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Kang Shin is a Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. His research spans multiple domains in computer science and engineering, focusing particularly on automotive security, wireless communications, and distributed systems.
Prof. Bruno Defude is a Professor at Telecom SudParis, part of the University of Paris-Saclay. He has been affiliated with the institution since 1992, holding roles such as lecturer-researcher, department director, and currently serves as Deputy Director of Research and Doctoral Training. He leads the ACMES studies initiative and focuses on interdisciplinary research in distributed systems, cloud computing, and educational technologies. Education: Doctorate in Computer Science (1986), Grenoble INP Habilitation à Diriger des Recherches (HDR) (2005), UPMC Research Interests: Prof. Defude's work spans cloud computing architectures, data integration challenges, process mining, sensor networks, and adaptive learning systems. His contributions emphasize scalable solutions for distributed environments and privacy-aware service composition. Recent Trends: Recent publications highlight advancements in natural language querying of process data, multi-objective task scheduling in fog computing, and spatio-temporal data aggregation in vehicular networks. His work bridges theoretical foundations with practical implementations in distributed systems. Labs/Teams: Director of ACMES studies, involved in interdisciplinary research collaborations across computer science and telecommunications domains.
Stéphane MAAG is a Professor at Telecom SudParis, associated with the SAMOVAR research laboratory. His work focuses on formal methods for protocol validation, network security, and distributed systems monitoring. He has contributed to advancing testing methodologies for mobile ad-hoc networks (MANETs), IoT protocols, and wireless communication systems. His research integrates machine learning techniques for automation and has been applied to web testing frameworks and ERP systems. Key research areas include protocol performance evaluation, trust management in networks, and curriculum design for computer science ethics. His work spans both academic surveys (e.g., European ethics education studies) and technical innovations (e.g., proactive interoperability solutions for wireless routing). Publications emphasize practical applications of formal methods, with over 50 peer-reviewed articles in journals like International Journal of Ethics Education , Computer Communications , and IEEE Transactions . His work bridges theoretical foundations with real-world systems like ODOO ERP and SIP protocols.
Professor Michel MAROT is affiliated with Telecom SudParis, where he holds the position of Professor in the NeSS department. His research focuses on networking, wireless communication systems, performance evaluation, smart grids, and machine learning applications in telecommunications. MAROT has contributed to advancements in vehicular networks (VANETs/V2V), IoT architectures (LoRaWAN), and energy-efficient protocols for wireless sensor networks (WSNs). He has led studies on coalition formation in smart grids, reinforcement learning for policy optimization, and network resource management in 6G systems. Key research areas include optimizing network performance through cross-layer design, improving QoS in mobile and vehicular environments, and deploying intelligent reflecting surfaces (IRS) for 6G. His work frequently addresses challenges in mobility management, collision avoidance, and energy efficiency in distributed systems. MAROT has co-authored influential papers in journals like Neurocomputing, IEEE Transactions on Smart Grid, and IEEE Open Journal of the Communications Society. His research group (SAMOVAR/NeSS) develops practical solutions for real-world networks, including cold chain monitoring systems using sensor networks and DNS-based optimizations for SCHC protocols. MAROT’s recent work explores machine learning embedded in LPWAN sensors and mobility-aware resource allocation in LoRaWAN.
