Dr. Jagruti Sahoo is an Associate Professor in Computer Science and Academic Program Coordinator for the Cybersecurity Program at South Carolina State University (SCSU), USA. Her research focuses on Internet of Things (IoT) , cybersecurity , machine learning , vehicular networks , and network functions virtualization . Ph.D. in Computer Science and Information Engineering from National Central University, Taiwan (2013) Postdoctoral research at University of Sherbrooke and Concordia University, Canada (2013-2016) Her research lab explores optimization, security, and privacy in IoT and cyber-physical systems, particularly in smart transportation and smart farming domains. She has published extensively in IEEE journals and conferences, with expertise in fog node placement, vehicular network protocols, and VNF management. Dr. Sahoo serves on technical program committees for major conferences (IEEE ICC, Globecom, CCNC, LCN) and as Associate Editor for IEEE Access . She is certified by CompTIA Security+ and contributes to professional organizations like ACM, N² Women, and Women in Cybersecurity (WiCyS).
Professor Robert G. Maunder is affiliated with the University of Southampton and leads research in wireless communications, algorithms design, and hardware implementation. He has been with the School of Electronics and Computer Science since 2000, advancing from Lecturer to Professor in 2017. BEng (First Class) in Electronic Engineering (2003) PhD in Telecommunications (2007) His research focuses on joint source/channel coding and optimizing wireless communication systems through algorithm-hardware co-design. Recent work includes 5G non-terrestrial networks, OTFS modulation, and quantum code decoding. Key collaborators include Prof. Lajos Hanzo and Prof. Sir Bashir Al-Hashimi. Selected awards: IEEE Senior Member (2012), Chartered Engineer (IET, 2013), Fellow of the IET (2017). He supervises PhD student Arumjeni Mitayani and founded AccelerComm Ltd to commercialize soft-IP solutions.
Sergei Savitsky is a Professor at Wedel University of Applied Sciences, where he serves as Head of the Bachelor of Computer Science program and Senate Chairman. He has been a university lecturer at the institution since October 2008, following professional experience at NXP Semiconductors (2006-2008) and Philips Research Europe (2001-2006). His educational background includes: Doctorate in Engineering (Dr.-Ing.) from Technical University of Dresden (2002) with distinction "summa cum laude" Habilitation (Dr.-Ing. habil.) from Technical University of Dresden (2024) with teaching authorization in "Technical Computer Science" Diplom-Informatiker (equivalent to MSc) in Computer Science from Technical University of Dresden (1998) Savitsky's research focuses on reconfigurable computing systems , with particular expertise in FPGA design, hardware acceleration, and error correction coding. His work bridges theoretical computer science with practical hardware implementation, resulting in numerous patents and publications in top venues. He has made significant contributions to the development of adaptive hardware architectures for forward error correction, which are critical for modern communication and storage systems. His recent publications demonstrate a strong trajectory in optimizing hardware design processes, with particular focus on applying machine learning techniques like self-organizing maps and gradient descent algorithms to improve FPGA placement efficiency. His research spans both theoretical foundations and practical applications, with patents filed in collaboration with industry partners like NXP Semiconductors and ST-Ericsson. Among his recognitions is the Best Paper Award at CENICS 2019 for his work on accelerating FPGA placement algorithms. As an educator, Savitsky teaches courses related to digital system design, including "Computer-aided design of digital systems," where he emphasizes algorithmic aspects of Electronic Design Automation beyond basic digital technology concepts.
António Trigo is an Assistant Professor at ISCTE-IUL (University Institute of Lisbon) and an Integrated Researcher at ISTAR-Iscte, where he contributes to the Information Systems research group. He is affiliated with the Department of Information Science and Technology (ISTA), focusing on the intersection of technology and organizational management. His academic and professional activities span research, teaching, and leadership in information systems. Research Interests: His primary research areas include Management Information Systems, Business Process Management, IT Governance, Data Governance, Software Development, and Project Management. He investigates how organizations adopt and manage information technologies, with recent work on DevOps, low-code platforms, AI fairness, and digital transformation in education. His interdisciplinary approach integrates computer science, engineering, and management perspectives. Publication Trends: From 2022 to 2025, his research has been published in journals such as Sustainability , Journal of Open Innovation , and IT Professional , reflecting a strong focus on practical applications of information systems in business and society. Topics include digital transformation, AI ethics, project success, and data privacy, indicating a trajectory toward responsible and efficient technology deployment. Scientific Engagement: He serves on the editorial boards of several journals, including: International Journal of Information Systems and Project Management (Editor since 2015) International Journal of Human Capital and Information Technology Professionals (Editorial Team since 2020) International Journal of Smart Education and Urban Society (Editorial Team since 2017) He is also a frequent member of scientific committees for international conferences such as EMCIS, ARTIIS, and IBIMA. Teaching and Guidance: He has supervised 50 master’s dissertations and co-supervised 30, demonstrating a strong commitment to graduate education. He has held leadership roles in the Master’s program in Information Systems Management, including Director and Year Coordinator roles (2025–2027). He has also authored three editions of a textbook on programming with C#. Research Projects: He is involved in the InCITIES project, funded by the European Commission under Horizon Europe, which focuses on inclusive, sustainable, and resilient urban development through digital innovation and knowledge sharing among European universities.
