Olga León Abarca is a faculty member at Polytechnic University of Catalonia (UPC), affiliated with the Department of Telematic Engineering within the School of Telecommunications and Aerospace Engineering of Castelldefels (EETAC). She co-leads the Information Security Group - Mathematics Applied to Cryptography (ISG-MAK) research group, focusing on advanced cybersecurity solutions. Her research explores: IoT and medical device security architectures Wireless positioning vulnerabilities (Wi-Fi RTT) Privacy-preserving mechanisms for vehicular networks Cryptographic applications in cognitive radio systems Intrusion detection frameworks for critical infrastructure Publications (2010-2025) demonstrate consistent focus on practical security solutions, evolving from foundational cognitive radio protection to contemporary IoT/medical security challenges. Recent work emphasizes machine learning applications and domain-specific threat modeling. Awards: Mejor paper RECSI (2018) Leads multiple competitive R&D projects including CARISMATICA (2023 cybersecurity chair) and privacy-focused blockchain initiatives. Collaborates extensively within UPC's security research network and European partnerships.
Jiejun Hu-Bolz is a Lecturer in Computer Science at the Data Science Institute, Lancaster University. Her research focuses on blockchain technologies, IoT security, game theory, and decentralized systems. Research Trends: Recent work spans federated learning architectures, human-AI symbiosis via game theory, energy-efficient blockchain systems for IoT, and semantic-aware crowdsensing frameworks. Key themes include data privacy, incentive design, and network optimization. Projects: Smart and Proactive Multi-RAT Traffic Steering for V2X (2024-2027) TaaraSkillQuest Consultancy (2023-2024) Research Groups: Security Lancaster (Systems Security)
Goutham Reddy Alavalapati is an Assistant Professor in the Department of Computer Science at the University of Illinois Springfield. Previously, he held academic positions at Fontbonne University and the National Institute of Technology (India), and research roles at Sejong University (South Korea) and the KINDI Center for Computing Research (Qatar). He earned his Ph.D. from Kyungpook National University's Information Security Lab in South Korea. His research specializes in applied cryptography and cybersecurity , with a focus on lightweight authentication protocols, blockchain integration, IoT security, and quantum-resistant systems. Key domains include electric vehicles, metaverse environments, and federated learning for privacy-preserving analytics. Recent publications emphasize quantum cryptography , physically unclonable functions (PUFs) , and dynamic EV charging security , reflecting a trend toward hardware-efficient and future-proof solutions. He also teaches courses in Cryptography, Network Security, and Web Application Security. Dr. Alavalapati serves on editorial boards for journals including Security and Communication Networks (Hindawi), International Journal of Network Security , and International Journal of Computer Theory and Engineering .
Walid Saad is a Professor of Electrical and Computer Engineering and the Next-G Wireless Lead at the Virginia Tech Innovation Campus. He leads the Network sciEnce, Wireless, and Security (NEWS) laboratory, focusing on wireless networks, machine learning, quantum communications, and cybersecurity. His research spans 5G/6G systems, game theory, UAVs, and semantic communications. Education: Ph.D. (University of Oslo, 2010), M.E. (American University of Beirut, 2007), B.E. (Lebanese University, 2004). Key awards include the IEEE Fellow distinction, NSF CAREER Award (2013), and multiple best paper awards. He serves as an Area Editor for the IEEE Transactions on Communications and Editor-in-Chief of the IEEE Transactions on Machine Learning in Communications and Networking. Research interests emphasize resilient networks, quantum-enabled systems, and AI-driven communication protocols. His work addresses challenges in next-generation wireless infrastructure and networked cyber-physical systems. Advising and grants include leadership in the NSF-funded NEWS lab and collaborations with the Office of Naval Research. He has been annually recognized as a Clarivate Web of Science Highly Cited Researcher since 2019. Labs/Teams: NEWS laboratory, Virginia Tech Innovation Campus initiatives.
