Dr. Mohammad Zulkernine is a Full Professor and Canada Research Chair in Cyber-Physical System Security at Queen’s University’s School of Computing (Faculty of Arts and Science). He leads the Queen’s Reliable Software Technology (QRST) research group and directs the Queen’s Centre for Security & Privacy. His research focuses on secure software systems for cyber-physical systems, including autonomous vehicles, IoT, and cloud computing. Dr. Zulkernine holds a cross-appointment in Electrical and Computer Engineering and is a licensed Professional Engineer in Ontario. Education: BSc (Bangladesh BUET), MEng (Japan), PhD (University of Waterloo). He joined Queen’s in 2003 and has held sabbaticals at University of Trento, Italy and Irdeto Canada. He has published over 250 papers, led 35+ research projects, and supervised 120+ students. Awards include Canada Research Chairs (Tier I and II), Queen’s Excellence in Graduate Supervision Award, and Distinguished Supervision Award from the School of Computing. Research Interests: Cyber-Physical System Security, Software Reliability, IoT Security, Vehicle Networks, Secure Software Engineering, and Cybersecurity Risk Assessment. Active industry collaborations include EU-funded projects and Canada-Africa initiatives.
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
Soheil Salehi is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at the University of Arizona, with a joint appointment in Systems and Industrial Engineering. He is the Director of the Privacy-preserving, Intelligent, and Secure Computing (PRISM) Lab, established in August 2022. Prior to this, he was an NSF-Sponsored Computing Innovation Fellow and Postdoctoral Research Fellow at the University of California, Davis. Ph.D., Electrical and Computer Engineering, University of Central Florida, 2020 M.S., Electrical and Computer Engineering, University of Central Florida, 2016 B.S., Isfahan University of Technology, Iran, 2014 Dr. Salehi's research focuses on the intersection of hardware, AI, and security. His work spans hardware and AI-enabled security in IoT , Generative AI for hardware design and security , neuromorphic and biologically-inspired AI hardware , emerging spin-based devices , reconfigurable architectures , low-power VLSI circuits , and digital twins and mixed reality for semiconductor workforce development . He also explores the application of Generative AI in personalized education . His recent publications, spanning 2023–2025, reveal a strong trend toward integrating AI and machine learning into hardware security and design. Key themes include automated secure IC design flows , AI-driven hardware obfuscation , firmware and side-channel attack analysis , security in neuromorphic and spiking neural networks , and educational frameworks using digital twins and generative models . His work appears in top venues like DAC, ICCAD, USENIX Security, IEEE TCAS-I, and ISCAS. Outstanding Reviewer Award, IEEE/ACM Design Automation Conference (DAC), 2023 Best Presentation of the Symposium Award, UC Davis Postdoctoral Research Symposium, 2021 UCF Excellence by a Graduate Teaching Assistant (University-Level), 2016 Nominated for 30-under-30 Award, UCF, 2020 Nominated for Postdoctoral Research Excellence Award, UC Davis, 2022 Dr. Salehi has secured significant research funding as PI and Co-PI, including a $300K NSF SaTC EAGER grant on Generative AI-based Personalized Cybersecurity Tutor, a $174,000 University of Arizona PIF Award, and multiple RII grants totaling over $198K. He has also received industry funding from CHEST. He actively mentors students and leads the PRISM Lab, which focuses on privacy-preserving and intelligent secure computing. His service includes roles as Technical Program Committee (TPC) Member and Session Chair at premier conferences such as DAC, ICCAD, CCS, NDSS, and GLSVLSI. The PRISM Lab, under his direction, conducts cutting-edge research in secure and intelligent hardware systems, with applications in IoT, edge computing, and workforce development. The lab emphasizes interdisciplinary collaboration and innovation in both research and education.
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.
Dr. Steven H. H. Ding is an Assistant Professor at McGill University's School of Information Studies, specializing in cybersecurity, machine learning, and data mining. His research focuses on AI-driven solutions for malware detection, software vulnerability analysis, and reverse engineering. He holds a PhD from McGill University and has been supported by BlackBerry Cylance and DRDC. His work bridges theoretical advancements with practical applications in military systems and avionics cybersecurity. Dr. Ding earned his PhD in 2019 with notable awards including the FRQNT Doctoral Research Scholarship and McGill's Dean’s Graduate Award. His educational background includes degrees from McGill, Concordia University, and the University of Shanghai for Science and Technology. His research interests span cybersecurity domains such as zero-day malware identification, code obfuscation countermeasures, authorship verification for digital forensics, and AI applications in avionics anomaly detection. He actively contributes to open-source tools like the Kam1n0 MapReduce-based assembly clone search system. Recent work emphasizes adversarial machine learning for evasive malware generation, transformer-based anomaly detection in avionics, and automated SBOM generation for firmware analysis. His publications reflect a focus on real-world cybersecurity challenges in both civilian and defense sectors. Dr. Ding leads the L1NNA Lab and collaborates with industry partners on cutting-edge projects. His contributions include novel techniques for phishing detection leveraging large language models and innovative approaches to reverse engineering software composition in JavaScript applications.
