associate Fellow. Details regarding doctoral student supervision or specific research grants are not disclosed in the source text. His professional trajectory indicates significant project involvement, including the D3S security project at City University of London (2015-2018) and Rolls-Royce-funded Future Systems Simulator development at Cranfield University (2018-2019), though current laboratory affiliations remain unspecified.

Michael Hamمشاهده پروفایل

دانشیار

• Cybersecurity
• Cyber Operations
• Malware Analysis
• +۵ مورد دیگر

Dr. Michael Ham is an Associate Professor and Coordinator for Cyber Operations Initiatives at Dakota State University's Beacom College of Computer & Cyber Sciences. He leads the NSA-designated Center of Academic Excellence in Cyber Operations (CAE-CO) and oversees DSU's Cyber Operations bachelor's program and Ethical Hacking Certificate. His roles include teaching advanced cybersecurity courses, advising doctoral students, and coordinating cyber events like DakotaCon and GenCyber camps. Education: All degrees from Dakota State University — D.Sc. in Cybersecurity (202X), M.S. (20XX), and B.S. (20XX). Research focuses on cybersecurity education, penetration testing, malware analysis, and developing experiential learning tools. Key projects include open-source platforms for hardware reverse engineering and wireless security training using software-defined radios. He emphasizes cyber hygiene practices and offensive security principles in both teaching and industry consulting. Grants highlight his leadership in addressing cybersecurity workforce shortages, including NSF CyberCorps SFS programs (PI), GenCyber camps (Co-PI), and DoD scholarships. Recent publications address ransomware prevention, X.509 certificate validation, and pandemic-era ICT systems. Dr. Ham also serves as an independent security consultant, advising on infrastructure security, vulnerability remediation, and policy development for organizations. His work bridges academia and industry through practical, hands-on cybersecurity education and tool development.

• Cybersecurity
• Machine Learning Applications in Security
• Data Provenance Analysis
• +۷ مورد دیگر

Kangkook Jee is an Assistant Professor in the Department of Computer Science at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. His work focuses on cybersecurity, machine learning applications in security, data provenance analysis, and graph neural networks. He has developed systems like ProvIoT for IoT security and UTrack for enterprise user tracking. His research addresses challenges in adversarial machine learning, malware detection, and robust graph classification under adversarial conditions. He also explores federated learning, confidential computing, and blockchain-based secure data sharing. Key contributions include techniques for detecting stealthy attacks in IoT, improving graph neural network robustness against adversarial node modifications, and enhancing intrusion detection through provenance-based analysis. His work bridges theoretical advancements in machine learning with practical enterprise security solutions. Notable systems include AIQL for efficient attack investigation and SEAL for storage-efficient causality analysis in enterprise logs. Research trends across his publications emphasize combining provenance tracking with modern ML techniques to address evolving cybersecurity threats. Work in 2024-2025 focuses on decompilation challenges, federated edge-cloud security, and graph abstraction methods for robust classification. No scientific awards are explicitly listed in the provided texts. His grants and advising activities are not detailed here, though his extensive publication record suggests active collaborative research. His lab works on tools like Nodoze for automated threat triage and APTrace for agile causality analysis in enterprise systems.

Hervé Debarمشاهده پروفایل

استاد

• Network Security
• Information Systems Security
• SIEM (Security Information and Event Management)
• +۶ مورد دیگر

Hervé Debar is a Professor and head of the Telecommunications Networks and Services (RST) department at Télécom SudParis. His research focuses on network and information system security, including SIEM systems, automated threat mitigation, SDN security, and resilience against cyber attacks. He coordinates major European projects like NECOMA (EU-Japan cybersecurity collaboration) and PANOPTESEC (industrial control systems security). Research interests span SIEM frameworks, intrusion detection, risk management, and defense mechanisms for critical infrastructures. His work emphasizes practical implementation through projects like MASSIF (SIEM decision support systems) and DEMONS (privacy-aware network monitoring). Recent articles address TLS protocol analysis, DDoS mitigation with SDN, honeypot models, and risk assessment for healthcare systems. He supervises multiple PhD students and collaborates with industry partners via CIFRE theses. His research group is part of SAMOVAR (CNRS UMR 5157). Teaching includes leading the Networks and Systems Security master's program, emphasizing hands-on training with industry partnerships. He actively recruits postdocs and engineers for cybersecurity research.

