جست‌وجوی استاد و پژوهشگر

Zachary Petersonمشاهده پروفایل

استاد

• Cybersecurity
• Computer Security Education
• Privacy
• +۵ مورد دیگر

Zachary Peterson is a Professor in the Department of Computer Science at California Polytechnic State University (Cal Poly), specializing in cybersecurity education and privacy research. He develops innovative pedagogical tools such as Fakesbook (a simulated social network for teaching privacy concepts) and cybersecurity ARGs (Alternate Reality Games) to engage students in security practices. His work bridges technical cybersecurity challenges with educational outreach, particularly for K-12 and undergraduate audiences. Research Focus: Peterson's research spans cybersecurity education, privacy-enhancing technologies, and secure file systems. He emphasizes inclusive design principles, such as browser security for visually impaired users, and has explored compliance frameworks for regulatory requirements in healthcare and federal systems. His work also addresses emerging threats in cyber-physical systems like autonomous vehicles. Awards & Recognition: A Fulbright Scholar in cybersecurity, Peterson has received prestigious grants including the NSF SaTC Award and Google CS Engagement Award. His contributions to cybersecurity competitions and underrepresented group participation have shaped educational equity initiatives in the field. Grants & Advising: Leads NSF-funded projects for K-12 cybersecurity education and advises initiatives such as the GenCyber Teacher Training program. His collaborations include industry partnerships and international lectures at venues like UCL's Cybersecurity Research Centre. Key Platforms: Active in conferences like USENIX Security, IEEE S&P, and SIGCSE. Develops open-source tools for secure storage (e.g., DEFY file system) and cybersecurity training platforms. His research outputs span over 30 peer-reviewed articles and patented technologies.

Samuli Reijulaمشاهده پروفایل

دانشیار

• Philosophy of Science
• Cognitive Science
• Scientific Problem Solving
• +۷ مورد دیگر

Samuli Reijula is a University Lecturer in Theoretical Philosophy at the University of Helsinki, holding a permanent faculty position equivalent to US associate professor. He is also a docent (habilitation / adjunct professor) in Practical Philosophy and an Academy Research Fellow. Reijula is affiliated with the TINT Centre for Philosophy of Social Science and specializes in the philosophy of science, cognitive science, and institutional epistemology. His research focuses on how science works as a distributed cognitive system, examining scientific problem-solving at multiple levels from individual scientists to research groups and scientific communities. Reijula investigates cognitive diversity, coping with uncertainty, epistemology of simulation modeling, foundations of scientific classification, and issues related to the science of science, scientific discovery, and science policy. He is particularly interested in viewing science as a collective cognitive system and understanding the social, cognitive, and institutional preconditions for well-functioning scientific research. Reijula's recent publications explore topics including objectivity in academic recruitment, AI and epistemic humility, the Fediverse as a solution to epistemic challenges in the AI era, diversity in scientific communities, and the concept of Bildung university. His work often bridges philosophy with practical policy implications, addressing issues like inheritance tax policy, public authorities' use of social media platforms, and the philosophical foundations of open science. He has received research funding from the Academy of Finland for his project 'Modeling the republic of science: Collaborative problem solving and collective rationality in scientific inquiry' (2020-2025). Reijula is scheduled to visit Carnegie Mellon University's Center for Formal Epistemology and Institute for Complex Social Dynamics in October-November 2024. His approach integrates philosophical analysis with computational methods, particularly agent-based modeling, to understand scientific communities as complex adaptive systems.

• Hardware Security
• Cryptographic Circuits
• Formal Methods
• +۳ مورد دیگر

Devanshi Upadhyaya is a Researcher at the Institute of Computer Architecture and Computer Engineering under the University of Stuttgart. Her work focuses on hardware security, cryptographic circuit protection, and formal methods for analyzing vulnerabilities in embedded systems. She is actively engaged in advancing secure hardware design principles through research in side-channel attacks, fault injection, and logic locking mechanisms. Her research interests include cryptographic circuit security, formal verification of hardware systems, and securing neural network accelerators. She has contributed to developing frameworks that assess vulnerabilities in mixed-signal and approximate computing architectures, emphasizing practical defenses against both software and hardware-based attacks. Notable projects include optimizing waveform accurate fault attacks and enabling power side-channel simulations for AI hardware accelerators. Her work bridges theoretical security models with real-world hardware implementation challenges. Devanshi holds a M.Sc. degree and is affiliated with the Hardware Oriented Computer Science department at the University of Stuttgart, where she collaborates on interdisciplinary projects involving cryptography, embedded systems, and machine learning hardware.

