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Himanshu UpadhyayView profile

Adjunct Professor

• Artificial Intelligence
• Cybersecurity
• Quantum Machine Learning
• +2 more

Himanshu Upadhyay serves as Adjunct Professor in the College of Electrical and Computer Engineering and Principal Scientist at the Applied Research Center, Florida International University. With over 33 years of experience, he leads AI/cybersecurity research initiatives for Department of Defense and Department of Energy projects. Upadhyay's research bridges artificial intelligence, quantum computing, and cybersecurity. His current investigations focus on quantum machine learning applications for cyber threat detection and predictive environmental modeling. Recent publications demonstrate innovations in quantum-enhanced neural networks for security applications and spatiotemporal contamination analysis. Thematic analysis reveals Upadhyay's consistent focus on developing advanced computational solutions for security and environmental challenges. His research integrates quantum computing breakthroughs with practical cybersecurity and environmental monitoring applications.

Marzieh AhmadzadehView profile

Associate Professor

• Computer Science Education
• Human-Computer Interaction
• Applied Data Mining
• +3 more

Dr. Marzieh Ahmadzadeh is an Associate Professor (Teaching Stream) at the Department of Electrical Engineering & Computer Science, York University. She holds a Ph.D. and MSc in Information Technology (Software Engineering) from the University of Nottingham, UK, and a BSc in Computer Engineering from Isfahan University. A certified Professional Engineer (P.Eng.) in Ontario, she has held academic positions at Shiraz University of Technology, University of Toronto, and University of Georgia, USA before shifting her focus to education research in 2015. Education: Ph.D., Information Technology (Software Engineering), University of Nottingham (2006) MSc, Information Technology (Software Engineering), University of Nottingham (2002) BSc, Computer Engineering, Isfahan University Her research intersects Computer Science Education and Human-Computer Interaction , with a focus on Applied Data Mining for educational analytics and security applications. She has published in prestigious venues like ACM SIGCSE, IEEE Transactions, and Future Generation Computer Systems. Recent publications demonstrate expertise in: Exam design and cognitive load optimization Ransomware detection in fog computing environments Breast cancer survivability modeling with imbalanced data Gender preferences in e-commerce UX design Academic integrity analysis in programming education

Marina MongielloView profile

Associate Professor

• Blockchain Technology
• IoT Systems
• Software Engineering
• +3 more

Marina Mongiello is Associate Professor at Polytechnic University of Bari focusing on blockchain applications, IoT security, and distributed software systems. Her work integrates formal methods with practical solutions for cybersecurity challenges. Research Focus: Develops secure blockchain architectures for supply chain traceability, IoT security frameworks, and intrusion detection systems combining formal modeling with machine learning approaches. Technical Innovations: Designs hybrid systems using Petri nets and LSTM networks for enterprise security, and biometric-based cryptographic solutions for blockchain platforms. Application Domains: Implements traceability solutions for agri-food supply chains, secure data transmission frameworks, and decentralized alternatives to cloud computing infrastructures.

Md Tauhidur RahmanView profile

Assistant Professor

• Hardware Security
• Embedded Security
• Side-channel Analysis
• +4 more

Dr. Md Tauhidur Rahman is an Assistant Professor in the Department of Electrical and Computer Engineering at Florida International University (FIU), part of the College of Engineering and Computing. He earned a Ph.D. in Computer Engineering from the University of Florida (2017), an M.Sc. from the University of Connecticut (2015), and a B.Sc. in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (2009). His research focuses on hardware security, embedded security, side-channel analysis, memory systems, and reliability, with funding from NSF, NSA, and CyberFlorida. Research Interests: Hardware Security and Trust Embedded Security Side-channel Analysis Memory System Reliability Machine Learning Applications in Security Grants and Awards: $750K NSA Grant (2022) for UAS Security $1.4M CyberFlorida Grant (2022) for Hardware-Security Training NSF SaTC Grant (2021) NSF CRII Grant (2019) UAH New Faculty Research Award (2019) Labs and Leadership: Director of the SeRLoP Lab (Security, Reliability, Low-power, and Privacy), leading collaborative projects on hardware security and critical infrastructure protection.

