جست‌وجوی استاد و پژوهشگر

Xinwen Fuمشاهده پروفایل

استاد

• Computer Security and Privacy
• IoT Security and Privacy
• Mobile Security
• +۷ مورد دیگر

Dr. Xinwen Fu is a Professor in the Miner School of Computer & Information Sciences at the University of Massachusetts Lowell, where he also serves as Director of the iSAFER Center. He received his Ph.D. in Computer Engineering from Texas A&M University (2005), M.S. in Electrical Engineering from University of Science and Technology of China (1998), and B.S. in Electrical Engineering from Xi'an Jiaotong University (1995). Research Interests Dr. Fu specializes in Computer Security and Privacy , with particular focus on IoT Security , Mobile Security , Network Security , and Digital Forensics . His research has been published in all four top computer security conferences: IEEE Symposium on Security and Privacy (S&P/Oakland), ACM Conference on Computer and Communications Security (CCS), USENIX Security Symposium, and Network and Distributed System Security Symposium (NDSS), as well as prestigious journals like ACM/IEEE Transactions on Networking and IEEE Transactions on Dependable and Secure Computing. His work has gained significant media attention from CNN, Wired, Huffington Post, Forbes, Yahoo, MIT Technology Review, and PC Magazine, including multiple appearances on CNN Domestic and International. He has also served as TPC member for numerous prestigious conferences including ACM CCS, IEEE INFOCOM, and IEEE ICDCS. Scientific Awards Best paper award at IEEE International Conference on Industrial Internet (ICII) 2019 Best paper award, International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2017 Teaching Excellence Award of Department of Computer Science, UMass Lowell, 2016 Best paper award, International Performance Computing and Communications Conference (IPCCC) 2016 Award of Excellence, GeekPwn 2016 Ethic Smart Life Hack Competition Erich Spengler Student Cyber Paper Award with students, The Colloquium for Information Security Education (CISSE), 2016 Spotlight Paper of the IEEE Transactions on Mobile Computing (TMC), February 2014 Best paper award, International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2013 Best paper award, IEEE International Conference on Communications (ICC): Communications and Information Security Symposium, 2013 Teaching award, Department of Computer Science, University of Massachusetts Lowell, 2011

Ardalan Amiri Saniمشاهده پروفایل

دانشیار

• Mobile Systems
• Operating Systems
• Security
• +۵ مورد دیگر

Ardalan Amiri Sani is an Associate Professor in the Computer Science Department at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information & Computer Sciences. He leads the Trustworthy Systems Lab (TrussLab), focusing on secure and reliable mobile systems, operating systems, and virtualization. His research bridges mobile computing, security, and OS design, addressing challenges in I/O devices, kernel hardening, and verifiable provenance. Education: Ph.D. and M.Sc. from Rice University (ECE), B.Sc. from Sharif University of Technology. Awards include the NSF CAREER Award, Google ASPIRE Award, and UCI Dean's Mid-Career Research Award. He has advised numerous graduate and undergraduate students, many of whom now work in academia and industry. Research highlights include Tabellion (secure legal contracts on mobile devices), ProvCam (verifiable video provenance), and work on minimizing smartphone TCBs via hardware isolation. His grants include NSF funding for OS kernel security and NSA support for provenance systems. Education: Ph.D., Electrical and Computer Engineering, Rice University, 2014 B.Sc., Electrical Engineering, Sharif University of Technology Grants: $500K NSF Award (with UCR) for OS kernel security (2020) NSF SaTC Award for GPU security in browsers Google ASPIRE Award for Android system call filtering Labs/Teams: Trustworthy Systems Lab (TrussLab), collaborating with industry partners like Intel and Broadcom.

