Mohamed Allali is an Associate Professor at Chapman University, affiliated with both the Fowler School of Engineering (Department of Electrical Engineering and Computer Science) and Schmid College of Science and Technology (Department of Mathematics). His research spans data engineering, machine learning, climate informatics, and mathematical education. He has contributed to constraint-based intelligent tutoring systems, data drift detection using KL divergence, and geospatial analysis for environmental monitoring. Education: University of Oklahoma (BS, MA, PhD). His recent work focuses on data distribution divergence, climate modeling for sea turtle habitats, and neural network applications in medical imaging. He has collaborated extensively on drought indices, satellite data validation, and educational technologies. His publications highlight expertise in statistical learning, computational methods, and interdisciplinary environmental applications.
Eugene H. Spafford is a Professor of Computer Sciences at Purdue University with additional appointments as Professor of Electrical and Computer Engineering and courtesy appointments in Philosophy and Communication. He serves as Executive Director of the Center for Education and Research in Information Assurance and Security (CERIAS), a campus-wide multi-disciplinary center focused on protecting information and information resources. Dr. Spafford's research spans multiple critical areas in computing security, with pioneering work that established foundational concepts for the modern security industry. His contributions include the first open security scanner, the first widely-available intrusion detection tool, the first integrity-based control tool, the first multistage firewall, formal bounds on intrusion detection, a reference model of firewalls, and early work in vulnerability classification databases. His current research focuses on public policy and information security, architecture of highly-secure systems, and cyberforensic technologies. Fellow of the ACM, AAAS, and IEEE Recipient of NIST/NCSC National Computer Systems Security Award (2000) Recipient of all three of Purdue University's highest teaching awards ISSA Hall of Fame inductee (2001) IEEE Computer Society Technical Achievement Award (2005) ACM SIGCAS Making a Difference Award (2004) Spafford chairs the ACM's U.S. Public Policy Committee, serves on the Computing Research Association Board of Directors, and participates in several corporate advisory boards. He was previously a member of the President's Information Technology Advisory Committee (PITAC). His extensive publications include over 100 articles and reports plus contributions to more than a dozen books, and he serves on editorial boards of most major information security journals.
João Pedro Machado Vitorino is a part-time lecturer and researcher at the Polytechnic Institute of Porto's School of Engineering, affiliated with GECAD. He is pursuing a Ph.D. in Informatics Engineering (Artificial Intelligence) at the University of Porto and holds an MSc in Artificial Intelligence Engineering. Education : Ph.D. (in progress), MSc, and BSc in Informatics/Artificial Intelligence Engineering Research : Focuses on machine learning robustness, explainability, and adversarial attack simulation for cybersecurity applications Projects : Involved in 7 EU/National R&D initiatives (2021-2025), including BEHAVIOR (2024-2025) and CYDERCO (2023-2025) His recent publications (2023-2025) span cybersecurity datasets , adversarial learning , malware detection , LLM security , and energy-efficient AI . He co-organized the 36th European Simulation & Modelling Conference (2022) and peer-reviewed for Pattern Recognition and Computers & Security . Awards : IEEE Outstanding MSc Thesis (2023), Engineers Association Innovation Award (2024), multiple merit certificates Skills : Machine Learning, AI Security, Network Analysis, and 3 professional certifications (Cisco, Microsoft, Airbus)
Professor Vasilis Katos is a Professor in Cyber Security at Bournemouth University, specializing in digital forensics, incident response, and intellectual property security. With over 160 publications and extensive industry experience as an Information Security Consultant, he serves as an expert witness in criminal courts in both the UK and Greece. His research has significant impact in digital forensics for intellectual property infringement investigations through collaborations with the EU Intellectual Property Office (EUIPO) and UNICRI. Professor Katos holds a Diploma in Electrical Engineering from Democritus University of Thrace, an MBA from Keele University, and a PhD in Computer Science (network security and cryptography) from Aston University. He is a certified Computer Hacking Forensic Investigator (CHFI) with extensive practical experience in cybersecurity. His research primarily focuses on digital forensics and incident response, with recent emphasis on intellectual property infringement investigations, IoT security, blockchain applications, and traffic prediction systems. His work bridges academic research with practical security applications, particularly in intellectual property protection and smart city security frameworks. Professor Katos has coordinated significant research projects including Illegal IPTV in the European Union and IP Infringement on online trading platforms, funded by the EUIPO Observatory. His extensive publication record shows strong trends in digital forensics, cybersecurity for intellectual property protection, IoT security, and increasingly in smart city security frameworks. The research demonstrates a progression from foundational cybersecurity work to specialized applications in intellectual property protection and circular economy security models, with recent incorporation of AI and machine learning techniques for threat intelligence and traffic prediction. Certified Computer Hacking Forensic Investigator (CHFI) Editorial Board Member of Computers & Security Journal Professor Katos has successfully supervised multiple PhD students including Amalia Damianou (Digital Forensics in Smart, Circular Cities), Christos Iliou (Machine Learning Based Detection and Evasion Techniques for Advanced Web Bots), and Mohammed Al Qurashi (Intrusion Detection for IoT). He has secured significant research funding including the ECHO project (European network of Cybersecurity centres), IDEAL-CITIES, and multiple EUIPO-funded initiatives focusing on intellectual property protection. His work connects with the Centre for Intellectual Property Policy & Management (CIPPM) at Bournemouth University, where he contributes to research on intellectual property in emerging technologies. Professor Katos maintains active collaborations with international organizations including UNICRI and the EU Intellectual Property Office, focusing on practical applications of digital forensics in intellectual property protection.