• Game Theory
• Machine Learning
• Wireless Security
• +3 more

Cristina Comaniciu is an Associate Professor in Electrical and Computer Engineering at Stevens Institute of Technology. Her research applies game theory and machine learning to wireless security, physical layer secrecy, and network slicing. Education includes PhD from Rutgers University. Develops energy-security tradeoffs and adversarial learning techniques with applications in 5G/6G networks and IoT systems. Awarded IEEE Marconi Best Paper Prize and Rutgers Distinguished Young Alumna Medal. Patents cover cooperative diversity in sensor networks and secure communication frameworks.

Sajjad DadkhahView profile

Assistant Professor

• Cyber Security
• IoT Security
• Machine Learning in Security
• +4 more

Sajjad Dadkhah is an Assistant Professor at the University of New Brunswick (UNB), holding the Canada Mastercard IoT Research Chair and leading the Cybersecurity Team at the Canadian Institute of Cybersecurity (CIC) within the Faculty of Computer Science. He specializes in cybersecurity, IoT security, and machine learning applications in security. His work focuses on developing robust security frameworks, intrusion detection systems, and datasets for emerging technologies like IoT and IoV. He has earned Bronze and Gold medals in international invention competitions and holds a fellowship from Kyushu Institute of Technology. Dadkhah serves as a Board Member and Managing Editor for the Applied Soft Computing (ASOC) Elsevier journal since 2016. His research includes pioneering datasets such as CICIoMT2024 and TruthSeeker, addressing critical challenges in medical IoT security, fake news detection, and vehicular network protection. His academic contributions span over 40 publications, emphasizing practical solutions for real-world cybersecurity threats. He actively collaborates with organizations like Kyushu University and IRIS Smart Technology Complex, bridging academic research with industrial applications.

Rafiqul IslamView profile

Associate Professor

• Cybersecurity
• Malware Analysis and Classification
• Authentication Systems
• +5 more

Dr. Rafiqul Islam is an Associate Professor in the Department of Computing at Charles Sturt University's School of Computing, Mathematics & Engineering, within the Faculty of Business, Justice and Behavioural Sciences. He specializes in Cybersecurity with a focus on malware analysis, authentication systems, cloud security, IoT security, and privacy in digital environments. He leads the Cybersecurity Research Group and has been recognized nationally/internationally with awards like the 2021 Cyber Security Researcher of the Year Award from AISA. His research has attracted over $7M in external grants, including a $68M Cybersecurity CRC project. Education: PhD (Network Security), MSc (Research), BSc (Hons), PGDip (Learning & Teaching) Leadership: Director of the Cybersecurity Research Team at CSU Publications: Over 200 peer-reviewed articles, emphasizing AI-driven cybersecurity solutions for IoT, cloud, and industrial systems Research interests span adversarial machine learning, ransomware detection, secure agri-food supply chains, and medical data privacy. His work bridges theoretical advancements with real-world applications, such as resilient IoT configurations and threat intelligence frameworks for smart agriculture. Recent articles focus on AI-enhanced cybersecurity for IoT, malware classification systems, and blockchain-based healthcare data protection. He actively collaborates on projects addressing cybersecurity challenges in distributed networks and emerging technologies. Awards: Professional Excellence, Research Excellence, Leadership Award (CSU), Cyber Security CRC contributions Grants: $7M+ secured as Co-PI in collaborative projects His lab focuses on interdisciplinary research, integrating AI, data science, and cybersecurity to address modern digital challenges.

Kurt RohloffView profile

Associate Professor

• Cybersecurity
• Homomorphic Encryption
• Lattice-Based Cryptography
• +5 more

Prof. Kurt Rohloff is an Associate Professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT). He serves as the founding director of the NJIT Cybersecurity Research Center, focusing on advanced cryptographic techniques such as homomorphic encryption, lattice-based cryptography, and secure computing. With a background in electrical engineering from the University of Michigan (Ph.D., 2004) and Georgia Tech (B.E., 1999), his career includes prior roles as a DARPA Program Investigator in industry before joining academia. His research emphasizes practical implementations of privacy-preserving technologies, including open-source libraries like PALISADE and OpenFHE , which enable secure computation on encrypted data. Key areas of contribution include FPGA-accelerated homomorphic encryption, proxy re-encryption systems, and applications in healthcare, telecommunications, and distributed computing. He has led workshops such as WAHC (Workshop on Encrypted Computing and Applied Homomorphic Cryptography), fostering interdisciplinary collaboration. Rohloff’s work bridges theoretical cryptography with real-world challenges, addressing scalability, performance optimization, and usability of secure computing frameworks. His innovations target use cases like encrypted genome analysis, privacy-preserving AI, and secure data sharing across distributed networks.