• Cybersecurity
• Software Security
• System Security
• +۶ مورد دیگر

Ruoyu (Fish) Wang is an Associate Professor at the School of Computing and Augmented Intelligence, Arizona State University (Tempe campus). He also holds affiliations as Associate Director of Impact at the Global Security Initiative, Center for Cybersecurity & Trusted Foundations, and with the Biodesign Center for Biocomputing, Security and Society. His educational background includes: Ph.D. in Computer Science, University of California, Santa Barbara Professor Wang's research focuses on system security, with an emphasis on automated binary program analysis and reverse engineering of software. He is the co-founder and core developer of the angr binary analysis platform, which won third place in the DARPA Cyber Grand Challenge (2018). His work spans vulnerability discovery, fuzzing, and security tool development for binary program analysis. His current research interests include: Binary program analysis and reverse engineering Automated vulnerability discovery and mitigation Fuzzing techniques and robust testing Phishing and fraud detection in e-commerce Security of firmware and embedded systems Application of machine learning to security problems His recent publications (2024-2025) demonstrate cutting-edge research in fraud detection for e-commerce using LLMs, advanced fuzzing methodologies, and binary decompilation techniques. Key trends include bridging theoretical program analysis with practical security tools, as evidenced by extensions to the angr platform, and addressing emerging threats in financial ecosystems and client-side security. Dr. Wang has received notable recognition: Third place in DARPA Cyber Grand Challenge (2018) with team Shellphish As an active educator, he supervises graduate research (CSE 599/799) and teaches core cybersecurity courses including Software Security (CSE 545) and Information Assurance (CSE 365). His teaching spans multiple semesters through 2025, covering practicums, internships, and special topics in computing security. Dr. Wang co-founded the angr binary analysis platform and contributes to Arizona State University's security research ecosystem through leadership roles in the Center for Cybersecurity & Trusted Foundations and Biodesign Center for Biocomputing, Security and Society.

• IoT Security
• AI Security
• Wireless Networks
• +۲ مورد دیگر

Xiaojiang Du is the Anson Wood Burchard Endowed Professor at Stevens Institute of Technology, directing research in IoT security, AI security, and wireless networks. An IEEE Fellow and ACM Distinguished Member, he leads NSF-funded projects on secure IoT systems and cross-platform security vulnerabilities. Education PhD in Electrical Engineering, University of Maryland MS in Electrical Engineering, Tsinghua University BE in Electrical Engineering, Tsinghua University Research Focus: Develops security frameworks for IoT ecosystems and adversarial machine learning, with recent breakthroughs in smart home security anomaly detection. Honors: IEEE Fellow, ACM Distinguished Member, multiple best paper awards at IEEE conferences. Graduated PhD students hold faculty positions at UNC Charlotte, UL Lafayette, and ShanXi University. Professional Service: IEEE ComSoc Distinguished Lecturer, Associate Editor for IEEE Transactions, and General Co-Chair for IEEE/ACM IWQoS 2023. Secured $9M+ in research funding from NSF, NSA, and DOD.

Danyang Zhuoمشاهده پروفایل

استادیار

• Datacenter and Cloud Computing
• Machine Learning Systems
• Operating Systems
• +۳ مورد دیگر

Danyang Zhuo is an Assistant Professor of Computer Science at Duke University, Trinity College of Arts & Sciences, with expertise in datacenter/cloud computing and machine learning systems. He joined Duke in 2020 after postdoctoral research at UC Berkeley under Ion Stoica and a PhD at the University of Washington advised by Tom Anderson and Arvind Krishnamurthy. Education: PhD in Computer Science (University of Washington, 2019) His research focuses on improving cloud infrastructure through systems like Phoenix (application-level abstractions) and Phantora (GPU cluster simulation). Recent work explores LLM verification, tensor compression via video codecs, and fairness in LLM serving. His 15 most recent publications span operating systems, machine learning, and networked systems conferences like HOTOS, NSDI, SIGCOMM, and OSDI. Scientific honors include NSF CAREER Award (2023), USENIX Security Distinguished Paper (2023), and multiple industry research awards. He has secured major NSF grants for projects including "OS-Managed Remote Procedure Call" and "Campus-level RDMA Networking." At Duke, he advises PhD students and teaches courses such as Introduction to Operating Systems (CompSci 310) and Systems for Machine Learning (CompSci 590.05). His work appears in leading conferences and journals, with collaborations across institutions including UC Berkeley, University of Washington, and industry partners.