Madhav Marathe is a tenured Professor of Computer Science and the Distinguished Professor in Biocomplexity at the University of Virginia, where he also serves as Executive Director of the Biocomplexity Institute. He has held leadership roles at Virginia Tech and Los Alamos National Laboratory, and his work is deeply rooted in transdisciplinary team science. His research spans a wide range of domains including network science, artificial intelligence, computational epidemiology, high-performance computing, and complex systems. He develops foundational methods to model, analyze, and control large-scale biological, information, social, and technical (BIST) systems. His work integrates theoretical computer science with practical applications in public health, disaster response, and infrastructure resilience. The recent publications reflect a strong trend toward data-driven modeling of societal challenges—especially in pandemic response, forced migration, and energy systems. His team leverages agent-based simulations, machine learning, and high-performance computing to create scalable, policy-relevant models that support real-world decision-making. Fellow, American Association for the Advancement of Science (AAAS) Fellow, Association for Computing Machinery (ACM) Fellow, Institute of Electrical and Electronics Engineers (IEEE) Fellow, Society for Industrial and Applied Mathematics (SIAM) Distinguished Researcher Award, University of Virginia (2023) Honorary Doctoral Degree, Chalmers University (2023) Best Paper Award, SIGKDD 2021 (Applied Data Science) Endowed Distinguished Professor of Biocomplexity (2019) Dean’s Award for Excellence in Research, Virginia Tech (2018) Constellation Group’s Supernova Award (2016) Dr. Marathe has mentored over 30 doctoral students, 20+ MS students, and 15 postdoctoral fellows, and has led major federally funded projects including those related to computational epidemiology and national security. His lab, the Biocomplexity Institute, develops high-performance computing services and data analytics platforms for policymakers and emergency planners. He is also involved in initiatives such as the National Security Data and Policy Institute and the Expeditions in Global Pervasive Computational Epidemiology.
Mohammad Derawi is a Professor in the Department of Electronic Systems at the Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU), Gjøvik campus. He leads the Smart Wireless Systems (SWS) research group and serves as the scientific leader of the IoT Lab at NTNU Gjøvik. Educational Background: PhD in Information Security from NISLab (Norway) and CASED (Germany) BSc and MSc in Informatics from DTU (Denmark) His research interests span smart wireless systems, Internet of Things (IoT), information security with a focus on biometric authentication, digital electronics, applied machine learning for activity recognition, and e-learning technologies. His work integrates cybersecurity, embedded systems, and data science to develop secure and intelligent IoT solutions for real-world applications. The recent publications highlight a strong trend in mmWave-based sensing for unmanned aerial systems, RF fingerprinting for secure identification, IoT security frameworks, and machine learning applications in education and human resource analytics. His research bridges theoretical innovation with practical implementation, particularly in smart cities, healthcare, and transportation. Scientific Awards and Recognition: Invitation to the Crown Prince and Princess's 50th birthday celebration, 2023 Study Quality Award, NTNU, 2017 Norway’s Youngest Professor Award, 2016 Denmark’s youngest M.Sc. engineering award, 2009 IEEE Commendation for Young Professionals Volunteer, 2011 Multiple best paper awards from IEEE, ACM, and Springer Mohammad Derawi has been involved in several funded research and development projects, including IoT Safetraffic (RFF Inland), Ambulance Drone (NTNU Vice-Rector), Wireless ECG (Innovation Norway), biometric handgun security (RFF Innlandet), and the EU Framework 7 TURBINE project. He mentors students and collaborates with international researchers, contributing significantly to both academic and applied domains. His leadership in the SWS group and IoT Lab fosters innovation in wireless and secure embedded systems. He is actively engaged in laboratory and team-based research, particularly through the Smart Wireless Systems group and the IoT Lab, focusing on developing secure, intelligent, and scalable solutions for next-generation wireless applications.
پژوهشگر ارشد
Kenny Barlee is a Research Fellow in the Department of Electronic and Electrical Engineering at the University of Strathclyde, where he conducts research in the Software Defined Radio Laboratory. His work is centered on software-defined radio, cognitive radio, dynamic spectrum access, and rural 5G network deployment. He played a key role in the 5G RuralFirst project, contributing to the development of one of the UK’s first rural 5G networks in Orkney, Shropshire, and Somerset. PhD in Electronic and Electrical Engineering, University of Strathclyde (2020) BEng (Hons) in Electrical and Electronic Engineering, University of Strathclyde (2014) His research focuses on enabling affordable mobile connectivity in rural areas through shared and licensed spectrum, neutral hosting, and SDR technologies. He has developed cognitive radios using MATLAB and Simulink deployed on ZynqSDR devices, with applications in secondary user access to the FM radio band. His work in 5G RuralFirst involved full-stack network design, from SIM cards to core networks, including RF planning, basestation programming, and bespoke security solutions. The recent publications highlight advancements in private 5G for broadcast, low-latency wireless production, and SDR system control on RFSoC platforms. These works reflect a strong trend toward practical, deployable solutions in broadcast engineering, rural connectivity, and FPGA-based SDR prototyping. Kenny Barlee has co-authored a free 670-page SDR textbook, Software Defined Radio using MATLAB & Simulink and the RTL-SDR , and has contributed to multiple peer-reviewed journals and conferences. His industrial experience includes an internship at MathWorks and teaching SDR courses at UCLA. He leads the development of innovative systems such as the "PiFi" modem kits for drones and tour buses and a portable popup 5G network trailer for RF trials. His work supports UN Sustainable Development Goals, particularly in education and infrastructure development.