Arunita JaekelView profile

Professor

• Vehicular Ad Hoc Networks
• Secure V2V Communications
• Wireless Sensor Networks
• +3 more

Arunita Jaekel is a Professor in the School of Computer Science at the University of Windsor. She directs the Vehicular Communication Laboratory and maintains professional affiliations with IEEE. Her research focuses on vehicular ad hoc networks (VANETs), secure V2V communications, wireless sensor networks, and mobile network optimization. Key themes include developing machine learning approaches for intrusion detection, congestion control algorithms using reinforcement learning, and privacy-preserving strategies for connected vehicles. Recent publications emphasize deep learning-based anomaly detection, position forgery countermeasures, and adaptive transmission protocols for safety-critical vehicular systems. Her work shows consistent application of AI techniques to enhance security and efficiency in intelligent transportation networks.

Yang XiaoView profile

Assistant Professor

• Distributed System Security
• Blockchain and Decentralized Systems
• Trusted and Privacy-preserving Computing
• +2 more

Yang Xiao is an Assistant Professor in the Department of Computer Science at the University of Kentucky, part of the Stanley and Karen Pigman College of Engineering, where he has been serving since 2022. His research focuses on security and privacy in distributed and cyber-physical systems, with a particular emphasis on practical applications in blockchain, IoT, and mobile networks. Dr. Xiao holds the following academic degrees: Ph.D. in Computer Engineering, Virginia Polytechnic Institute and State University, 2017–2022 M.S. in Electrical Engineering-Systems, University of Michigan, 2015–2017 B.S.E. in Information Engineering, Shanghai Jiao Tong University, 2010–2014 His research interests are centered around securing modern computing infrastructures. Key areas include: Distributed System Security Blockchain and Decentralized Systems Trusted and Privacy-preserving Computing Mobile Communications and Network Security Cyber-Physical Security Dr. Xiao's work addresses critical challenges in ensuring trust and privacy in emerging technologies, particularly in the context of decentralized applications and resource-constrained devices. Analysis of his recent publications (2022-2025) reveals a consistent focus on blockchain security, privacy-enhancing technologies, and machine learning security. He has made significant contributions to decentralized data markets, verifiable credentials for authentication, and robust defenses against backdoor attacks in federated learning. Additionally, his research extends to spectrum sharing, automotive network security, and real-time system integrity. Scientific Awards: No scientific awards were mentioned in the provided information. Regarding advising and grants, the available information does not specify any current advisees or funded research projects.

• Software Engineering Education
• Computational Technology in Education
• Machine Learning Applications
• +5 more

Saheed Popoola, PhD, is an Assistant Professor at the University of Cincinnati's CECH - School of Information Technology. His research spans software engineering education, computational technology in K-12 classrooms, and model-driven engineering. He actively explores strategies to enhance collaborative learning environments through student-driven software projects and investigates challenges in open-source development and cybersecurity incident analysis. His work bridges empirical software engineering practices with educational technology, focusing on topics such as static analysis tool efficacy, user sentiment analysis in software communities, and ensemble learning techniques for network security. He has contributed to tools like Loupe for model analysis and has examined LabVIEW/Simulink model evolution patterns. Recent studies include the impact of computational thinking in K-12 education, early heart disease detection via machine learning, and strategies for managing diverse classroom environments. His research emphasizes practical applications in both academic and industrial software development contexts. Notably absent from the provided data are specific details about grants, awards, or direct student advising. However, his involvement in initiatives like the student software solutions center highlights a focus on experiential learning and community-driven development practices.