Peter Dindaمشاهده پروفایل

استاد

• Parallel and Distributed Systems
• Virtualization
• Operating Systems
• +۸ مورد دیگر

Peter Dinda is a Professor in the Department of Computer Science at Northwestern University , with a secondary appointment in the Department of Electrical and Computer Engineering . He has authored over 130 scientific papers, holds five patents, and is a Fellow of the IEEE . As the former head of the Computer Engineering and Systems division, he has contributed extensively to experimental computer systems. Education: B.S. in Electrical and Computer Engineering from the University of Wisconsin Ph.D. in Computer Science from Carnegie Mellon University Research Focus: Experimental computer systems, particularly parallel and distributed systems , virtualization , operating systems , and empathic systems that integrate user satisfaction with systems-level decision-making. His work also spans compiler design, memory management, and hardware-software co-design for performance optimization. Recent Trends: His publications emphasize virtualization efficiency, memory protection frameworks, parallel programming language design, and power management in heterogeneous computing environments. Key areas include exascale systems, IoT privacy, and physiological sensor-based user modeling. Scientific Awards: Fellow, IEEE Leadership: Served as Director of Graduate Studies and previously led the Computer Engineering and Systems division.

Yan Chenمشاهده پروفایل

استاد

• Cybersecurity
• Networking
• Distributed Systems Security
• +۵ مورد دیگر

Yan Chen is a Professor of Computer Science at Northwestern University's Robert R. McCormick School of Engineering and Applied Science. He leads the Northwestern Lab for Internet and Security Technology (LIST) and the Center for Ultra-scale Computing and Information Security. His research focuses on cybersecurity, network measurement, and distributed systems security. Chen holds a Ph.D. from UC Berkeley (2003), M.S. from SUNY Stony Brook, and B.E. from Zhejiang University. Research interests include securing networking systems, intrusion detection, cloud-native platforms, and mobile security. Notable awards include the DOE Early CAREER Award (2005), Air Force Young Investigator Award (2007), and ACM ASPLOS'18 Most Influential Paper Award. His work has been cited over 17,000 times with an h-index of 62 (2024). Key contributions include the LIST lab's advancements in APT detection, provenance tracking in microservices, and security frameworks like FlowCog. He advises numerous Ph.D. students and has graduated over 20 researchers now in academia and industry.