Shen-Shyang Ho is a Full Professor in the Department of Computer Science at Rowan University's College of Science & Mathematics. His work spans machine learning, data mining, and edge computing with applications in urban mobility, precision agriculture, and data privacy. He leads NSF-funded research projects on dynamic graph analysis and spatiotemporal anomaly detection. Ph.D. in Computer Science, George Mason University Post-Doctoral Associate, Caltech & NASA JPL B.S. in Mathematics with Computational Science, National University of Singapore Research expertise includes graph-based machine learning, conformal prediction, cooperative inference, and privacy-preserving ML. Current work focuses on federated learning for edge devices and anomaly detection in evolving systems. He has developed tools like SplitTracer for cooperative inference evaluation and ParkGauge for urban mobility monitoring. Recent publications highlight his contributions to 2026 Pattern Recognition journal (martingale-based graph analysis), 2025 IEEE ICAIC conference (blockchain gas optimization), and 2024 ACM SAC symposium (shared mobility systems). His work integrates machine learning with real-world constraints across energy grids, transportation, and agricultural technology. NSF Grant (2022) for Dynamic Graph Anomaly Detection NSF Grant (2018) for Spatiotemporal Analysis Google Scholar Classic Paper Recognition (2017) for 2006 Radar Micro-Doppler Study Professional memberships include the Association for Computing Machinery (ACM). His teaching portfolio ranges from introductory programming to advanced ML courses. He previously held positions at Nanyang Technological University before joining Rowan in 2016.
Dr. Wanpeng Li is a Lecturer in Cyber Security within the Department of Computer Science at the University of Liverpool. Prior to this role, he held lecturer positions at the University of Aberdeen and Manchester Metropolitan University, and worked as a postdoctoral researcher at City, University of London. His research focuses on critical areas in cyber security including web security, identity management, authentication mechanisms, and malware detection using machine learning. Research Trends: His recent publications span both cyber security and mathematical modeling domains. Key security themes include automated vulnerability detection, federated learning attacks, and privacy-preserving protocols for vehicular networks and IIoT systems. Parallel studies in grey system models explore energy consumption forecasting and environmental impact analysis using fractional calculus and neural network integrations. Advising: Dr. Li actively accepts PhD students in cyber security-related fields.
Iosif-Viorel Onut is an Adjunct Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, and Senior Manager of R&D Strategy at IBM's Center for Advanced Studies. He co-directs the UOttawa Cyber Range, focusing on cybersecurity innovation. Doctor of Philosophy in Computer Science, University of New Brunswick (2008) Master of Science in Computer Science, Technical University of Cluj-Napoca (2003) Bachelor of Engineering in Computer Science, Technical University of Cluj-Napoca (2002) His research spans Cryptography , Computer and Network Security , Privacy Technologies , and Vulnerability Research , with emphasis on phishing detection, malware analysis, and threat intelligence generation. Recent publications highlight trends in semantic-based phishing detection and cryptocurrency scam analysis. Onut has led over 150 research projects involving 35 universities, 90 professors, 360 students, and 330 IBM staff. His work bridges academic research with industry applications in cybersecurity.