Sachin Jain is a Teaching Associate Professor in the Department of Computer Science within the College of Engineering at Oklahoma State University, where he has served since July 2019 (initially as Teaching Assistant Professor until June 2025, then promoted to Teaching Associate Professor). His academic career spans over two decades with previous appointments at multiple engineering institutions in Nagpur, India, including Yeshwantrao Chavan College of Engineering, Priyadarshini Institute of Engineering and Technology, and St. Vincent Pallotti College of Engineering. Education: PhD from Sant Gadge Baba Amravati University, Amrāvati, India Master of Technology from Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur, India Bachelor of Engineering from Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur, India Professor Jain's research spans multiple cutting-edge domains in computer science, with primary focus on Wireless Sensor Networks, Artificial Intelligence, Internet of Things, Blockchain Technology, Machine Learning, Pattern Recognition, and Digital Image Processing. His interdisciplinary work bridges theoretical computer science with practical applications in healthcare, energy management, agriculture, and security. His teaching portfolio includes foundational courses like C/C++ Programming and Discrete Mathematics for Computer Science, along with advanced topics such as Artificial Intelligence, Internet of Things, Computer Networks, and Digital Image Processing. His scholarly output reveals a consistent trajectory of research evolution from foundational work in Wireless Sensor Networks toward contemporary applications of AI and IoT across multiple domains. Recent publications demonstrate strong interdisciplinary connections between computer science and practical applications in healthcare diagnostics, agricultural optimization, energy management, and cybersecurity. His work shows particular strength in applying machine learning techniques to solve real-world problems across diverse fields. Professor Jain has taught numerous courses across multiple institutions throughout his career, with extensive experience in both undergraduate and graduate education. His teaching record at Oklahoma State University shows consistent course offerings in core computer science subjects as well as emerging technologies. While specific grant information isn't detailed in the available materials, his publication record suggests involvement in research projects spanning wireless networks, medical applications of AI, and blockchain technology. Though specific laboratory or research team information isn't explicitly detailed in the available materials, Professor Jain's extensive publication record across multiple domains suggests leadership in research groups focused on wireless sensor networks, AI applications, and image processing technologies. His work on blockchain-based energy management and medical applications indicates collaboration with interdisciplinary teams across engineering and healthcare domains.
Jianping Gao is a Professor in applied mathematical modeling and control systems, with significant contributions to vehicular networks, privacy protection algorithms, and nonlinear dynamical systems. His work spans interdisciplinary domains including intelligent transportation, federated learning, and biomechanical engineering. Core Research Areas : Mathematical modeling of chemotaxis and ecological systems Secure computation offloading in vehicle edge networks Federated learning optimization for Internet of Vehicles Privacy-preserving algorithms in social networked transportation Recent Trends : 2025 publications focus on dynamic gradient compression strategies and 3D radar sensing for autonomous vehicles 2024 work emphasizes blockchain-based privacy methods and Gaussian process vehicle state estimation 2023 studies include comprehensive surveys on social IoV security and contraflow control optimization The most frequent co-authors include Ling Xing (13 collaborations), Honghai Wu (12), Huahong Ma (8), and Kaikai Deng (4), indicating sustained interdisciplinary team efforts.
Sabita Maharjan is a Full Professor at the Department of Informatics, University of Oslo, Norway, and a Senior Research Scientist (adjunct) at Simula Metropolitan Centre for Digital Engineering. She holds a PhD in Networks and Distributed Systems from the University of Oslo (2013) and has been active in research and academic leadership since. Her roles include Associate Editor for IEEE Internet of Things Journal and Guest Editor for several high-impact journals. Education: Ph.D. in Networks and Distributed Systems (2013), University of Oslo; M.Sc. in Antenna and Propagation (2008), Tokyo Institute of Technology. Prior roles include Postdoctoral Fellow at Simula Research Lab (2014–2016) and Visiting Scholarships at Zhejiang University and UIUC. Research focuses on Green Networks, Energy Efficiency, Smart Grid, Vehicular Networks, and Machine Learning applications. Key interests include network security, privacy-preserving systems, and edge computing. Recent work emphasizes digital twins, federated learning, and resilience in smart grids. Publications span 5G/6G, blockchain for energy systems, and AI-driven network optimization. Notable contributions include privacy-preserving pricing schemes and secure vehicular edge computing frameworks. Awards include three Best Paper Awards (IEEE SCALCOM 2015, IEEE CS CLOUD 2016, IEEE ICCT 2019) and the 2020 IEEE TCGCC Outstanding Young Researcher Award. She is an IEEE Senior Member since 2019. Leadership roles: Vice-Chair of IEEE TCGCC SIG on Green AI (2020–present), Member of UiO’s AI/ML Study Programs Working Group. Supervises students in Energy Informatics and leads projects like CRISP (NFR-funded) and PriTEM. Research groups: Digital Infrastructure and Security (DIAS) at UiO and Simula’s Center for Resilient Networks. Active in organizing summer schools on Energy Informatics and Green Computing.