دانشیار
Gianluca Aloi serves as an Associate Professor in Telecommunications (IINF-03/A) at the Department of Computer Engineering, Modeling, Electronics and Systems (DIMES) of the University of Calabria, Italy. He holds the position of scientific director for the Telecommunications and Information Theory for Advanced Networking Laboratory (TITAN Lab.). Dr. Aloi earned his PhD in Systems Engineering and Computer Science from the University of Calabria in 2003 and became a University Researcher in Telecommunications (ING-INF/03) in 2004 before advancing to his current academic rank. His research expertise spans wireless networks, cellular networks, sensor networks, Internet of Things systems and their interoperability, management of resources and services in the Cloud/Edge and IoT (CEI) Continuum, and management and orchestration of network resources using Artificial Intelligence. His work particularly focuses on UAV-assisted IoT systems for industrial applications, geological hazard monitoring, and maritime environments. Analysis of Dr. Aloi's recent publications (2023-2025) reveals a strong emphasis on applying reinforcement learning and deep learning techniques to solve complex networking challenges. His research shows a clear trajectory toward developing intelligent network architectures that optimize data collection, improve system resilience, and enhance resource management across the edge-to-cloud continuum. Key application areas include smart factories, disaster monitoring, and urban vehicular systems. Dr. Aloi teaches courses including Fundamentals of Telecommunications Networks and Telecommunications Networks for both Electronic Engineering and Computer Engineering programs. He maintains regular reception hours every Tuesday from 9am to 11am or by appointment via email. As scientific director of TITAN Lab, Dr. Aloi leads research initiatives focused on advanced networking technologies, with particular emphasis on developing solutions for next-generation communication systems that integrate artificial intelligence with traditional networking paradigms to address real-world challenges in telecommunications and IoT applications.
دانشیار
Luis Ortiz is an Associate Professor at the University of Michigan - Dearborn in the Department of Computer and Information Science , College of Engineering and Computer Science. He previously held faculty positions at Stony Brook University (2008-2015), University of Puerto Rico, Mayaguez (2007-2008), and postdoctoral roles at MIT (2004-2006) and University of Pennsylvania (2001-2004). His research spans Artificial Intelligence , Machine Learning , Game Theory , and Graphical Models , with applications to networks, security, finance, and health. Education: Ph.D., Computer Science, Brown University (2002) B.S., Computer Science, University of Minnesota, Twin Cities His recent publications focus on graphical games, causal inference, and probabilistic modeling, with contributions to Nash equilibrium computation, strategic network analysis, and multi-agent systems. He has received multiple NSF awards , including a CAREER grant. Scientific Awards: 2019 NSF Research Award 2011 NSF CAREER Award 2008 NSF Faculty Diversity Award Ortiz has advised projects in computational game theory , machine learning , and network security . His research grants include NSF funding and industry support from Huawei/FutureWei Technologies. He has led projects on interdependent defense games, wireless localization, and causal strategic inference in networked systems. Labs & Teams: Collaborates with the Stony Brook Game Theory Summer Festival , University of Pennsylvania's Computer and Information Science Department , and industry partners in cellular networking and security.
