جست‌وجوی استاد و پژوهشگر

Maria Mushtaqمشاهده پروفایل

دانشیار

• Embedded System Security
• Microarchitectural Security
• Artificial Intelligence Applications in Security
• +۲ مورد دیگر

Maria Mushtaq is an Associate Professor at Telecom Paris , affiliated with the Information Processing and Communication Laboratory (LTCI) and the Secure and Safe Hardware (SSH) Lab . She received her PhD in Information Security from the University of South Brittany, France (2019) and completed 2 years of postdoctoral research at LIRMM, University of Montpellier under the CNRS excellence post-doc grant. Research Focus: Microarchitectural vulnerability assessment, runtime mitigation against side/covert-channel attacks, cryptanalysis, OS-based security primitives, and hardware-software interface security Technical Expertise: Cache timing attacks, transient execution attacks (Spectre/Meltdown), Hardware Performance Counter analysis, gem5 simulation Her recent work involves RISC-V security analysis using gem5 simulations and machine learning for attack detection. She serves as Guest Editor for the Journal of Applied Sciences special issue on Side Channel Attacks in Embedded Systems and has been on the Program Committee for the European Test Symposium (2020-2021). 2021 HiPEAC Collaboration Grant recipient Organized IP Paris Winter School on Microarchitectural Security (2022) Active in international conferences as panelist and keynote speaker

Gururaj Saileshwarمشاهده پروفایل

استادیار

• Microarchitectural Security
• System Security
• Memory Safety
• +۵ مورد دیگر

Gururaj Saileshwar is an Assistant Professor in the Department of Computer Science at the University of Toronto, within the Mathematical and Computational Sciences school. His research focuses on securing computing hardware and systems, with a focus on microarchitectural security (cache side-channels, Rowhammer attacks), system security (memory safety), and security for machine learning systems. Education: PhD in Computer Science from Georgia Institute of Technology (2019), advised by Prof. Moinuddin Qureshi. B.Tech and M.Tech from Indian Institute of Technology Bombay (India). Prior to UofT, he was with NVIDIA Research. Research interests include developing new attacks, defenses, and tools for automated security analysis. His work has received multiple awards including the IEEE Top Pick in Hardware and Embedded Security, HPCA Best Paper Award, and IEEE HOST Best PhD Dissertation Award. He teaches courses on secure computer systems and hardware security, including CSC427 (Computer Security) and a topics course on secure computer systems. His lab focuses on hardware-software co-design solutions for security and reliability challenges in modern computing systems. Labs/Teams: Leads the Secure Hardware Systems Lab at UofT, collaborating on Rowhammer mitigation, cache attack defenses, and machine learning security. Grants: Active funding from NSF, industry partnerships with NVIDIA, and other hardware security initiatives. Advising: Currently recruiting PhD students interested in hardware security, system security, and machine learning systems security.

Mathias Payerمشاهده پروفایل

دانشیار

• Software Security
• System Security
• Fuzzing
• +۵ مورد دیگر

Mathias Payer is an associate professor at EPFL's School of Computer and Communication Sciences (IC), leading the HexHive research group since 2018. He focuses on strengthening software and system security through fuzzing, vulnerability mitigation, and compiler-based approaches. His work includes open-source prototypes and contributions to embedded systems, IoT security, and trusted execution environments. Education: PhD in Computer Science (Dr. sc. ETH) from ETH Zurich (2012), postdoctoral researcher at UC Berkeley (2012–2014), and assistant professor at Purdue University (2014–2018). Tenured at EPFL since 2021. Research Interests: Fuzzing frameworks, memory safety, vulnerability analysis, compiler optimizations for security, and firmware security. Projects include Enclosure , HexType , and DP3T (decentralized contact tracing). Awards: Multiple best/distinguished paper awards at top venues (e.g., Usenix Security, NDSS, RAID). Co-founded the EPFL polygl0ts and Purdue b01lers CTF teams to foster cybersecurity innovation. Labs/Teams: HexHive group, CTF initiatives, and collaborations with industry (e.g., Intel SGX, Android security).