Andrew Winslowمشاهده پروفایل

مدرس پاره‌وقت

• Computational Geometry
• Algorithmic Self-Assembly
• Discrete Geometry
• +۳ مورد دیگر

Andrew Winslow is a Part-time Lecturer in the Department of Computer Science at Tufts University, affiliated with the School of Engineering. Previously, he held positions as an Assistant Professor at the University of Texas Rio Grande Valley and worked as a software engineer at Google, Boeing, and Arizona State University. His research interests span computational geometry, algorithmic self-assembly, discrete geometry, computational complexity, and recreational mathematics. He has contributed to theoretical computer science, focusing on self-assembly systems, geometric algorithms, and puzzle complexity analysis. Winslow's work emphasizes algorithm design, with notable contributions to tile assembly models, motion planning, and geometric unfolding problems. His research bridges theoretical foundations with practical applications, such as molecular computing and game puzzle analysis. He has published extensively in venues like the Symposium on Theoretical Aspects of Computer Science (STACS) and the European Symposium on Algorithms (ESA). His academic journey includes roles in both academia and industry, reflecting a commitment to interdisciplinary problem-solving. While no formal awards are listed, his publications indicate recognition within computational geometry and self-assembly communities. Winslow’s advising and grant activities are not detailed in the provided texts, though his research collaborations suggest active participation in academic networks. He maintains a presence at Tufts University’s Department of Computer Science, contributing to education and research in theoretical computer science.

Kemal Akkayaمشاهده پروفایل

استاد

• Network Security
• IoT & Cyber-physical System Security
• Key Management
• +۵ مورد دیگر

Dr. Kemal Akkaya is a Professor at the Department of Electrical & Computer Engineering, Florida International University (FIU), where he leads the Advanced Wireless and Security Lab (ADWISE). He holds a Ph.D. in Computer Science from the University of Maryland Baltimore County and has expertise in Network Security, IoT/CPS Security, Blockchain Applications, and 5G Security. His professional roles include serving as Research Director for FIU’s Emerging Preeminent Program in Cybersecurity and as Program Director for the first BS degree in IoT in the U.S. Education: Ph.D. in Computer Science, University of Maryland Baltimore County M.S. in Computer Engineering, Middle-East Technical University, Turkey B.S. in Computer Science, Bilkent University, Turkey Research Interests: Dr. Akkaya focuses on securing IoT and cyber-physical systems, blockchain for micro-payments, and network defense mechanisms. His work emphasizes privacy-aware protocols, secure key management, and SDN/NFV-based solutions. Awards: FIU Faculty Senate Excellence in Research Award (2020) College of Engineering and Computing Faculty Research Award (2020) Top Cited Article Award from Elsevier (2010) Advisees and Grants: While no student names are listed, his lab (ADWISE) likely supports graduate research in IoT and cybersecurity. His grants include interdisciplinary initiatives at FIU, focusing on securing emerging technologies like 5G and blockchain. Labs/Teams: Leads the ADWISE Lab, collaborating on projects like secure IoT payment systems, drone communication security, and resilient smart grid networks.