Andrea Ridolfi is a Professor at Bern University of Applied Sciences (BFH), School of Engineering and Computer Science, and a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL). He is affiliated with the Department of Electrical Engineering and Information Technology at BFH, where he contributes to both teaching and research in communication technologies and information processing. His research interests include: Sensor Networks Internet of Things (IoT) Signal Processing for Communications Stochastic Processes Biomedical Portable Devices Mobile Sensors Andrea Ridolfi teaches undergraduate and graduate courses such as Digital Signal Processing, Communication Networks, Wireless Communication Systems, and Statistical Signal and Data Processing. His international academic engagement includes lecturing at EPFL, reflecting his strong technical and pedagogical expertise. He is fluent in English, French, Italian, Spanish, and German, with professional working proficiency in German, and has intercultural experience across Switzerland, Italy, France, the United States, Canada, and Spain. Prof. Dr. Ridolfi is actively involved in advising and curriculum development, though specific grants or student supervision details are not mentioned. He is passionate about human-centered technologies and outdoor activities such as mountaineering, climbing, skiing, paragliding, and mountain biking.
پژوهشگر ارشد
Dr. Yifei Dong is a Research Fellow at the Data Science Institute , University of Technology Sydney, with expertise in LLM-assisted agent systems , explainable AI , and multimodal artificial intelligence . Holding a PhD in Computer Science from UNSW Sydney and over a decade of fintech industry experience including CTO roles, he has secured $2.4 million in competitive funding for AI solutions bridging academia and real-world applications in healthcare, education, and finance. Education : PhD in Computer Science from UNSW Sydney Current Role : Research Fellow at UTS Data Science Institute (2023–present) Past Academic Appointments : Lecturer at Southern Cross University and Western Sydney University Dr. Dong’s research focuses on making AI systems transparent and socially beneficial , with contributions to adversarial AI, trustworthy digital societies, and wireless sensor networks. His recent work includes: Developing AICAttack (2025) for adversarial image captioning attacks Creating the QMAD fairness metric (2025) for dynamic environments Advancing explainable ECG diagnosis systems (2025) via multimodal LLMs As a scientific awardee (2025 RegTech Social Impact of the Year), he has pioneered AI solutions for vulnerable populations, such as NDSI participants through the "My Complaint Assistant" tool. His supervision of PhD and Honours students emphasizes technical rigor and ethical responsibility.
Feng Li is a Professor in the Department of Computer and Information Technology at Indiana University - Purdue University Indianapolis (IUPUI), School of Science. He received his PhD from Florida Atlantic University in 2009 and has since established himself as a leading researcher in network security, wireless networks, and privacy-preserving technologies. His research interests span across multiple domains in computer science, with a primary focus on Network Security , Wireless and Mobile Ad-hoc Networks , Federated Learning Security , Differential Privacy , and Social Network Analysis . Dr. Li's work consistently addresses critical challenges in securing distributed systems while preserving user privacy, with applications ranging from social networks to edge computing environments. His research methodology often combines theoretical frameworks with practical implementations, resulting in solutions that balance security, privacy, and system performance. Dr. Li's publication record reveals a strong trajectory in addressing evolving security challenges in distributed systems. His recent work has focused on securing federated learning systems against sophisticated attacks like backdoors, developing privacy-preserving techniques for social networks using differential privacy, and enhancing malware detection through advanced machine learning approaches. His research shows a clear evolution from traditional network security problems to more complex challenges in modern distributed AI systems. Dr. Li has successfully mentored numerous graduate students who have become active contributors in the field, including Agnideven Palanisamy Sundar, Tianchong Gao, Qin Hu, and Ryan Hosler, who frequently appear as co-authors on his publications. His research has been supported by various funding mechanisms that have enabled his team to tackle significant challenges in network security and privacy. His laboratory focuses on practical implementations of security and privacy solutions, with particular emphasis on real-world applicability of theoretical concepts. Current research directions include enhancing the security of federated learning systems, developing more robust privacy-preserving techniques for social networks, and creating advanced malware detection systems using deep learning approaches.