Basheer Qolomany is an Assistant Professor at Howard University's College of Medicine, Department of Medicine. He also holds academic roles at institutions including the University of Cincinnati, University of Nebraska, and Kennesaw State University. His research focuses on AI-driven solutions for computational medicine, cybersecurity, smart health systems, and data analytics. He earned his Ph.D. in Computer Science from Western Michigan University (2018) and has taught courses in AI, cybersecurity, and data science across multiple universities. Dr. Qolomany's expertise includes network science, evolutionary computation, natural language processing, and big data analytics. His work addresses challenges in precision medicine, disease diagnosis via wearable sensors, and optimizing therapeutic strategies. He has secured grants totaling over $150,000, including a co-PI role in a 2021-2023 project on peripheral artery disease detection and a PI role in a 2020-2021 study analyzing Bitcoin dynamics via Twitter data. His publications span AI optimization techniques, smart building energy management, and cybersecurity in autonomous systems. He actively contributes to interdisciplinary collaborations, including the Center for Sickle Cell Disease and the Center for Applied Data Science and Analytics at Howard University.
Pascal Urien is a Professor at Télécom Paris, specializing in computer security with a focus on secure elements. He holds a PhD in computer science from École Centrale de Lyon and an HDR. His research spans cybersecurity, blockchain systems, IoT security, and network security. He leads the Cybersecurity and Cryptography (C²) research team and is affiliated with the Information Processing and Communication Laboratory (LTCI). Awards include the 2009 National Competition for Innovative Technology Companies and multiple industry accolades for smart card innovations. He co-founded EtherTrust, a startup rooted in his research. His work emphasizes secure elements in 6G, IoT, and blockchain, with over 100 publications and 15 patents. He collaborates with IETF on TLS/DTLS security modules and has contributed to standards like EAP-TLS smartcards. His teaching includes courses on cybersecurity, network security, and blockchain technologies.
Mark Nejad is an Associate Professor at the University of Delaware, focusing on autonomous and connected vehicle systems, sustainable transportation, and interdependent infrastructure optimization. His research integrates blockchain technology, federated learning, and operations research to address challenges in smart transportation and cybersecurity. Education: M.S., Wayne State University Ph.D., Wayne State University Research Interests: Blockchain applications in transportation security and trust management Federated learning for real-time traffic prediction Autonomous vehicle integration in mixed traffic environments Optimization of cloud computing and edge infrastructure for smart cities Game theory-driven resource allocation strategies Key Article Trends (2022-2025): Recent work emphasizes blockchain-based solutions for VANET trust systems, decentralized EHR management, and adaptive federated learning frameworks. His research bridges cybersecurity, AI, and transportation engineering to create resilient infrastructure systems. Awards & Grants: No explicit awards listed. Active in securing grants for blockchain-transportation and cloud federation projects. Advising & Labs: No listed advisees. Engaged in collaborative research teams focusing on smart city technologies and decentralized systems.
Yifan Zhang is an Associate Professor in the Computer Science Department at Binghamton University (SUNY). He joined the School of Computing in 2014 after completing his Ph.D. in Computer Science at the College of William and Mary and a B.S. in Computer Science from Beihang University. Prior to academia, he worked as a system software engineer in industry. Education Bachelor of Science in Computer Science, Beihang University Doctor of Philosophy in Computer Science, College of William and Mary Research Focus Zhang's work centers on mobile computing systems, operating systems, embedded systems, and wireless networks. He explores emerging paradigms like edge/cloud computing, mobile/IoT applications, and distributed machine learning systems. His research emphasizes system design for energy efficiency, resource optimization, and security in mobile and distributed environments. Notable Achievements Recipient of Best Paper Runner-up at ACM/IEEE Symposium on Edge Computing (SEC 2024) Supervised students in projects such as Meunik, EdgeCourier, and StoArranger Academic Contributions Zhang has authored over 20 publications in top-tier conferences/journals including ACM MobiSys, IEEE INFOCOM, and IEEE Transactions on Networking. His work addresses challenges in energy-efficient systems, secure mobile communication, and distributed computing architectures.