João Carlos Marques Silva is an Assistant Professor at the Department of Information Science and Technology (ISTA), School of Technology and Architecture, ISCTE - Instituto Universitário de Lisboa. He is also an Integrated Researcher at ISTAR-Iscte, the Research Center in Information Sciences, Technologies and Architecture. His academic and professional expertise spans telecommunications, artificial intelligence, computer networks, cybersecurity, and technology management. PhD in Computer and Informatics Engineering, Higher Technical Institute - UTL, 2006 Integrated Master's Degree in Aerospace Engineering, University of Lisbon Higher Technical Institute, 2000 Master's in Management, ISEG, 2016 MBA, ISEG, 2015 Postgraduate studies in Competitiveness of Companies and Clusters, ISEG, 2015 His research interests include Artificial Intelligence , Computer Networks , 6G Systems , Cybersecurity , Project Management , and Business Management . He applies AI and machine learning techniques to next-generation communication systems and digital transformation in various sectors including construction and finance. He has supervised numerous graduate students, including 2 doctoral theses currently in progress and 11 master’s dissertations (8 completed, 3 in progress), as well as 1 completed master’s final project. His guidance spans topics such as applied machine learning for 6G, IoT network dimensioning, threat intelligence, DevOps, and generative design in construction. He has received multiple scientific awards, including the FAE/EDP Award for Business Case Writing in 2016, 2017, 2018, and 2019, and was recognized as Best Master’s Student in Management at ISEG and Best ISEG MBA Student in 2015. He also earned the Best Postgraduate Student CEDE 2016 award and an international recognition for Best Case Study 2018. João has been involved in significant research projects such as EnAcoMIMOC (underwater MIMO communications), LTE-Advanced Enhancements using Femtocells , SAAS (remote aerial surveillance), COILS (WiMAX vs LTE for multimedia services), and SATSTATION (satellite ground station development). He has also contributed to projects on enhanced UMTS networks and broadcasting over mobile broadband. He has held academic management roles including 3rd Year Coordinator for the Bachelor's in Computer Engineering and ECTS Coordinator for his department, and is currently a member of the Scientific Committee.
Marc St.-Hilaire is a Professor at the School of Information Technology and cross-appointed to the Department of Systems and Computer Engineering at Carleton University within the Faculty of Engineering and Design . He holds a Ph.D. from École Polytechnique de Montréal and serves as the NET Program Coordinator. He is a Senior Member of IEEE and has received multiple awards, including the Carleton Faculty Graduate Mentoring Award and the Teaching Achievement Award. Education: Ph.D., École Polytechnique de Montréal His research centers on telecommunication network planning, mobile computing, and network optimization , with strong emphasis on wireless and vehicular networks, fog/edge computing, blockchain integration, and AI-driven network protocols . His recent work applies reinforcement learning, genetic algorithms, and fuzzy logic to solve challenges in dynamic and distributed environments. The trend in his recent publications shows a strong focus on smart infrastructure , including Internet of Vehicles (IoV), smart grids, and cloud/edge resource management . He frequently collaborates with students and researchers on topics such as virtual network embedding, SLA-aware provisioning, and cooperative positioning , often leveraging emerging technologies like blockchain and deep learning. Scientific Awards and Honors: Senior Member, IEEE Best Industry Paper Award, WF-IoT 2024 Best Paper Award, ADHOCNETS 2019 Best Paper Award, iThings 2018 IEEE WIE Best Paper Award, CCECE 2018 Best Paper Award, ADHOCNETS 2017 Carleton Faculty Graduate Mentoring Award, 2014 Carleton Teaching Achievement Award, 2014–2015 Dr. St.-Hilaire actively supervises a large team of graduate students and has mentored over 40 Ph.D., Master’s, and postdoctoral researchers to completion. He has secured significant research funding through industry and government grants, enabling extensive experimental testbeds in SDN, fog computing, and vehicular networks. His work bridges theoretical optimization with practical implementation, often releasing tools and simulators (e.g., NetAnalyzer, DEVS fog simulator). He leads a vibrant research team focused on network intelligence, edge-based complex event processing, and sustainable computing . His lab collaborates with industry partners on projects involving 5G/6G integration, TSN in cloud environments, and smart city applications such as cloud-based waste management and smart grid simulation.