Lawrence Chungمشاهده پروفایل

دانشیار

• Software Engineering
• Requirements Engineering
• Non-Functional Requirements
• +۳ مورد دیگر

Dr. Lawrence Chung is an Associate Professor of Computer Science at the University of Texas at Dallas, affiliated with the Erik Jonsson School of Engineering and Computer Science. He holds a PhD in Computer Science from the University of Toronto (1993) and has been a faculty member since 1994. His research focuses on software engineering, requirements engineering, and non-functional requirements, with notable contributions to goal-oriented approaches, cloud architecture simulation, and blockchain applications in collaborative systems. Professional Preparation: PhD (1993), M.S. (1981), B.S. (1984), all from the University of Toronto. Prior to academia, he worked in software development at the University of Toronto (1984–1986) and as a Visiting Scholar at Andersen Consulting (1994–1998). Research Interests: Non-functional requirements analysis, software architecture simulation, blockchain for enterprise collaboration, and requirements engineering methodologies. Notable projects include the SilverLining cloud architecture simulator (funded by Google) and frameworks for IoT security policy modeling. Awards: Four Achievement Awards from the World Academy of Sciences (2002–2005) for contributions to computer science research. Active in NSF-funded projects, including $498,323 for Model-Driven Requirements Engineering (2006–2009). Grants and Collaborations: Partnered with Keane Inc., Alcatel, and Texas Enterprise Fund on projects related to software quality and component-based systems. His work often integrates goal-oriented methods with machine learning and big data analytics.

Nur Imtiazul Haqueمشاهده پروفایل

استادیار مهمان

• Cybersecurity
• Machine Learning
• Formal Methods
• +۳ مورد دیگر

Nur Imtiazul Haque is a Visiting Assistant Professor at the University of Cincinnati's School of Information Technology within the College of Education, Criminal Justice, and Human Services (CECH). He holds a Ph.D. and M.Sc. in Electrical and Computer Engineering and Computer Engineering from Florida International University, USA, and a B.Sc. in Computer Science and Engineering from Khulna University of Engineering and Technology (Bangladesh). Previously, he served as a lecturer at Daffodil International University and a graduate research assistant in the Analytics for Cyber Defense lab, where he contributed to NSF and DOE projects. His research focuses on securing cyber-physical systems through formal methods, machine learning, and mathematical optimization, particularly in smart healthcare, smart homes, and industrial IoT. He has published 12 peer-reviewed papers, one book chapter, and patented a tool. Notable achievements include the Best Paper Award at IEEE/IFIP DSN 2023 and the Dissertation Year Fellowship Award. Dr. Haque has organized the International Workshop on AIOTS as publication chair and is an active IEEE member. His work addresses critical infrastructure vulnerabilities, with contributions to frameworks like SHATTER, PHASE, and iDDAF for detecting and mitigating advanced cyber threats.

Ranga Vemuriمشاهده پروفایل

استاد

• Hardware Trust and Security
• VLSI Design
• Formal Verification
• +۵ مورد دیگر

Dr. Ranga Vemuri is a Professor in the Department of Electrical and Computer Engineering at the University of Cincinnati since 1989. His research focuses on Hardware Security, VLSI Design, Formal Verification, Reconfigurable Computing, and Electronic Design Automation. He has advised over 40 PhD and 60 MS students, and his work is funded by agencies like AFRL, DARPA, NSF, and industry partners. Education: Ph.D. in Computer Engineering, Case Western Reserve University (1988) M.Tech. in Computer Engineering, Indian Institute of Technology Kharagpur (1984) B.Tech. in Electronics and Communications Engineering, Nagarjuna University (1983) Research Interests: Dr. Vemuri's work spans Hardware Trust and Security , VLSI Design and Architectures , Formal Methods , and Reconfigurable Computing . He pioneers techniques in analog and digital circuit synthesis, FPGA architectures, and leakage-power reduction strategies. His contributions include innovations in post-silicon validation, secure IC design, and side-channel attack mitigation. Grants & Collaborations: He has led over 20 grants totaling millions in funding, including projects on secure system design (SETS), obfuscation of hardware designs, and formal security assertions. Key collaborators include Galois Inc., Air Force Research Laboratory, and EDAptive Computing. Labs & Teams: His research group focuses on secure embedded systems, trusted microelectronics, and post-silicon validation methodologies. Collaborates extensively with industry and government labs on hardware security and design automation challenges.