Kevin W. Hamlenمشاهده پروفایل

استاد

• Cybersecurity
• Software Security
• Formal Methods
• +۶ مورد دیگر

Kevin W. Hamlen is the Louis A. Beecherl, Jr. Distinguished Professor in the Department of Computer Science at the University of Texas at Dallas. He serves as Executive Director of UT Dallas' Cyber Security Research and Education Institute. His research focuses on language-based security , binary software hardening , cyberdeception , and formal program verification . He has received multiple grants from agencies like AFOSR, NSF, DARPA, and industry partners including Lockheed Martin and Intel. PhD and MS from Cornell University BS from Carnegie Mellon University His research explores automated approaches to software security through techniques like binary disassembly , control-flow integrity , and honey-patching . He has pioneered methods for malware defense and cloud/web/mobile security . Recent work examines adaptive cyberdeception and GPU-based security frameworks . His publications span binary code manipulation , malware mitigation , and blockchain security . Key awards include the NSF IUCRC Technology Breakthrough Award and two CSAW Best Paper 2nd Prizes . He advises numerous PhD students, many of whom now work at Google, IBM, and Microsoft. His book Autonomous Cyber Deception (Springer, 2019) with Ehab Al-Shaer and Cliff Wang provides comprehensive coverage of adaptive cyberdeception strategies.

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.

• Cybersecurity
• Computer Security
• Information Security
• +۶ مورد دیگر

Matthew Allen Bishop is a Professor in the Department of Computer Science at the University of California, Davis. His primary affiliation is with the College of Engineering. Bishop's research focuses on cybersecurity, including secure programming, insider threat detection, malware analysis, and cybersecurity education. He has contributed extensively to curricular guidelines (e.g., CSEC 2017) and frameworks for cyber defense. His work spans theoretical advancements (e.g., intrusion detection models) and applied systems (e.g., secure voting platforms). Notable research areas include: Cybersecurity Education: Developing curricula and pedagogical frameworks for secure coding and ethical practices. Insider Threat Mitigation: Declarative approaches and behavioral analysis for detecting and preventing attacks. Malware Mitigation: Techniques leveraging uncertainty principles and defensive programming. Election Security: Analyzing vulnerabilities and designing secure voting systems. Bishop has collaborated with institutions like the Department of Homeland Security (DHS) and National Security Agency (NSA) on critical infrastructure protection. His publications span conferences like IEEE Security & Privacy, HICSS, and NSPW, emphasizing real-world applications of cybersecurity principles.

• Cybersecurity
• Cryptography
• Malware Analysis
• +۳ مورد دیگر

Tudor Dumitras is an Affiliate Associate Professor at the University of Maryland, College Park, holding appointments in the Department of Electrical and Computer Engineering (ECE) and the Department of Computer Science (CS). He is affiliated with The Maryland Cyber Security Center (MC2), where he leads research initiatives in cybersecurity and cryptography. His work focuses on malware detection, system security, and analyzing real-world vulnerabilities like the Heartbleed bug. Dumitras has collaborated with institutions such as Northeastern and Stanford Universities on critical security challenges, including SSL certificate reissuance and revocation strategies. His research interests span machine learning applications in cybersecurity, network security protocols, and adversarial attack mitigation. Notable contributions include developing automated tools for vulnerability exploitation prediction (SCAVY) and investigating the robustness of machine learning models against adversarial examples. Dumitras advises PhD students Simge Tekin and Kamala Varma, focusing on advancing cybersecurity through data-driven approaches. Key projects include analyzing software adoption patterns, studying zero-day attacks, and improving PKI security. His work often bridges academic research with industry practices, leveraging big data from sources like Symantec's WINE system. Dumitras has published extensively on topics ranging from malware behavior analysis to hardware fault attacks on neural networks.

Vasileios P. Kemerlisمشاهده پروفایل

دانشیار

• Software Security
• Hardware Security
• Systems Security
• +۴ مورد دیگر

Vasileios P. Kemerlis is an Associate Professor of Computer Science at Brown University, where he conducts research in systems and software security. He serves as the director of the Secure Systems Lab (SSL) and is a recipient of the prestigious NSF CAREER Award. His work focuses on practical security solutions for real-world systems. Dr. Kemerlis specializes in software, hardware, and systems security with particular emphasis on OS kernel protection, software hardening, fuzz testing, and information flow tracking. His research bridges theoretical security concepts with practical implementations that can be deployed in commodity systems. His work often leverages hardware features to build more robust security mechanisms while maintaining system performance. His recent publications demonstrate a consistent focus on memory safety, control flow integrity, and practical security mechanisms that can be deployed in real-world systems. His work spans multiple security domains including kernel security, network security, and application security, with a strong emphasis on developing solutions that balance security guarantees with practical performance considerations. Scientific Awards: NSF CAREER Award Dr. Kemerlis teaches advanced security courses at Brown University including CSCI 1650: Software Security and Exploitation (offered Fall 2016-2024) and CSCI 2951U: Topics in Software Security (offered Spring 2016-2018, 2020, 2021, 2024). As director of the Secure Systems Lab, he leads research efforts that have resulted in numerous publications at top security venues including IEEE Symposium on Security and Privacy, ACM CCS, and USENIX Security. The Secure Systems Lab under his direction focuses on developing practical security solutions that can be deployed in real-world systems, with recent work exploring hardware-assisted security mechanisms, binary hardening techniques, and novel approaches to memory safety.