Mauro Conti is a Full Professor at the University of Padua, Italy, where he serves as Editor-in-chief of IEEE TIFS, UniPD Academic Advisor for Entrepreneurship Development, Study Program Coordinator of the MSc degree in Cybersecurity, Head of the SPRITZ Security and Privacy Research Group, and Director of the UniPD node of CINI Cybersecurity National Lab. He also maintains affiliations with TU Delft (NL) and the University of Washington (USA). Additionally, he is the CEO and co-founder of CHISITO and co-founder of DYALOGHI. His research focuses on security and privacy for wireless resource-constrained mobile devices (WSNs, RFIDs, and smartphones), computer system security, computer forensics, access control, and distributed and networked systems. Professor Conti has published extensively in top security venues including ACM CCS, IEEE S&P, NDSS, and USENIX Security, with recent work covering topics such as battery authentication, federated learning privacy, private set intersections, USB peripheral fingerprinting, and ATM PIN inference. He has received numerous prestigious awards including IEEE Fellow, Young Academy of Europe Fellow, EU Marie Curie Fellow, and DAAD Fellow. Professor Conti has advised over 100 students at various levels including PhD, MSc, and BSc, many of whom have gone on to successful careers in academia and industry. His research has been supported by multiple European Commission projects, university grants, and industry collaborations with companies like Cisco and Intel.
Christopher Kruegel is a Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), where he conducts research in systems security. He is affiliated with the International Secure Systems Lab (iSecLab) and was a co-founder of Lastline, Inc., which was acquired by VMware in 2020. His work focuses on creating practical security solutions that address real-world problems through system building and experimental validation. Professor Kruegel's research spans multiple areas of computer security including malware analysis, web security, network security, and vulnerability analysis. His work often involves developing systems that analyze programs for malicious behavior, scanning web applications for vulnerabilities, and improving privacy on social networks. He has made significant contributions to firmware security, smart contract analysis, and mobile security through his extensive publication record. His 15 most recent publications (2022-2023) demonstrate a strong focus on practical security solutions across diverse domains including firmware security (Shimware, Fuzzware), blockchain and smart contract security (Confusum Contractum, NFT security), mobile security (TEEzz, Columbus), and vulnerability detection techniques (Actor, Toss a Fault to Your Witcher). His research shows consistent innovation in security tools and methodologies with several papers receiving distinguished awards. Fellow of the Institute of Electrical and Electronics Engineers Outstanding Graduate Mentor Award, UCSB Academic Senate Distinguished Artifact Award for Fuzzware paper Distinguished Paper Award for Ramblr paper Best Student Paper Award for Detecting Spammers On Social Networks Professor Kruegel has advised numerous graduate students and collaborated extensively with researchers at UCSB and beyond. His work has been funded by various research grants supporting his security research initiatives. He is actively involved in the International Secure Systems Lab, which focuses on practical security solutions for real-world problems.
Associate Professor Dan Dongseong Kim is Deputy Director of UQ Cybersecurity and an Associate Professor at The University of Queensland (UQ), Australia. Previously, he held permanent academic positions at The University of Canterbury (UC), New Zealand (2011-2018) as a Senior Lecturer and Lecturer. His research focuses on Cybersecurity and Dependability for AI, IoT, Autonomous Vehicles, Cloud Computing, and Moving Target Defenses (MTD). Doctor of Philosophy in Computer Engineering from Korea Aerospace University Postdoctoral Research at Duke University (2008-2011) Visiting Scholar at University of Maryland (2007) Dan's work explores Graphical Security Models , Moving Target Defense for proactive resilience, and AI-Driven Cybersecurity with emphasis on adversarial robustness and interpretable models. His recent publications (2024-2025) span journals like IEEE Transactions on Dependable and Secure Computing and conferences such as DSN , addressing automated defense, evolving attacks, and hardware-aware security frameworks. He has advised 15 Ph.D. graduates, including researchers now at institutions like RMIT University, La Trobe University, and CSIRO's Data61. Current supervision includes projects on Automated Penetration Testing , AI-Based Intrusion Response , and Moving Target Defense . Dan's research is funded by agencies including the Republic of Korea's Agency for Defence Development and US Army Research Lab . His professional roles include Associate Editor for IEEE Communications Surveys and Tutorials and Steering Committee Chair for IEEE PRDC .