Fikret Basicمشاهده پروفایل

پژوهشگر

• Battery Management Systems
• Wireless Communication Security
• Embedded Systems
• +۳ مورد دیگر

Fikret Basic is a researcher at the Institute of Technical Informatics at TU Wien, specializing in cybersecurity for embedded systems and battery management systems (BMS). His work focuses on integrating RFID, NFC, and secure communication protocols into industrial and automotive applications. He has led/co-led multiple EU-funded projects including SPiDR, OPEVA, and Intelligent & Networked Embedded Systems. Basic has published extensively at IEEE conferences and received awards such as Scientist of the Year 2024 and AVL Hans List Fonds Preis 2023. His contributions span secure data acquisition, wireless BMS architectures, and authentication mechanisms for IoT devices. Research interests include: Battery Management Systems, Cybersecurity for Industrial Networks, RFID/NFC Applications, Embedded System Security, and IoT Architecture Design. He actively participates in workshops like SPICES 2024 (as Chair) and peer reviews for conferences like EuroPLoP. Basic holds a Dipl.-Ing. (Diploma in Engineering) and a Dr.techn. (Technical Doctorate) in electrical engineering. Projects: SPIDR2 (2025-2028), OPEVA (2023-2025), SPiDR (2021-2024) Grants: AVL Hans List Fonds, Austrian Research Promotion Agency Labs/Teams: Member of TU Wien's Embedded Systems Security Group, collaborates with industrial partners like AVL List GmbH Media engagements include a TV interview in Bosnia discussing academic career paths and a feature in Kleine Zeitung highlighting IT talent development.

Hans-Joachim Wunderlichمشاهده پروفایل

استاد

• Computer Architecture
• Hardware Reliability
• Fault Tolerance
• +۷ مورد دیگر

Prof. Hans-Joachim Wunderlich is a Professor at the University of Stuttgart's Institute of Computer Architecture and Computer Engineering, within the Faculty of Computer Science, Electrical Engineering, and Information Technology. His research focuses on hardware reliability, fault tolerance, and testing methodologies for VLSI circuits and embedded systems. He specializes in areas such as delay fault testing under PVT variability, approximate communication, and aging-aware design. Key research interests include robust testing techniques for small delay faults, error-tolerant communication protocols (e.g., RAPPER and Gray code-based approaches), and GPU-accelerated simulation of faults. His work addresses challenges in functional safety, interconnect reliability, and securing reconfigurable architectures against security violations. He explores energy-efficient iterative solvers for approximate computing environments and develops methods for predicting device aging and early life failures. Prof. Wunderlich’s contributions span academic and industrial applications, with a focus on real-time systems and dependable multi-processor systems-on-chip (MPSoCs). His research integrates formal verification, machine learning for defect detection, and hybrid protection schemes for reconfigurable scan networks. Recent work emphasizes stress-aware testing strategies and optimization of sensor data streaming in resource-constrained environments.

Jianying Zhouمشاهده پروفایل

استاد

• Applied Cryptography
• Network Security
• Cyber-Physical System Security
• +۵ مورد دیگر

Jianying Zhou serves as Professor and Centre Director at Singapore University of Technology and Design (SUTD), leading the iTrust Centre for Research in Cyber Security. He holds a PhD in Information Security from Royal Holloway, University of London and maintains active leadership roles including co-founding ACNS, chairing ACM AsiaCCS steering committee, and serving on Asiacrypt steering committee. PhD in Information Security, Royal Holloway, University of London His research spans applied cryptography, cyber-physical systems security, and mobile/wireless security with emphasis on industrial control systems, blockchain, and automotive networks. Recent work focuses on practical security solutions for critical infrastructure including maritime systems, smart grids, and IoT ecosystems, combining cryptographic innovation with real-world deployment challenges. Analysis of his 2025 publications reveals concentrated efforts in blockchain security (selfish mining, payment channels), industrial IoT protection (PLC authentication, CAN bus intrusion detection), and privacy-preserving machine learning (federated learning attacks/defenses). Maritime cybersecurity and automotive security represent rapidly growing application domains reflecting real-world critical infrastructure needs. Scientific recognition includes: ESORICS Outstanding Contribution Award (2020) ACM Distinguished Member status As iTrust Centre Director, Zhou oversees multi-institutional research teams developing security frameworks for critical infrastructure. While specific student advising details aren't public, his leadership in major conferences indicates extensive mentorship activities. His research program demonstrates strong industry collaboration focus with practical security implementations for maritime, healthcare, and industrial systems. iTrust operates as SUTD's flagship cybersecurity research center under Zhou's direction, bringing together interdisciplinary teams to address cyber-physical security challenges through testbed development, protocol design, and risk assessment frameworks for critical infrastructure protection.