Dr. Wenbing Zhao is a Professor of Electrical and Computer Engineering at Cleveland State University (CSU), affiliated with the College of Engineering. He holds a Ph.D. from the University of California, Santa Barbara, and has extensive experience in research and academia. His work focuses on smart healthcare systems, blockchain technology, dependable distributed systems, and IoT security. Zhao has received numerous awards, including the 2020 IEEE Access Outstanding Associate Editor Award and the 2017 CSU Golden Apple Award for teaching excellence. **Education**: Ph.D., University of California, Santa Barbara (2002) M.S. in Electrical and Computer Engineering, UC Santa Barbara (1998) M.S. in Physics, Peking University (1993) B.S. in Physics, Peking University (1990) **Research Interests**: Human motion recognition and activity tracking using sensors like Kinect Blockchain applications in healthcare, energy grids, and smart cities Dependable distributed systems and fault tolerance AI-driven healthcare solutions and patient monitoring systems IoT security and edge computing **Grants & Projects**: NSF MRI grant for smart city research (2022) DoE grant for blockchain-secured sensor systems in fossil fuel plants (2019) Ohio Department of Higher Education grant to combat opioid epidemic (2020) **Awards & Recognition**: Outstanding Associate Editor (IEEE Access, 2020) CSU Distinguished Faculty Award in Teaching (2017) Golden Apple Award (CSU, 2017) **Key Contributions**: Authored a research monograph on blockchain technology (2021) Developed the PACTS compliance-tracking system Patented motion-tracking and authentication technologies (2018–2023) Organized flagship conferences like IEEE SMC and ICVISP
Roya Firoozi is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. She holds a Ph.D. in Control Theory from UC Berkeley (2021) and a Postdoctoral Research position at Stanford University's Multi-Robot Systems Lab (2024). Her research focuses on advancing safe robot autonomy in interactive environments through generative AI, distributed optimization, and game theory. Key areas include multi-agent systems, autonomous vehicles, and perception-driven control. Education: Ph.D. in Control Theory, UC Berkeley (2021) Bachelor's in Mechanical Engineering, UC Berkeley (2014) Postdoctoral Research, Stanford University (2024) Research Interests: Robotics-aided generative AI, multi-modal perception, interactive autonomy in multi-agent systems, game-theoretic optimization, and safe navigation in dynamic environments. Her work bridges theoretical foundations with real-world experiments in robotics and autonomous systems. Awards: NSF Postdoctoral Research Fellowship ASEE Fellowship (2021-2023) Rising Stars in Aerospace Engineering (2022) Outstanding Graduate Instructor Award (2021) Advising & Grants: Currently supervising graduate students (PhD/Master's) focused on robotics and control systems. Research is supported by grants from NSF and industry collaborations. She has pioneered algorithms for distributed multi-vehicle coordination and occlusion-aware navigation systems. Labs & Teams: Leads the Autonomous Systems Lab at Waterloo, focusing on robotics, AI, and control. Collaborates with Stanford's Multi-Robot Systems Lab and UC Berkeley's MPC Lab on projects involving autonomous vehicles and fault detection systems.
Mohamed Kamel was a Professor in the Department of Electrical and Computer Engineering, co-founding director of the Centre for Pattern Analysis and Machine Intelligence (CPAMI). He contributed extensively to interdisciplinary research across machine learning, robotics, biometrics, and vehicular networks. His work integrated computational methods with ecological, medical, and engineering challenges. Research interests span machine learning applications, biometric systems, robotics, image analysis, and VANET (Vehicular Ad Hoc Network) technologies. Notable contributions include biometric identification systems, human-robot interaction frameworks, and environmental modeling using Maxent techniques. He also explored advanced battery systems and genetic diagnostics for psoriasis treatment. Publications reflect a focus on interdisciplinary topics: from underwater gesture recognition to protein sequence analysis, and from Li-ion battery cathodes to medical imaging algorithms. His work bridges theoretical advancements with practical implementations in safety systems, conservation biology, and clinical diagnostics. Awards and recognitions are not explicitly stated in available texts. His legacy includes foundational contributions to the CPAMI and mentorship through collaborative research projects.
Dr. Mehrdad Kazerani is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on power electronics, renewable energy integration, electric vehicles, energy storage systems, and microgrids. He has extensive experience in multidisciplinary projects funded by NSERC, ESTAC, and industry partners like Hydro One and GM. Dr. Kazerani has supervised numerous students and contributed to IEEE editorial roles. He advises the University of Waterloo's Alternative Fuels Team (UWAFT) and Formula Electric Vehicle team. Education: Ph.D., Electrical Engineering, McGill University, Canada (1995) Master's, Electrical Engineering, Concordia University, Canada (1990) Bachelor's, Electrical and Electronic Engineering, Shiraz University, Iran (1980) Research Interests: Power electronic converter modeling/control, hybrid energy storage systems, electrified vehicular powertrains, renewable energy integration, and AC/DC microgrid design. His work emphasizes smart grid technologies, energy access, and grid resilience. Grants & Contributions: Secured funding from NSERC, OCE, and industry partners. Active in IEEE technical committees, conference organization, and journal editing. Served on national research panels and as an external PhD examiner. Labs & Teams: Leads the Canadian Renewable Energy Laboratory and advises student teams focused on alternative fuels and electric vehicles.