Xing Xinyuمشاهده پروفایل

دانشیار

• Kernel Security
• Reverse Engineering
• AI Security
• +۳ مورد دیگر

Xing Xinyu is an Associate Professor of Computer Science at Northwestern University's McCormick School of Engineering. Their research focuses on kernel security, reverse engineering, and AI security, with a strong emphasis on fuzzing techniques, adversarial machine learning, and vulnerability discovery. They hold a PhD from Georgia Institute of Technology, an MS from the University of Colorado Boulder, and a BASc from Beihang University. Research interests include advanced cybersecurity methodologies such as heap memory protection, automated exploit generation, and defense mechanisms against adversarial attacks on large language models. Their work bridges theoretical computer science with practical applications in system security and AI ethics. Publications span topics like LLM jailbreak assessments, reinforcement learning optimization, and blockchain anomaly detection. Notable contributions include frameworks like BandFuzz for collaborative fuzzing and SeaK for secure kernel allocators.

• Cybersecurity
• Privacy-Preserving Technologies
• Federated Learning Security
• +۳ مورد دیگر

Alexandra Dmitrienko is a researcher at the University of Würzburg's Institute of Computer Science. Her work focuses on cybersecurity, privacy-preserving technologies, and secure machine learning systems. She has collaborated extensively with institutions like TU Darmstadt and the University of California. Her research spans federated learning security, IoT device protection, Tor network analysis, and mobile platform vulnerabilities. Key contributions include defenses against poisoning attacks in federated learning, analysis of contact discovery exploits in messengers, and practical SGX cache attack mitigations. She has authored over 90 publications across top conferences like NDSS, CCS, and USENIX Security, and contributed to open-source tools like DNNShield and ClearMark for model ownership verification.

• Cybersecurity
• Computer Security
• Hardware Security
• +۶ مورد دیگر

Herbert Bos is a Full Professor at Vrije Universiteit Amsterdam, holding positions in the Faculty of Science (Computer Systems department), the Network Institute, and the Systems and Network Security group. His research focuses on hardware and software security, including transient execution attacks, memory exploitation, and vulnerability detection. He has authored over 229 research outputs, including influential papers on Spectre mitigation, Rowhammer attacks, and fuzzing techniques. Notable contributions include frameworks like PANDAcap and BinRec. Bos teaches courses such as Binary and Malware Analysis and Operating Systems. His work aligns with UN Sustainable Development Goals related to innovation and infrastructure security. Education details are not explicitly provided, but his academic titles (prof. dr. ir.) suggest advanced degrees in computer science and engineering. Ancillary activities include roles as an author for Pearson textbooks and a member of the Kiesraad in The Hague. Research interests emphasize cutting-edge hardware vulnerabilities (e.g., Spectre, Rowhammer), memory safety, and automated testing (fuzzing). Recent work highlights practical defenses against transient data leaks (Phantom Trails) and data-only attacks. Collaborations span international institutions, reflecting his global influence in cybersecurity. Publications since 2016 showcase advancements in CPU architecture security, kernel exploitation, and embedded device defenses. His datasets (e.g., PANDAcap SSH Honeypot) provide foundational resources for the security community. Grants and lab affiliations are inferred through his research outputs and teaching roles.

Hamed Ghavamniaمشاهده پروفایل

استادیار

• System/Software Security
• Attack Surface Reduction
• Memory Safe Languages
• +۲ مورد دیگر

Hamed Ghavamnia is a Security Researcher at Bloomberg, where he focuses on software and systems security. Previously, he served as an Assistant Professor at the School of Computing, University of Connecticut (2023–2024). He holds a PhD in Computer Science from Stony Brook University (under Michalis Polychronakis), an M.S. in Computer Engineering from Sharif University of Technology (Network Security focus), and a B.E. in Software Engineering from University of Isfahan. His research interests center on system/software security, particularly attack surface reduction through program analysis and memory-safe languages. Key projects include Confine (system call policy generation for containers), Temporal Specialization (system call filtering based on execution phases), and LeakLess (data protection in serverless platforms). He has contributed to seminal works on configuration-driven security (C2C), memory protection (xMP), and automated policy inference. His work bridges static/dynamic analysis, program specialization, and security hardening. Notable outcomes include reducing attack surfaces via system call filtering and debloating techniques, with applications in cloud and containerized environments.