• Formal Verification
• Software Testing
• Programming Languages
• +۱۲ مورد دیگر

Alastair F. Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he leads the FastPL research group. His work bridges formal methods, software testing, and programming languages, with a focus on enhancing the reliability of high-performance and parallel software systems. He has held key roles including Director of Research (since 2023) and previously served as Lecturer (2011–2014), Senior Lecturer (2014–2017), and Reader (2017–2020) before being promoted to Professor in 2020. His research interests include formal verification, compiler testing, GPU programming, concurrency, and fuzzing. He has made significant contributions to the verification of GPU kernels, metamorphic testing of graphics drivers, and the development of tools like GPUVerify and GraphicsFuzz. His work combines theoretical rigor with practical impact, demonstrated by the acquisition of his startup GraphicsFuzz by Google in 2018 and his subsequent roles as Senior Software Engineer and Visiting Researcher at Google. His recent publications reflect a sustained focus on compiler and system reliability, with trends in fuzzing, formal specification, and automated testing of complex systems such as WebGPU, CXL cache coherence, and large language models for code generation. His work increasingly integrates empirical validation with formal techniques to uncover subtle bugs in real-world systems. Scientific awards and recognitions include: 2017 BCS Roger Needham Award EPSRC Early Career Fellowship Fellow of the British Computer Society Best Paper awards at EuroSys 2024, MET 2021, IISWC 2019, IWOCL 2019, and ICST 2016 Best Industry Paper at ICST 2024 ACM SIGSOFT Distinguished Paper at ISSTA 2023 ACM SIGPLAN Most Influential OOPSLA Paper Award (2012 paper), awarded in 2022 Best Student Paper at PPoPP 2014 He has advised numerous PhD students and leads a vibrant research group. He has secured significant research funding and collaborates extensively with industry and academia. His service includes leadership roles such as General Chair of PLDI 2020, PC Chair of ECOOP 2019, and Steering Committee Chair of PLDI (2022–2025). He also serves on the advisory board of PACM-PL and on program committees for top venues including POPL, OOPSLA, PLDI, ICSE, and ISSTA. He leads the FastPL research group, which focuses on the design and implementation of programming tools and techniques for reliable software. The group conducts cutting-edge research in compiler testing, formal methods, and high-performance systems, fostering collaboration across academia and industry.

• Digital Provenance
• Operating Systems
• Distributed Systems
• +۵ مورد دیگر

Thomas Pasquier is an Assistant Professor in the Department of Computer Science at the University of British Columbia, affiliated with the Systopia Lab and UBC Security & Privacy Group. His research focuses on digital provenance, system auditing, intrusion detection, and performance optimization. He investigates systems security through provenance graph analysis, developing practical frameworks for intrusion detection (including PROVNET and Kairos) and provenance summarization tools. His work combines machine learning with systems research to enhance cybersecurity transparency. Recent Publications (2022-2025) Provenance-based intrusion detection systems analysis Whole-system provenance for practical security eBPF kernel extension security enhancements LLM-driven provenance summarization Research code quality assessment Scientific Awards Incredible Instructor Awards Amazon Science Research Award He supervises graduate students in systems security research and teaches courses on security & privacy and operating systems. His lab welcomes diverse students for thesis-based research opportunities.

Yonghwi Kwonمشاهده پروفایل

استادیار مهمان

• Software Systems Security
• Cyber Forensics
• Software Engineering
• +۳ مورد دیگر

Yonghwi Kwon is a Visiting Assistant Professor in the Department of Computer Science at the University of Virginia. His research focuses on software systems security, cyber forensics, and software engineering. He received the CAREER Award for developing dynamic defenses against cyber threats. His work emphasizes securing software from cyber attacks, recovering forensic evidence, and improving software testing and reverse engineering techniques. Key research areas include memory safety mechanisms, automated vulnerability detection in web applications and mobile systems, and forensic analysis of phishing campaigns. He has pioneered frameworks like CMASan for memory allocator-aware sanitization and Racedb for detecting race conditions in database-backed systems. His contributions span cloud security automation, kernel exploitation analysis, and embedded system fuzzing. Notable achievements include the 2025 CAREER Award supporting his dynamic defense research, and impactful publications in areas like Android information leakage detection (DryJIN), Bluetooth protocol fuzzing (BTFuzzer), and autonomous driving bug discovery (Drivefuzz). His work bridges theoretical computer science with practical cybersecurity solutions.

Andrea Bastoniمشاهده پروفایل

پژوهشگر ارشد

• Real-Time Systems
• Cyber-Physical Systems
• Operating System Design
• +۵ مورد دیگر