Vasileios Argyriou is an academic researcher affiliated with Kingston University, with extensive contributions in computer vision, image processing, and AI applications in IoT, healthcare, and smart agriculture. His work spans photometric stereo, motion estimation, federated learning, and UAV-based remote sensing. Research Interests: His research focuses on developing advanced computer vision techniques including photometric stereo for 3D reconstruction, deep learning for anomaly detection, federated learning for privacy-preserving AI, and AI-driven solutions for smart farming and healthcare. He explores motion estimation, facial recognition, and synthetic data generation for training robust models. The recent publications (2024–2025) highlight a strong trend toward applying machine learning in real-world systems—particularly federated learning for intrusion detection, UAV-based agricultural monitoring, 5G security, and medical imaging. His work integrates computer vision with IoT, wireless communications, and edge computing, demonstrating interdisciplinary innovation. Scientific Contributions: Author of a book on image and video registration with quality metrics. Extensive publication record in top journals including IEEE Transactions, Sensors, and Pattern Recognition. Pioneering work in photometric stereo, motion estimation using phase correlation, and GAN-based face reenactment. He has advised or collaborated with numerous researchers across fields, though specific student names are not listed. His work often involves large-scale data analysis, simulation frameworks, and real-time systems. He is involved in projects related to smart cities, precision agriculture, and autonomous systems. Laboratories and Teams: His collaborations suggest involvement with research groups focused on intelligent systems, computer vision, and IoT at Kingston University and beyond, particularly with Panagiotis Sarigiannidis, Thomas Lagkas, and others in networking and AI.
Michał Panek is a researcher at the Department of Computer Systems and Networks, Faculty of Computing, Wroclaw University of Science and Technology. He is a member of the Machine Learning Team (ZUM) and actively contributes to research in optimization and machine learning applications in networking. His research interests include: Machine Learning in cellular networks Multi-criteria and many-objective optimization Evolutionary algorithms with gene-linkage techniques Application-aware multi-layer network optimization Classifier training using optimization methods The research projects he is involved in focus on developing advanced general-purpose optimizers (Dark-Box Optimization), evolutionary methods for high-dimensional multi-criteria problems, and performance analysis for wireless network automation. These projects reflect a strong interdisciplinary trend combining computer science, optimization theory, and telecommunications engineering. Michał Panek serves as a supervisor for diploma theses and is engaged in teaching activities. He is currently completing his doctoral studies, with a thesis titled "Machine Learning-based performance analysis to enhance the wireless network automation," supervised by Prof. Michał Woźniak and Prof. Ireneusz Jabłoński. The defense is scheduled for March 18, 2025. He is involved in key research teams including: Machine Learning Team Teaching Team Computer Networks Team Advanced Data Analysis Methods Team Metaheuristics Team
Xiaonan Liu is a Lecturer (Assistant Professor) in the Department of Computer Science at the University of Aberdeen, affiliated with the School of Natural and Computing Sciences. Their research lies at the intersection of artificial intelligence, machine learning, and communication systems, with a strong focus on Edge AI and federated learning frameworks. Their primary research interests include: Integrated Sensing, Communication, and Computation Edge AI and machine learning Multimodal learning Federated Learning Task-oriented Communications Dr. Liu is actively accepting PhD students in Computing Science, Artificial Intelligence, and Engineering, encouraging prospective candidates to reach out with research proposals. Dr. Liu's scholarly work centers on advancing intelligent systems that integrate sensing, computation, and communication at the network edge. Their research trends reflect a strong emphasis on distributed AI, privacy-preserving machine learning, and efficient resource utilization in next-generation networks. This is aligned with emerging domains such as 6G communications and IoT-driven AI applications. There are no scientific awards mentioned in the provided text. Dr. Liu advises PhD students in areas related to AI, computing science, and engineering, and is open to new supervisees. While specific grants are not listed, their research scope suggests involvement in projects related to Edge AI, distributed systems, and intelligent communications. Teaching responsibilities include undergraduate and postgraduate courses such as JC2503 Web Application Development and JC4001 Distributed Systems. There is no explicit mention of labs or research teams, but their research specialisms suggest potential involvement in AI, communications, and distributed computing research groups within the School of Natural and Computing Sciences.