Guido Lombardi is a Full Professor in the Department of Electronics and Telecommunications at Polytechnic University of Turin, where he serves as a member of the Interdepartmental Center CARS@PoliTO - Center for Automotive Research and Sustainable Mobility. His academic career spans over two decades with significant contributions to computational electromagnetics and related fields. Dr. Lombardi's research focuses on computational electromagnetics, particularly analytical and numerical methods, electromagnetic propagation (scattering and diffraction), metamaterials, wave propagation, and the Wiener-Hopf technique. His work extends to practical applications including microgrid/technological modernization of eco-districts, triboelectricity in industrial applications, and security and science for peace initiatives. His research aligns with several Sustainable Development Goals, particularly those related to affordable and clean energy, industry innovation, and sustainable cities. His publication record demonstrates a strong focus on electromagnetic theory, with numerous papers in IEEE Transactions on Antennas and Propagation and other prestigious journals. The research trajectory shows consistent development in solving complex electromagnetic problems using advanced analytical and numerical techniques, particularly the Wiener-Hopf method applied to wedge diffraction problems, waveguide analysis, and metamaterial applications. Notable scientific awards and recognitions include: Raj Mittra Junior Researcher Award from IEEE Antennas and Propagation Society (2003) Executive Committee member of IEEE Antennas and Propagation Society (2016-2021) Honorary member of URSI (2018-) Honorary member of IEEE (2011-) Dr. Lombardi has served as a mentor to PhD students including Matteo Perrone (working on multiphysics acoustic-electromagnetic metasurfaces) and Sergio Cannata (focusing on biological image analysis through deep learning techniques). He has secured significant research funding through competitive calls including the PNRR Mission 4 HPC Spoke 6 project (2022-2025) and the GREEN TAGS project (2020-2024). His editorial service includes roles on IEEE Transactions on Antennas and Propagation, Electronics Letters, and IEEE Access. He has been actively involved in organizing major international conferences, serving as program chair for multiple IEEE-APS Topical Conferences on Antennas and Propagation in Wireless Communications and the International Conference on Electromagnetics in Advanced Applications (ICEAA) from 2001 to present. His research group, Electromagnetic Modeling and Applications, focuses on advanced numerical methods for electromagnetic problems.
پژوهشگر
Arjen Mentens is a Researcher at the Faculty of Engineering Sciences of Vrije Universiteit Brussel, affiliated with the MOBI - Electromobility Research Centre . His work spans lighting technology, vehicular communication, and light pollution mitigation. Key Research Areas : Lighting Technology, Visible Light Communication, Safety Engineering, Light Pollution. Recent Projects : Light it up – MERLIN BASE (2025), MAGIC WITH LIGHT – MERLIN BASE (2024). Collaborations : Regularly works with Valéry Ann Jacobs, Guillaume Dotreppe, and Peter Van Den Bossche. Research Trends : Focused on balancing safety and sustainability in lighting design, with recent emphasis on vehicular VLC channel models and ecological impacts of artificial light. Presentations : Delivered talks at the Electric Vehicle Symposium (2024) and Science Festival Brussels (2024).
مدرس ارشد
Konstantinos Banitsas is a Senior Lecturer at the Department of Electronic and Computer Engineering , Brunel University London, affiliated with the College of Engineering, Design and Physical Sciences and the Wireless Networks and Communications Centre . Holding a PhD in Telemedicine (2004), an MSc in Electronic Engineering (1997), and a BSc in Computer Science (1995), he has taught computer networking, mobile communications, and internet engineering while supervising undergraduate and postgraduate projects. His research spans telemedicine , wireless sensors , and medical imaging , with recent publications focusing on spinal cord injury treatments , myoelectric sensors for movement classification , and low-cost EMG sensor validation . Earlier work explored Microsoft Kinect applications in gait analysis, wireless medical image security , and 3G network utilization in emergency telemedicine . Dr. Banitsas supervises 4 PhD students in telemedicine and medical imaging, contributes to projects like DoctorEye (a tumor annotation platform), and participates in the IEHS research group . His work emphasizes practical implementations of wireless technologies in healthcare, including ambulance teleconsultation systems and wearable devices.
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