• Reinforcement Learning
• Robust Optimization
• Machine Learning
• +۱۰ مورد دیگر

Fei Miao is a Pratt & Whitney Associate Professor at the School of Computing, University of Connecticut, and a courtesy faculty member of the Department of Electrical & Computer Engineering. She serves as Director of the Miao Embodied AI Lab and is affiliated with the Institute for Advanced Systems Engineering. Previously, she was a postdoc researcher at the GRASP Lab and PRECISE Lab with Professors George J. Pappas and Daniel D. Lee at the University of Pennsylvania. Dr. Miao received her PhD in Electrical and Systems Engineering from the University of Pennsylvania in 2016, where she also earned a dual Master's degree in Statistics from the Wharton School. She completed her undergraduate studies at Shanghai Jiao Tong University, earning a Bachelor's degree in Automation with a minor in Finance in 2010. Her research focuses on developing the foundations for the science of Embodied AI, with emphasis on assuring safety, efficiency, robustness, and security of cyber-physical systems through the integration of learning, optimization, and control. Her technical expertise spans multi-agent reinforcement learning, robust optimization, uncertainty quantification, control theory, and game theory. These methods are applied to connected and autonomous vehicles, intelligent transportation systems, transportation decarbonization, smart cities, and power networks. Her work involves both theoretical development and practical implementation, including system modeling, theoretical analysis, algorithmic design, and experimental validation using real urban transportation data, simulators, and small-scale autonomous vehicles. Dr. Miao's publication record reveals a strong focus on robustness in AI systems for transportation applications, with recent work emphasizing uncertainty quantification, safety guarantees, and multi-agent coordination. Her research demonstrates a clear trajectory from foundational theoretical work to practical implementations in real-world transportation systems. Her notable awards include the prestigious NSF CAREER Award (2021) for "Distributionally Robust Learning, Control, and Benefits Analysis of Information Sharing for Connected and Autonomous Vehicles," a Best Paper Award at ICCPS'21 for "DeResolver: A Decentralized Negotiation and Conflict Resolution Framework for Smart City Services," and the "Charles Hallac and Sarah Keil Wolf Award for Best Doctoral Dissertation" during her PhD studies. Dr. Miao has secured significant research funding, including a $509,573 NSF CAREER Award (2021-2026) and a $2.3 million NSF collaborative grant as PI of UConn (2020-2023). She has also received multiple NSF grants for projects related to electric vehicle fleets, vehicular sensing, and control for smart city systems. She actively collaborates with researchers across institutions and has given talks at leading universities and industry research labs including CMU, Microsoft Research, Northeastern, Caltech, UCLA, USC, UCSD, Facebook FAIR, Lawrence Berkeley National Lab, UC Berkeley, Nvidia, Stanford, Princeton University, Columbia University, Waymo, and New York University.