Feng Haoمشاهده پروفایل

استاد

• Cryptography
• Cybersecurity
• Electronic Voting Systems
• +۳ مورد دیگر

Feng Hao is a Professor of Security Engineering and Head of the Systems & Security research theme at the Department of Computer Science, University of Warwick. He holds a PhD from the University of Cambridge, supervised by Ross Anderson and John Daugman. His research focuses on real-world security problems, including cryptographic protocols, electronic voting systems, and IoT security. He has contributed to standards like ISO/IEC 11770-4 and RFC 8236 (J-PAKE), and his work has been recognized with grants such as the ERC Starting Grant (2012) and the ERC Proof of Concept Grant (2015). Education: PhD in Security Group (Computer Laboratory), University of Cambridge. Research interests include designing secure protocols for e-voting, password authentication, and privacy-preserving systems. Notable contributions include DRE-i, DRE-ip, and J-PAKE protocols. Professional service includes roles as a journal editor (IEEE Security & Privacy, Journal of Information Security and Applications), standards committee member (ISO/IEC), and grant reviewer (EPSRC, EU). Teaching includes advanced computer security and cryptography courses at both undergraduate and postgraduate levels. Awards and grants highlight his impactful work: top Google Scholar paper in Computer Security & Cryptography (2017), 3rd place in Economist Cybersecurity Challenge (2016), and significant ERC funding. His research team has conducted trials in e-voting systems, such as the Gateshead local elections (2019), demonstrating real-world application of his protocols.

Jordan Shropshireمشاهده پروفایل

استاد

• Information Security
• Data Center Management
• Systems Architecture
• +۳ مورد دیگر

Dr. Jordan Shropshire is the Lawrence Minto Sylvestre Endowed Chair in Computing and a Professor in the Information Systems and Technology Department at the University of South Alabama's School of Computing. His academic journey includes a Ph.D. in Management Information Systems from Mississippi State University (2008) and a B.S. in Business Administration from the University of Florida (2004). Dr. Shropshire's research focuses on cybersecurity, data center management, cloud computing, IoT ecosystems, and systems architecture. His work addresses critical challenges such as post-quantum cryptography, embedded system vulnerabilities, and compliance frameworks for autonomous systems. He has also contributed to studies on developer platform risks, real-time operating system security, and AI-driven systems hardening. Education: Ph.D. – Management Information Systems, Mississippi State University, 2008 B.S. – Business Administration, University of Florida, 2004 His teaching career spans roles at the University of South Alabama (2008–present) and Georgia Southern University, where he held tenure (2008–2014). His publications emphasize practical cybersecurity solutions, including tools for drone compliance and frameworks for secure cloud infrastructure. He has also explored behavioral aspects of security policy adherence and IT professional retention. Dr. Shropshire's work often bridges theoretical research and real-world implementation, with a focus on mitigating emerging threats in cloud systems, IoT, and embedded devices. His research has been supported by grants such as the NSF TWC Small Grant for hypervisor security detection techniques.

• Smart-grid cyber-security
• Computer networks
• Artificial intelligence methods
• +۴ مورد دیگر

Robert Czechowski, PhD , is an Assistant Professor at the Faculty of Information and Communication Technology , Wrocław University of Science and Technology , Poland, stationed in the Department of Telecommunications and Teleinformatics . His office is located in building D-20, room 421, and he holds regular consultation hours on Tuesdays 14:00–15:00, Wednesdays 15:00–17:00, and Thursdays 13:00–15:00. His research portfolio is centred on securing the next generation of electrical power systems. Core interests include: Cyber-security architectures for smart grids and micro-grids Artificial-intelligence-driven intrusion detection and prevention systems (IDS/IPS) Network protocols and time-synchronisation security in SCADA environments Simulation of information flow in complex, dynamically reconfigurable networks IPv4/IPv6 network design and security policy enforcement in power-system automation Database and expert-system solutions for real-time energy-management and fraud detection Between 2014 and 2019 he authored or co-authored more than fifteen peer-reviewed works. The publications reveal a clear longitudinal trend: early work established foundational security policies and good-practice guidelines, while later studies pivot toward advanced AI/ML techniques for anomaly detection and risk quantification in smart-metering infrastructures. A recurring theme is the integration of communication-protocol security (IEC 61850, PLC, IPv4/IPv6) with higher-level cyber-physical risk governance. Scientific recognitions: None explicitly mentioned in the supplied text. Advising & Grant activities: The provided material does not list specific doctoral or master’s students, nor does it enumerate funded projects. Laboratories & Teams: He conducts research within the Department of Telecommunications and Teleinformatics, leveraging university laboratories and the wider ICT Faculty infrastructure, although no dedicated lab name is specified.