• Cloud/Edge Computing
• 6G Networks
• Artificial Intelligence
• +3 more

Dr. Ali Khoshkholghi is a Lecturer in Computing Science at Middlesex University's Faculty of Science and Technology, Department of Computer Science. He leads modules on Operating Systems, Computer Networks, and Network Security while conducting research at the intersection of cloud/edge computing, 6G networks, and AI-driven network optimization. His research develops intelligent frameworks for next-generation networks, focusing on performance optimization of service function chains in NFV-enabled environments, federated learning for multi-operator systems, and security protocols for IoT ecosystems. Recent projects include blockchain-IoT integration for smart environments, UAV network optimization, and threat detection systems for intelligent transportation. Dr. Khoshkholghi's publications demonstrate consistent innovation in network architectures, with work on in-band telemetry optimization (IntOpt), edge intelligence deployment, and federated learning models for telecommunications. His security research addresses vulnerabilities in messaging protocols, malware detection in smart homes, and cryptographic evaluation using formal methods.

Tuan VuongView profile

Senior Lecturer

• Cyber-Physical System Security
• Software Development
• Intrusion Detection
• +2 more

Dr. Tuan Vuong is a Senior Lecturer in Computer Science (Cyber-physical Security) at the University of Greenwich's School of Computing and Mathematical Sciences, within the Faculty of Engineering and Science. He holds a PhD in Cyber-Physical System Security with over 10 years of international experience in both academic and industrial settings. Research Focus: His research explores cyber-physical security frameworks, intrusion detection systems, and secure computation offloading for autonomous systems. His work bridges theoretical computer science with practical applications in vehicular networks and IoT security. Publication Trends: Vuong's recent publications focus on machine learning approaches for intrusion detection in robotic and vehicular systems, with consistent contributions to cybersecurity and edge computing literature.

Jian TangView profile

Professor

• Database Systems
• Distributed Computing
• Data Mining
• +3 more

Dr. Jian Tang is a Professor in the Department of Computer Science at Memorial University of Newfoundland. He holds a M.Sc. from the University of Iowa and a Ph.D. from Penn State University. His primary affiliation is within the Faculty of Science. His research focuses on database systems, distributed computing, data mining, and IoT security. Key projects include fault tolerance in distributed systems, workflow management, intrusion detection in IoT networks, and machine learning applications in healthcare and genomics. He has published extensively on topics like autonomous IoT security systems, feature selection methods for microarray data, and probabilistic resource scheduling in grid environments. Dr. Tang’s work bridges theoretical foundations with practical implementations, particularly in cybersecurity, bioinformatics workflows, and scalable distributed systems. His recent publications emphasize real-time autonomous IoT security solutions and machine learning-driven predictive models for healthcare outcomes.

• Automatic Control
• Robotics
• Critical Infrastructure Protection
• +4 more

Professor Stefano Panzieri is a Full Professor in the Department of Civil, Computer and Aeronautical Engineering at Roma Tre University. He has held academic positions since 1996, including Associate Professor (2003–present) and Assistant Professor (1996–2003). His research focuses on automatic control, robotics, critical infrastructure protection, and cyber-physical systems. He coordinates the Ph.D. program in Computer Science and Automation and leads initiatives like the CISIApro model for infrastructure resilience. Panzieri directs the Robotics Laboratory, MCIPlab, and Automation Lab, contributing to 10 Ph.D. students' supervision. His work spans distributed control, sensor networks, and smart grid technologies, with over 180 publications and projects funded by the EU and Italian Ministry of Economic Development. Key contributions include interlaced Kalman filters and anomaly detection frameworks. Research Interests: Automatic Control: Nonlinear techniques, iterative learning control, and MPC. Robotics: Mobile robotics, sensor fusion, and navigation. Critical Infrastructure: Protection strategies, cascading effects modeling, and decision support systems. Cybersecurity: False data injection defense, game-theoretic models, and resilient networks. Recent Articles Trends: Focus on distributed state estimation, cyber-physical system resilience, and adaptive filtering techniques. Recent work addresses adversarial attacks, multirate systems, and pandemic impact modeling. Grants & Projects: SMART Environments (2015): Smart city and infrastructure development. ATENA (2017): Secure IACS using Software-Defined Networking. URANIUM (2014): Resource allocation and game theory for critical infrastructure. Labs & Teams: Leads MCIPlab (Critical Infrastructure Protection) and the Automation Lab, collaborating on robotics and smart grid technologies.