Dr. Andrea Bastoni is a Postdoctoral Researcher and Research Fellow at the Chair of Cyber-Physical Systems in Production Engineering at Technical University of Munich (TUM), Faculty of Mechanical Engineering. He is also the CTO and co-founder of Minerva Systems , developing operating system solutions for AI-ready embedded applications. His expertise spans real-time operating systems, cyber-physical systems, and predictable system design for heterogeneous platforms. His research focuses on enhancing predictability of memory hierarchies in complex SoCs through techniques like memory bandwidth regulation and cache partitioning. This work has industrial applications in safety-critical domains such as avionics and railways, where he contributes to certifiable hypervisors and operating systems. As former Software Architect of the PikeOS hypervisor at SYSGO GmbH (2012-2020), he specialized in DO-178C, IEC 61508, and EN 50128 standards. His academic background includes a Ph.D. in Computer Engineering from the University of Rome Tor Vergata (2007-2011), where he developed LITMUS^RT as part of UNC's Real-Time Systems Group during a visiting researcher period (2009-2010). His publications reflect ongoing work on Multicore Real-Time Scheduling , Mixed-Criticality Task Isolation, and Arm DynamIQ shared unit analysis. He actively participates in program committees for conferences like RTSS, DSN, and DATE.

Gero Mühlمشاهده پروفایل

استاد

• Distributed systems
• Distributed algorithms
• Event-based systems
• +۷ مورد دیگر

Prof. Dr.-Ing. habil. Gero Mühl is a W2-Professor at the University of Rostock, where he holds the chair for "Architecture of Application Systems" since October 2009. His academic journey includes positions as a Heisenberg Fellow at the Technical University of Berlin (2009), postdoctoral research at TU Berlin (2002-2009), and doctoral studies at TU Darmstadt where he received his Dr.-Ing. degree with distinction in 2002. He completed dual Diplomas in Computer Science (Dipl.-Inform.) and Electrical Engineering (Dipl.-Ing.) from FernUniversität in Hagen in 1998. Prof. Mühl's research focuses on Self-Organizing Distributed Systems , with particular expertise in distributed systems, distributed algorithms, event-based systems, middleware, energy-efficient systems, organic computing, sensor networks, web services, and electronic commerce. His work bridges theoretical foundations with practical implementations in real-world distributed environments. His recent publications show a strong trend toward time-sensitive networking, content-based publish/subscribe systems, and P4 programmable data planes. These works address critical challenges in industrial communication, real-time systems, and network reliability. His research group has made significant contributions to making distributed systems more autonomous, reliable, and efficient. Scientific awards and recognitions include: Nomination for the Berlin Science Award for Young Scientists (2008) Heisenberg Fellowship by the German Research Foundation (DFG) (2008) Best paper award in System Software and Security at SAC 2015 Prof. Mühl has been actively involved in numerous research projects and collaborations, particularly focusing on self-organizing and self-stabilizing systems. His work on the REBECA publish/subscribe middleware represents a significant contribution to autonomous distributed systems. He has supervised numerous students and researchers, contributing to the development of the next generation of computer scientists specializing in distributed systems. His laboratory at the University of Rostock focuses on practical implementations of self-organizing distributed systems, with current projects investigating time-sensitive networking, publish/subscribe systems, and energy-efficient distributed computing. The team combines theoretical analysis with practical system development to address real-world challenges in industrial and commercial applications of distributed systems.

Baishakhi Rayمشاهده پروفایل

دانشیار

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Baishakhi Ray is an Associate Professor at Columbia University, specializing in improving software reliability and developers' productivity for both traditional and AI-driven systems. She leads the ARiSE Lab, focusing on interdisciplinary research at the intersection of software engineering and artificial intelligence. Her research interests include software testing for AI systems, adversarial robustness, automated testing of autonomous systems, and leveraging AI techniques such as neural networks for dynamic analysis and fuzzing. Notable projects include DeepTest for autonomous car testing and NEUZZ for efficient fuzzing. Awards: VMware Early Career Faculty Award (2020), IBM Faculty Award (2019), NSF CAREER Award (2019), and multiple best paper awards including EAPLS FASE (2020) and ACM Distinguished Papers (FSE 2017, MSR 2017). Grants: NSF CAREER grant (2019-2024) for deep learning testing, NSF grants for workshops and security bug detection, and collaborative grants on persistent memory and SSL/TLS implementations. Her recent work emphasizes advancing code generation with large language models (LLMs), evaluating model robustness under data contamination, and developing tools like CodeSense and CrashFixer for code semantics and kernel debugging. The ARiSE Lab also explores causal performance debugging and transfer learning for configurable systems.