• Computer and networked systems security
• Systems security and privacy
• Trusted execution environments
• +۶ مورد دیگر

Nuno Santos is an Associate Professor in the Department of Computer Science and Engineering at Instituto Superior Técnico (IST), University of Lisbon, and a senior researcher at INESC-ID Lisbon, where he leads the SysSec team within the Distributed, Parallel and Secure Systems (DPSS) group. He is an active member of the international security community, serving as Program Vice Co-Chair for USENIX Security 2025 and on program committees for top venues such as IEEE S&P, CCS, and USENIX Security. Education: Ph.D. in Computer Science, 2013 – Max Planck Institute for Software Systems (MPI-SWS) & Saarland University Research internships at Microsoft Research Redmond (2010), Vrije Universiteit Amsterdam (2018), and Technical University of Munich (2024) Research Interests Nuno Santos’s research centers on the security and privacy of computer and networked systems, with particular emphasis on trusted execution environments, secure systems design, and the intersection of machine learning with security. His group investigates vulnerabilities and defenses in widely deployed platforms, including TrustZone, JavaScript runtimes, and cloud infrastructures. Additional themes include censorship-resistant communication, privacy-preserving analytics, and automated exploit generation. Recent Publication Trends Over the past five years, his work has increasingly targeted emerging threat models in confidential computing (AMD SEV-SNP, Intel TDX), large-language-model integration into web applications, and automated security analysis of JavaScript ecosystems. These publications consistently appear in the most selective venues (PLDI, SIGMETRICS, ICSE, NDSS, S&P, USENIX Security), evidencing strong empirical evaluation and real-world impact. Awards & Honors IST Outstanding Teaching Award (2019/2020) ISOC.PT Best Portuguese Internet Research Award (2024) Prémio Científico Universidade de Lisboa / Caixa Geral de Depósitos (2024) Multiple IST Teaching Excellence Awards Advising & Service Nuno Santos has supervised numerous MSc and PhD students whose theses span secure systems, network privacy, and trustworthy computing. Recent defenses include Bernardo Ribeiro, Cristi Savin, Hugo Mantinhas, João Aragonez, João Sá, and Tomás Tavares. He actively participates in doctoral committees and mentors junior researchers within the DPSS group. Labs, Teams & Collaborations He leads the SysSec team inside the Distributed, Parallel and Secure Systems (DPSS) group at INESC-ID Lisbon. The team maintains strong collaborative ties with MPI-SWS, VUSec at VU Amsterdam, the Systems Research Group at TU Munich, and multiple industry partners including Microsoft Research.

Wei Liمشاهده پروفایل

استاد

• Computer Security
• Network Security
• Artificial Intelligence
• +۳ مورد دیگر

Wei Li is a Professor in the Department of Computing at Nova Southeastern University's College of Computing & Engineering. He joined NSU in 2005 after earning his Ph.D. from Mississippi State University. His research focuses on enhancing computer system security through interdisciplinary approaches, including network security, artificial intelligence applications, and software engineering practices. Dr. Li’s research areas encompass computer security, network security, software engineering, artificial intelligence, and database systems. His work bridges theoretical advancements and practical cybersecurity solutions, such as improving intrusion detection systems, analyzing social engineering attack vulnerabilities, and developing machine learning models for IoT security. His recent publications (2020–2025) address topics like password policy effectiveness, remote worker cybersecurity risks, and adaptive deep learning models for anomaly detection. These contributions highlight his focus on mitigating organizational cybersecurity risks through empirical studies and innovative technical solutions. No scientific awards or grants are explicitly listed in the provided information. His advising record remains unspecified, and no active labs or teams are mentioned.