• Modeling
• Software Design
• Digital Twins
• +۵ مورد دیگر

Antoine Beugnard is a Professor in the Department of Computer Science at IMT Atlantique (formerly Telecom Bretagne), located on the Brest campus, where he has served since December 2007. His academic journey began at ENST-Bretagne (1986), followed by a Doctorate in Computer Science from the University of Rennes 1 in 1993, and accreditation to supervise research in 2005. His educational background includes: Former student of ENST-Bretagne (1986) Doctorate in Computer Science from University of Rennes 1 (1993) Accreditation to supervise research (2005) Professor Beugnard's research centers on software modeling, particularly focusing on the meaning, notations, and properties like composition of models. Since 2017, he has applied his research to the Industry of the Future, specifically digital twins, participating in the "Digital Twin" working group of the Alliance Industrie du Futur. His work also explores static verification of names in heterogeneous languages, communication abstractions, component-based software engineering, and late-binding semantics in object-oriented languages. As a member of Lab-STICC (UMR 6285) and the P4S team, he contributes to the development of Openflexo for model federation. His recent publications demonstrate a strong evolution from foundational work on object-oriented languages and component models toward practical applications in Industry 4.0 contexts, with a pronounced focus on digital twin technology, model federation, and software engineering approaches to complex systems. The research trajectory shows increasing integration of theoretical modeling concepts with real-world industrial applications. Professor Beugnard has supervised numerous doctoral students throughout his career, guiding research in areas including model federation, digital twins, component-based software engineering, and socio-technical systems. His teaching philosophy emphasizes active learning with project simulations addressing both organizational and technical aspects of software development. He is responsible for the "Ingénierie Logiciel des Systèmes Distribués" (ILSD) thematic deepening program and teaches software engineering, UML design, object-oriented programming with Java, and fundamentals like concurrency, distribution, and design patterns. His approach centers on three principles: "explicitez" (make explicit the process and product at all levels), "adaptez" (adapt rules and methods to context), and "justifiez" (justify decisions and adaptations).

• Computer Engineering
• Hardware Security
• Artificial Intelligence
• +۳ مورد دیگر

Jaan Raik is a Tenured Full Professor and Head of the Centre for Dependable Computing Systems at Tallinn University of Technology (TalTech), Department of Computer Systems. His research focuses on hardware reliability, fault tolerance in embedded systems, and secure computing architectures. Key areas include fault-resilient deep neural network accelerators, approximation methods for DNNs, and vulnerability assessment in hardware-software systems. He leads the Centre for Dependable Computing Systems, which explores advanced reliability engineering techniques for modern computing systems. His work integrates formal verification, machine learning, and hardware design to address challenges in embedded systems, RISC-V processors, and edge AI chips. Notable contributions include frameworks like Saffira for DNN accelerator reliability assessment and innovative methods for assertion-based verification. Research interests span fault diagnosis, approximation computing, and security-aware architectures. He frequently publishes at top venues such as IEEE European Test Symposium and DDECS, with recent focus on resilient neural networks, cache leakage detection (CLD), and hardware Trojan mitigation. Collaborations include industry partnerships for practical deployment of fault-tolerant systems and academic initiatives to standardize reliability assessment methodologies. His work bridges theoretical computer engineering with applied solutions for real-world systems.

Ian Powerمشاهده پروفایل

استادیار

• Carbon Sequestration
• Mine Waste Management
• Natural Analogues for Carbon Mineralization
• +۳ مورد دیگر

Dr. Ian Power is an Assistant Professor and Tier 2 Canada Research Chair in Environmental Geoscience at Trent University's Trent School of the Environment. He leads the PowerGeolab, focusing on CO2 sequestration via mine waste carbonation and enhanced rock weathering. His work bridges geology, geochemistry, and environmental engineering to address climate change challenges while training the next generation of geoscientists. Education: B.Sc. and Ph.D. in Geology from Western University, Professional Geoscientist (P.Geo.) in Ontario. Research interests include carbon mineralization in ultramafic tailings, biogeochemical processes, and sustainable mining practices. Collaborates with industry partners like De Beers and mining companies to advance carbon-neutral technologies. Research Themes: CO2 sequestration in mine wastes (e.g., kimberlite residues, serpentinite) Enhanced rock weathering using mineral feedstocks Microbial mediation of carbonate formation Climate mitigation through geologic CO2 removal Key Projects: Field trials at Trent Experimental Farm and Haliburton Forest CO2 capture studies in South African diamond mines Development of magnesium oxide looping technology Lab & Facilities: PowerGeolab houses advanced equipment for mineral analysis, geochemical experiments, and field monitoring. Collaborates with Trent Water Quality Centre and CFI-funded facilities. Advising & Grants: Supervises 8+ graduate students and postdocs. Active in securing grants from NSERC, Ontario Research Fund, and industry partnerships. Leads Project CarbonVault and mineral carbonation initiatives. Future Work: Expanding ERW applications for agriculture, advancing MgO looping systems, and exploring Mars-analog environments for biosignature preservation studies.