• Cybersecurity
• Critical Infrastructure Security
• Reinforcement Learning
• +۳ مورد دیگر

Laszlo Tibor Erdodi is an Associate Professor at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Information Security and Communication Technology within the Faculty of Information Technology and Electrical Engineering . His research focuses on cybersecurity in critical infrastructure, reinforcement learning for penetration testing, and vulnerability exploitation in power grid systems. Erdodi collaborates with institutions like CIGRE and IEEE on projects evaluating security of wide-area monitoring systems and industrial control systems. Key research areas include advanced persistent threats (APT) targeting power grid substations, stealthy data integrity attacks on critical infrastructure, and the application of reinforcement learning to simulate cyber-attacks (e.g., SQL injection and CTF challenges). His work often involves hardware-in-the-loop testbeds to assess vulnerability mitigation strategies in real-world scenarios. Publications emphasize cybersecurity for industrial control systems, penetration testing methodologies, and ethical hacking frameworks. Notable contributions include studies on IEC 61850/60870-5-104 protocol vulnerabilities, PTP timing attacks in substations, and lightweight IoT security solutions (e.g., LIST framework). Erdodi’s work bridges theoretical cybersecurity models with practical implementation, addressing challenges in both academic and industrial sectors. He contributes to conferences like IEEE PES ISGT Europe and CIGRE symposiums, focusing on resilient critical infrastructure design and automated threat detection systems.

Qing Caoمشاهده پروفایل

دانشیار

• AI for Cyber-Physical Systems
• Networking and Distributed Systems
• Cyber Security
• +۵ مورد دیگر

Qing 'Charles' Cao is an Associate Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, part of the Tickle College of Engineering. His research focuses on AI-driven Cyber-Physical Systems, Networking, and Cyber Security, with applications in IoT, Edge Computing, and Smart Agriculture. He holds a PhD from the University of Illinois at Urbana-Champaign, an MS from the University of Virginia, and a BS from Fudan University, China. Education: PhD in Computer Science, University of Illinois at Urbana-Champaign, 2008 MS in Computer Science, University of Virginia, 2005 BS in Computer Science, Fudan University, Shanghai, China, 2002 Research Interests: His work emphasizes interdisciplinary solutions at the intersection of AI, networking, and security. Key areas include: - Blockchain-based security mechanisms for edge devices - LLM applications in public policy and climate decision-making - IoT-driven precision agriculture and livestock health monitoring - Probabilistic error reasoning and fault tolerance in distributed systems Grants & Awards: No awards explicitly listed, but his research has been supported by grants in areas like smart agriculture and edge computing infrastructure. Advising & Labs: While specific advisees are not listed, his research group focuses on collaborative projects involving students in cybersecurity, IoT, and AI systems. He has contributed to lab initiatives related to environmental computing and distributed sensor networks. Professional Activities: Active in conferences like AAAI, IEEE IPCCC, and ACM/IEEE Edge Computing Symposiums, presenting on topics ranging from LLM-assisted governance to secure edge architectures.

Farshad Firouziمشاهده پروفایل

استادیار مدعو

• Edge Computing
• Internet of Things (IoT)
• Artificial Intelligence
• +۴ مورد دیگر

Farshad Firouzi serves as an Adjunct Assistant Professor in the Department of Electrical and Computer Engineering at Duke University, where he teaches EGR 393: Research Projects in Engineering. His academic work bridges hardware and software domains with a strong emphasis on practical applications in critical systems. His research spans Edge Computing, Internet of Things (IoT), Artificial Intelligence, Machine Learning, Healthcare Systems, Chip Design, and Reliability Engineering. This interdisciplinary focus manifests in projects ranging from Parkinson's disease monitoring using edge devices to LLM-enhanced chip design and security-hardened neural networks. His work consistently addresses real-world challenges in system dependability, particularly in healthcare and biomedical contexts where failure is not an option. Analysis of his 2024-2025 publications reveals three dominant research thrusts: (1) LLM applications in hardware design (ChipMnd, Spiced), (2) Edge-based healthcare monitoring systems (freezing of gait recognition, blood glucose prediction), and (3) Security and reliability in AI/ML systems (gradient inversion defense, silent data corruption mitigation). His work demonstrates a clear trajectory toward integrating cutting-edge AI techniques with hardware-aware solutions for mission-critical applications. No scientific awards were mentioned in the source materials. The absence of student listings or grant information suggests his current role may be primarily research-focused without formal advising responsibilities. Similarly, no dedicated labs or research teams were referenced in the available documentation.