Dr. Chutima Boonthum-Denecke is a Professor in the Department of Computer Science at Hampton University's School of Science. She joined Hampton University in 2006 as an Assistant Professor and now serves as Director of the Information Assurance and Cyber Security Center (IAC@HU). She leads the NSF CyberCorps Scholarship for Service program and has contributed to NSF initiatives like ARTSI and STARS Alliances. Her educational background includes a Ph.D. in Computer Science from Old Dominion University (2007), an MS in Applied Computer Science from Illinois State University (2000), and a BS in Computer Science from Srinakharinwirot University (1997). Dr. Boonthum-Denecke's research integrates artificial intelligence, natural language processing, and cybersecurity. Key interests include: Developing intelligent tutoring systems and educational games Secure coding practices for software engineering NLP applications in information retrieval and assessment tools Cyber-physical security for IoT and robotics Her recent publications (2016-2021) focus on machine learning applications in cybersecurity, including sentiment analysis for threat detection, blockchain-enhanced IoT security, and vulnerability assessments of emerging technologies. Collaborative work with students frequently addresses privacy ethics in AI assistants, RFID implants, and cloud systems. She mentors students through the IAC@HU lab, resulting in award-winning conference presentations on cybersecurity topics. As Principal Investigator of NSF CyberCorps, she oversees scholarship programs that bridge academic research with national security needs.
Aravind Machiry is an Assistant Professor at Purdue University's Electrical and Computer Engineering Department and a founding member of the Purdue Systems and Software Security (PurS3) Lab . His research focuses on system security, particularly vulnerability detection, prevention, and secure system development using static/dynamic program analysis, fuzzing, type systems, and machine learning. Designing practical solutions for software and embedded system security Recipient of NSF CAREER and Amazon Research awards Active participant in SPLASH 2025 as OOPSLA Review Committee member His recent work includes automated vulnerability detection in embedded software, spatial memory safety enhancements, and security analysis of GitHub workflows. He has received recognition for his research through multiple distinguished paper awards and industry funding. Selected scientific awards include NSF CAREER Award (2024) Amazon Research Award (2022) Test of Time Award at FSE 2023 for DynoDroid Distinguished Paper Award at OOPSLA 2022 for 3c Qualcomm Innovation Fellowship (2025) His research team has developed frameworks like ARGUS for taint analysis of CI/CD workflows and FuzzUEr for UEFI interface fuzzing, discovering hundreds of critical vulnerabilities in open-source projects and thousands of command injection flaws in GitHub repositories.
Xin Peng is a Professor and Deputy Dean at the School of Computer Science, Fudan University, China. He leads the CodeWisdom research team focusing on intelligent software engineering techniques for development, maintenance, and operation of software systems. His educational background includes a PhD in Computer Science (2001-2006) and Bachelor's degree in Computer Science (1997-2001), both from Fudan University. He progressed through the academic ranks from Assistant Professor (2006-2010) to Associate Professor (2010-2015) and finally to Professor (2015-present). Professor Peng's research interests span Software Analytics, Intelligent Software Development, Microservice systems, and AIOps. His work leverages AI technologies including deep learning and knowledge graphs to develop intelligent software engineering techniques. A significant portion of his recent work focuses on applying Large Language Models to various software engineering tasks, including vulnerability detection, API usage analysis, and test automation. His publication record shows a clear trend toward increasingly sophisticated applications of AI in software engineering, with recent work heavily featuring LLMs for tasks ranging from vulnerability patch porting to resource leak detection. The research spans multiple domains including microservice systems, automotive software, and Web of Things security. Best Paper Award of ICSM 2011 ACM SIGSOFT Distinguished Paper Award of ASE 2018 and 2021 IEEE TCSE Distinguished Paper Award of ICSME 2018, 2019, and 2020 IEEE Transactions on Software Engineering Best Paper award for 2018 Professor Peng serves in numerous leadership roles including Deputy Director of CCF Technical Committee on Software Engineering, Co-Editor-in-Chief of Journal of Software: Evolution and Process, and Associate Editor for ACM Transactions on Software Engineering and Methodology. He has been actively involved in program committees for major software engineering conferences including ICSE, ASE, ESEC/FSE, and ICSME. He leads the CodeWisdom research team at Fudan University, which has developed several benchmark systems including TrainTicket for microservice research. The team's work bridges academic research with industrial applications, particularly in microservice systems analysis and intelligent software development tools.