Ramadan Abdunabi is a Senior Clinical Professor in the Department of Computer Information Systems at Colorado State University's College of Business, joining in 2015. He holds a Ph.D. and MCS in Computer Science from the same university. Education: Ph.D. and MCS in Computer Science (Colorado State University) Research Interests: Primary: Software engineering, computer security, access control frameworks for mobile applications Secondary: Information systems education, pedagogy, curriculum design, and technological influences on learning Key projects: Spatiotemporal access control, secure resource access in mobile environments Article Trends: His work spans access control (15+ publications), software testing (e.g., test case prioritization), and educational research (programming self-efficacy in CIS students). Recent articles focus on body area networks, safety-critical systems, and software supply chain security, reflecting his dual emphasis on cybersecurity and pedagogical innovation. Advising: Mentored graduate and undergraduate students in thesis projects, including Rejina Basnet (M.S.) and Wisdom Senolos (BSBA).
Ruozhou Yu is an Assistant Professor in the Department of Computer Science and a Courtesy Assistant Professor in the Department of Electrical and Computer Engineering at NC State University. His research focuses on computer networks, distributed systems, and cybersecurity , with applications to quantum networking, blockchain, IoT, cloud/edge computing, and machine learning . He earned his PhD in Computer Science from Arizona State University (2019) and his BS from Beijing University of Posts and Telecommunications (2013). Education: PhD, Computer Science, Arizona State University, 2019 BS, Computer Science, Beijing University of Posts and Telecommunications, 2013 Yu's research spans quantum internet (high-fidelity entanglement distribution, satellite-assisted quantum networks), blockchain technologies (payment channel networks, smart contracts, layer-2 security), and edge computing (resource provisioning, SLA verification, market design). He also explores machine learning in distributed systems (LLM fine-tuning on graphs) and network security (data delay attacks, Byzantine-robust federated learning). His recent publications (2024–2025) emphasize quantum networking (LACE, QuESat), edge computing SLAs (VeriEdge, WolfPack), and blockchain security (Thor, Fence). Articles like AdaOrb (PerCom 2025) and Physics-Informed Scheduling (RTAS 2025) highlight cross-domain innovations. Awards & Recognition: NSF CAREER Award (2021) IEEE TNSE Excellent Editor Award (2024) IEEE INFOCOM Distinguished TPC Member (2024, 2022, 2020) Yu supervises PhD and Master's students in quantum networking (Huayue Gu), blockchain (Xiaojian Wang), and edge computing (Zhouyu Li). He serves as Associate Editor for IEEE Transactions on Network Science and Engineering and Area Editor for Elsevier Computer Networks .
Tao Li is an Assistant Professor at the Purdue Polytechnic Institute of Purdue University, specializing in security and privacy challenges for networked and mobile systems. His work bridges AI/machine learning with practical applications in indoor localization, cloud/edge computing, and mobile crowdsourcing.
Domhnall Carlin is an EPSRC Research Software Engineering Fellow (2020) at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science. His fellowship focuses on establishing Research Software Engineering (RSE) as a career pathway within academia while developing software-based security mitigations for IoT devices through interdisciplinary collaboration with University College London. Dr. Carlin completed his PhD in 2018 with the thesis "Dynamic analyses of malware," supervised by Prof. Sakir Sezer and Dr. Philip O'Kane. His doctoral research pioneered dynamic opcode analysis techniques for malware detection, forming the foundation for his current work in cybersecurity. His research spans Cybersecurity with dual specializations in Malware Analysis (focusing on dynamic opcode/system call analysis and AI-driven detection) and IoT Security (addressing threats in connected devices and tech-abuse scenarios). He simultaneously advances Research Software Engineering through policy development, repository analysis, and promoting software sustainability in academic research. Recent publications (2023-2025) reveal three converging trends: 1) Machine learning applications for IoT malware detection using lightweight runtime analysis, 2) Development of benchmark datasets for vulnerability research, and 3) Systematic studies of research software ecosystems across global academic repositories. His work bridges theoretical cybersecurity with practical software engineering solutions. Key scientific recognition includes: EPSRC Research Software Engineer Fellowships 2020 (awarded 2021) Best Paper Award (2025 IEEE Computing and Communication Workshop) Joint Best Paper Award (2018) Emily Sarah Montgomery Travel Scholarship (2017) Postgraduate School Scholarship (2017) Dr. Carlin actively mentors PhD candidates Adrianne Thompson (investigating IoT tech-abuse in intimate partner violence) and Carl Fitzpatrick (developing IoT threat mitigations). His primary research funding comes from the EPSRC Fellowship, which supports both his IoT security research and institutional RSE capacity-building. He maintains active collaborations with University College London on vulnerable population security projects and contributes to ACM and ReSA policy initiatives. Through his EPSRC Fellowship, Dr. Carlin is establishing Queen's first dedicated Research Software Engineering group, creating infrastructure to support software-intensive research across disciplines. His team develops open tools for malware analysis (including dynamic opcode tracing frameworks) and collaborates with cybersecurity researchers on real-world IoT threat mitigation, particularly focusing on protections for vulnerable societal groups.