• Distributed Systems
• Embedded Systems
• Ubiquitous Computing
• +۳ مورد دیگر

NAKAJIMA, Tatsuo serves as a Professor at Waseda University's School of Fundamental Science and Engineering, Department of Computer Network Engineering. Holding a Doctor of Engineering from Keio University, he has been affiliated with Waseda since 1999 after positions at Japan Advanced Institute of Science and Technology (1993-1999), Cambridge University, and Carnegie Mellon University. His academic profile shows substantial research output with 433 papers and 3,338 citations on Scopus, and 7,604 citations with an h-index of 42 on Google Scholar. Dr. Nakajima's research focuses on Distributed Systems, Embedded Systems, and Ubiquitous Computing, with particular emphasis on virtualization architectures for embedded environments. His work bridges theoretical computer science with practical applications in information appliances, operating systems, and persuasive computing technologies. He has developed innovative systems including SPUMONE (a composition kernel for multi-OS environments), SIGMA System, and SPLiT (a performance optimization library for multicore processors). Analysis of his 15 most recent publications reveals a consistent research trajectory centered on enhancing reliability, security, and performance of embedded and pervasive computing systems. His work shows increasing integration of human factors, particularly in sustainable behavior applications through persuasive technology. The research spans from low-level system architecture to user-centered applications, demonstrating both technical depth and practical relevance. Nokia Research Center, Visiting Research Fellow (2005.04) Dr. Nakajima's research has produced numerous practical frameworks including SPUMONE for multi-OS environments, SPLiT for performance optimization, and persuasive applications like EcoIsland for sustainable behavior. His work on kernel monitoring, anomaly detection, and self-healing systems demonstrates strong focus on system dependability. Current research appears directed toward integrating human factors with embedded systems, particularly in environmental sustainability applications. His laboratory work centers around the SPUMONE project, a virtualization layer for multi-core embedded systems that enables multiple operating systems to coexist with minimal engineering cost. This research environment supports exploration of resource management, security monitoring, and performance optimization in embedded contexts. The work has practical applications in information appliances, smart homes, and pervasive computing environments.

Srinivas Narayanaمشاهده پروفایل

استادیار

• Computer Networks
• Formal Verification
• Compilers
• +۴ مورد دیگر

Srinivas Narayana is an Assistant Professor in the Department of Computer Science at Rutgers University, specializing in programmable networking, formal verification, and systems research. He holds a PhD from Princeton University and a B.Tech from IIT Madras, with postdoctoral work at MIT. His research focuses on building safe, high-performance networks through optimizing compilers, verified programming, and distributed system monitoring. He has received NSF grants, the CGO 2022 Distinguished Paper Award, and the 2017 SIGCOMM Best Paper Award. Education: PhD and MA in Computer Science, Princeton University (2016) B.Tech in Computer Science, IIT Madras (2010) Postdoctoral Research, MIT (2018) Research Interests: His work bridges networking and systems with a focus on compilers, formal methods, and programmable hardware. Notable projects include K2 compiler for eBPF, the eBPF verifier soundness work, and congestion control mechanisms like CCP. He explores parallel packet processing, privacy-preserving analytics, and load balancing strategies. Grants & Awards: NSF Awards #2422076, #1910796, #2019302 eBPF Foundation Grant Facebook Networking Research Award Network Programming Initiative (NPI) Funding Lab & Teams: Leads the NetSys group at Rutgers, collaborating with teams on projects like the eBPF verifier, verified packet processing, and network monitoring tools like Marple. His lab emphasizes open-source contributions and industry collaboration.