Andrea Continella is an Associate Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science of the University of Twente, where he contributes to the International Secure Systems Lab (iSecLab). His research focuses on systems security, particularly embedded firmware security, Android app security, malware detection, and program analysis techniques for vulnerability discovery. Ph.D. in Computer Science and Engineering, Politecnico di Milano (cum laude) Postdoctoral Researcher, Computer Science Department, UC Santa Barbara Visiting Researcher, School of Computer Science, University of Sydney Key research contributions include: Developing automated analysis techniques for embedded firmware (KARONTE, ShieldFS) Creating privacy leak detection mechanisms for mobile applications Designing ransomware defense systems using self-healing filesystems Advancing IoT security through misconfiguration detection (S3 buckets) and protocol analysis Pioneering semi-supervised methods for network traffic fingerprinting (FlowPrint) Scientific awards: Dutch Cyber Security Best Research Paper Award 2024 Runner-up USENIX Security Distinguished Reviewer Award 2024 Professional activities: Keynote speaker on firmware security (2024) Member of IPN Cyber Security Special Interest Group Oral presentations on automated vulnerability research (2023)
Santiago Torres-Arias is an Assistant Professor at Purdue University, affiliated with the Elmore Family School of Electrical and Computer Engineering . His research spans computer systems security , software supply chain security , and applied cryptography . Campus: West Lafayette, Indianapolis Office: BHEE 324B Contact: santiagotorres@purdue.edu , +1 765-496-6610 Research Interests: Computer systems security Software supply chain security Distributed systems security Applied cryptography Password storage mechanisms Publication Trends: His recent work focuses on software supply chain security , including code signing , provenance mechanisms , and IoT vulnerabilities . Key projects address Sigstore , DevSecOps , and zero-trust dependencies . Scientific Awards: Advising & Grants: No student details provided No grant information listed
Professor Carsten Rudolph serves as Deputy Dean at Monash University's Faculty of Information Technology and directs the Oceania Cyber Security Centre (OCSC). He holds a PhD in Information Security from Queensland University of Technology (2002) and a Diplom in Computer Science from Goethe University Frankfurt (1997). His interdisciplinary research focuses on cybersecurity foundations, including cryptographic protocols, AI-driven security, human factors, and national cybersecurity policy. Key areas include securing smart grids, digital health systems, and transnational energy networks. Notable contributions include establishing the OCSC, leading Pacific region cybersecurity maturity reviews with Oxford University, and advancing frameworks for firmware security in virtual power plants. He chairs major projects like RAI4IoE (Responsible AI for Energy) and Post-Quantum Cryptography initiatives. Teaching responsibilities include cybersecurity modules like FIT3173 and FIT3168. Rudolph's research outputs (137+ publications) emphasize phishing detection via AI, blockchain-based energy trading, and resilient smart grid systems. He collaborates internationally on policy development and has advised 12 major research projects funded by agencies like the U.S. Bureau of East Asia and Pacific Affairs.
Lianying Zhao is an Associate Professor in the School of Computer Science at Carleton University and serves as a Director of the Carleton Computer Security Lab (CCSL). His research focuses on low-level platform security, including hardware, firmware, hypervisor, and operating systems, with an emphasis on trusted computing, authentication, privacy preservation, and security metrics. He leads the CCSL research group, collaborating with interdisciplinary teams to address critical security challenges in IoT, cloud systems, and web applications. Education: Not explicitly listed in provided texts. Roles: CCSL Director, Research Supervisor, and Graduate Program Advisor. Dr. Zhao’s work spans hardware security improvements, firmware vulnerability analysis, and user-centric security metrics. Recent research highlights include studies on router configuration habits, tracker detection in web browsers, and CVSS score discrepancies. He has supervised numerous graduate students in cybersecurity domains, contributing to over 30 peer-reviewed publications since 2013. His lab affiliations include CCSL and CISL, where he collaborates on projects such as secure deletion frameworks, TLS validation vulnerabilities, and hybrid decision-making models for cloud security. Current research also explores cross-regional login throttling mechanisms and AI-driven vulnerability detection in embedded systems.