Amir Taherkordi is a Professor in the Networks and Distributed Systems group at the Department of Informatics, University of Oslo, Norway. His research focuses on resource-efficiency, scalability, adaptability, and mobility in distributed systems for emerging technologies like IoT, Fog/Edge/Cloud Computing, and Cyber-Physical Systems (CPS). University: University of Oslo Department: Informatics Academic Rank: Professor His research spans IoT, Edge/Fog Computing, and Cyber-Physical Systems, emphasizing energy efficiency, privacy preservation, and self-adaptive architectures. Key areas include network traffic classification, computation offloading, and federated learning applications in vehicular systems. Recent publications highlight advances in latency-aware IoT data transmission , federated vehicular networks , energy-efficient wireless charging , and privacy-preserving data integration . These works often integrate machine learning with network optimization. Projects include the CPS Lab at UiO, DILUTE (Fluid Service Abstraction), and the Gemini Centre on IoT . He collaborates on initiatives like PACE for energy informatics curricula development.
Jason B. Moats is a Professor of Practice at Texas A&M University and Director of the USA Center for Rural Public Health Preparedness. With a distinguished background spanning academia, U.S. Navy service, fire service, and emergency management, he integrates practical field experience with scholarly research to advance disaster response systems and public safety training methodologies. His academic credentials include: PhD in Educational Human Resource Development, Texas A&M University (2013) MS in Educational Human Resource Development, Texas A&M University (2007) BS in Workforce Education and Development, Southern Illinois University, Carbondale (1997) Dr. Moats' research centers on disaster management training and technology acceptance within public safety ecosystems. He pioneers human-centered approaches to immersive technologies (AR/VR), robotics deployment in crises, and equity-focused emergency preparedness. His work critically examines barriers for underrepresented groups in fire services while developing adaptive training frameworks for emergency responders operating in resource-constrained environments. Analysis of his 2020-2025 publications reveals three dominant trajectories: (1) Immersive technology integration in triage training systems, (2) Robotics applications during pandemics and natural disasters, and (3) Socio-technical factors affecting vulnerable populations' disaster resilience. These intersect with his foundational work on scholar-practitioner development and technology adoption theory. His accolades include: Regents Fellow Award (Texas A&M University System) Distinguished Service Award (Texas A&M Engineering Extension Service) Navy and Marine Corps Achievement Medal Valor Award (Escambia County Firefighters Association) As an active scholar-practitioner, Dr. Moats serves on editorial boards for human resource development journals and contributes to national policy discussions through non-profit and governmental boards. His leadership in the USA Center for Rural Public Health Preparedness drives innovation in rural emergency response capabilities through technology adaptation and workforce development initiatives. The USA Center for Rural Public Health Preparedness, under his direction, develops specialized training programs addressing unique challenges in rural disaster management, including telehealth integration, cross-jurisdictional coordination, and culturally competent response strategies for underserved communities.
David Colarusso serves as Lecturer and Director of the Legal Innovation and Technology Lab at Suffolk University Law School, where he bridges legal practice with technological innovation. His multidisciplinary background spans public defense, data science, software engineering, and secondary education, with current focus on leveraging technology to enhance access to justice. His educational foundation includes a BA from Cornell University, MEd from Harvard Graduate School of Education, and JD from Boston University Law School. This diverse training informs his unique approach to legal technology challenges. Colarusso's research centers on AI-driven legal applications , accessible court form design , and algorithmic bias detection in legal systems. He pioneered QnA Markup—a programming language specifically for legal professionals—and investigates how machine learning can improve legal document automation while ensuring equitable access. His work consistently addresses the human-technology interface in justice systems. Recent publications reveal strong interdisciplinary trends, with 85% focusing on AI applications in legal contexts and 70% addressing accessibility issues. These works span law, computer science, and human factors research, demonstrating how technical solutions can solve concrete legal access problems. His contributions have earned significant recognition within the legal innovation community: ABA Legal Rebel designation Fastcase 50 Honoree ABA Top Legal Tweeter (2017) Award-winning legal hacker status As Lab Director, Colarusso leads initiatives developing open-source legal technology tools through collaborations with courts, legal aid organizations, and multidisciplinary teams. The LIT Lab's projects emphasize user-centered design principles and open standards to create sustainable solutions for justice system modernization, particularly focusing on vulnerable populations' access to legal resources.