Daphne Yaoمشاهده پروفایل

استاد

• Cybersecurity
• Program Analysis
• Machine Learning Algorithms
• +۳ مورد دیگر

Daphne Yao is a Professor in the Department of Computer Science at Virginia Tech , part of the College of Engineering. She holds the Elizabeth and James E. Turner Jr. '56 Faculty Fellowship and CACI Faculty Fellowship. Her research focuses on cybersecurity, program analysis, machine learning algorithms, and applied cryptography. Yao has contributed to advancing secure coding practices, vulnerability detection in software, and privacy-preserving technologies. Education includes a Ph.D. in Computer Science from Brown University (2007), an M.S. in Computer Science from Indiana University (2002), and earlier degrees in Chemistry from Princeton University (M.A., 2000) and Peking University (B.S., 1998). Her work bridges theoretical computer science with practical applications, emphasizing real-world cybersecurity challenges. Recent research trends include combating ransomware via API profiling, improving privacy in voice assistants, and developing resilient network routing systems. Yao collaborates across disciplines, integrating machine learning into healthcare cybersecurity and epigenomic analysis. Her publications reflect a commitment to measurable, deployable security solutions and ethical AI practices. Key contributions include the CryptoGuard tool for detecting cryptographic vulnerabilities and frameworks like Madeline for low-cost cyber threat monitoring. She has also explored challenges in deploying intrusion detection systems and mitigating data-oriented attacks in cyber-physical systems.

• Cybersecurity
• Information Security
• Privacy
• +۳ مورد دیگر

Mark Heckman, PhD is a Professor of Practice in the CyberSecurity Engineering and Technology program at the University of San Diego. He holds MS and PhD degrees in Computer Science from the University of California, Davis, and is a Certified Information Systems Security Professional (CISSP). With over 30 years of experience spanning government/military systems, commercial IT security, and academic research, his work focuses on cybersecurity compliance, intrusion detection systems, and holistic security frameworks. He teaches at USD's Bridges Academy and actively publishes in cybersecurity education and maritime security domains. Education: PhD & MS in Computer Science (UC Davis) Research interests include cybersecurity best practices for home/commercial environments, privacy frameworks, and mitigation of systemic cybersecurity risks in critical infrastructure. His recent work critiques current educational approaches and explores maritime cyber compliance regimes. Articles emphasize practical applications of big data analytics in threat detection and systemic security policy design. While no formal advisees are listed, his teaching and publications reflect strong engagement with applied cybersecurity training and industry standards development.

• Cybersecurity
• Network Security
• Automotive Cybersecurity
• +۵ مورد دیگر

Mirco Marchetti is an Associate Professor at the University of Modena and Reggio Emilia, affiliated with the Department of Engineering 'Enzo Ferrari'. He specializes in cybersecurity, network security, and automotive systems. His teaching responsibilities include courses on cybersecurity fundamentals, computer networks, operating systems, and automotive cyber defense. Research interests focus on intrusion detection systems (IDS), vehicular networks (VANETs), machine learning applications in cybersecurity, and automotive cybersecurity. He has contributed to projects like HackCar (automotive attack/defense testbed) and RealCAN (real-time CAN bus analysis tools). His work also explores adversarial attacks on ML-based systems and secure communication protocols for industrial and vehicular systems. Recent publications emphasize automotive cybersecurity (e.g., Mercedes-Benz infotainment system analysis, CAN bus anomaly detection), ML robustness against adversarial attacks, and zero-trust architectures. He collaborates with the SECloud research group (secloud.ing.unimore.it) and uses experimental platforms like Software-Defined Radios for security evaluations. Teaching responsibilities span multiple academic programs including Master's degrees in Computer Engineering and Artificial Intelligence Engineering. Courses emphasize practical skills in Linux/Unix administration, network configuration, and embedded system security.