Kimmo Kansanen is an Adjunct Professor at Aalborg University , affiliated with the Department of Electronic Systems within the The Technical Faculty of IT and Design . His research focuses on cutting-edge wireless communication technologies, including Reconfigurable Intelligent Surfaces (RIS), Ultra-Reliable Low-Latency Communications (URLLC), and their applications in industrial and sensing systems. He has collaborated internationally on projects involving machine learning integration in wireless networks and industrial robotics. Main Research Themes : Wireless Sensing and Localization Reconfigurable Intelligent Surfaces (RIS) URLLC Optimization Machine Learning in Telecommunications Industrial IoT and Robotics His recent work explores statistical reliability in wireless systems and the potential of large intelligent surfaces (LIS) for high-resolution sensing in industrial environments. He has published in top conferences like IEEE ICC and journals like IEEE Open Journal of the Communications Society. Lab/Team Affiliation : Part of the Connectivity Section within the Department of Electronic Systems, focusing on advanced wireless systems and their practical implementations.
Dr. Pablo Sánchez Pérez is an Assistant Professor (Part-Time) at the Universidad Pontificia Comillas, specifically within the School of Engineering (ICAI), where he teaches core computer science subjects including Programming, Databases, Algorithms and Data Structures, and Fundamentals of Operating Systems. He earned his PhD in Computer Engineering and Telecommunications from Universidad Autónoma de Madrid (UAM) in 2021, where he was affiliated with the Information Retrieval Group. His current research focuses on recommender systems, machine learning, and information retrieval, with an emphasis on contextual factors such as time, sequence, and user behavior. Research Interests: His primary research areas include Machine Learning , Recommender Systems , Information Retrieval , and Artificial Intelligence . He investigates how contextual information—like temporal patterns and sequential behaviors—can enhance the accuracy and fairness of recommendation algorithms, particularly in tourism and location-based settings. His work also addresses critical issues such as bias mitigation, sustainability in tourism recommendations, and the evaluation of novelty and diversity in recommendations. The recent publications of Dr. Sánchez Pérez demonstrate a strong trend in advancing location-based and tourism-oriented recommender systems , with increasing attention to ethical AI , fairness , and sustainability . His work spans both theoretical contributions—such as new evaluation metrics—and practical applications, including data augmentation and reranking strategies. The interdisciplinary nature of his research connects computer science with tourism informatics and social impact. Scientific Awards: Accésit to Best Scientific Publication in Recommender Systems (2023–2024), ELIGE-IA Premio CAEPIA 2024 for 2nd best paper at SISREC 2024 Outstanding Reviewer Award, RecSys 2023 Honorable Distinction for Best Doctoral Thesis, UAM, 2022 Dr. Sánchez Pérez has been actively involved in academic service, including advising and peer review. He has served as a reviewer for top journals such as IEEE Communications Magazine , User Modeling and User-Adapted Interaction , and Information Processing & Management . He has also contributed to major conferences as a member of technical program committees (e.g., RecSys, RecTour, KaRS) and as Web Chair for HT’2022. While no formal grants are listed, his research has been disseminated through numerous publications and invited seminars, indicating strong scholarly engagement. Labs and Research Teams: He was previously affiliated with the Information Retrieval Group at Universidad Autónoma de Madrid during his PhD and postdoctoral research. Currently, he is associated with the Instituto de Investigación Tecnológica (IIT) at Universidad Pontificia Comillas, where he continues his research and delivers invited seminars.
Andrea M. Tonello is a Full Professor at the Institute of Networked and Embedded Systems, University of Klagenfurt, Austria, where he chairs the Embedded Communication Systems Lab. He previously held positions at the University of Udine, Italy, where he was an Associate Professor and founded the Wireless and Power Line Communication Lab (WiPLi Lab). His research spans power line communications, wireless systems, embedded communications, smart grids, and machine learning applications in signal processing. Doctor of Engineering, University of Padova (1996) Doctor of Research, Telecommunications, University of Padova (2003) His research interests focus on next-generation communication systems, including power line and wireless networks, signal processing, machine learning for communications, UAV systems, and smart grid technologies. He has made significant contributions to PLC channel modeling, full-duplex communications, and information-theoretic learning for communication systems. His work integrates theoretical innovation with practical implementation in real-world networks. The most recent publications highlight a strong trend toward integrating machine learning and information theory into communication systems, particularly in power line and wireless networks. Themes include f-divergence based classification, mutual information estimation, neural decoding (MIND), noise-robust receivers, and topology-aware machine learning for PLC quality prediction. There is also a notable focus on UAV control, full-duplex PLC, and digital pre-distortion techniques for high-speed converters. IET 2016 Premium Award Best Paper Award, ISPLC 2016 Best Student Paper Award, ISPLC 2016 Aerospace Best Paper Award, 2018 Best Paper Award, ISPLC 2021 Best PhD Dissertation Award, 2019 IEEE ComSoc Distinguished Lecturer (2018) Two Awards from IEEE ComSoc TC-PLC (2019) University of Klagenfurt Technology Scholarships (2019) Dr. Tonello has supervised numerous PhD and Master’s students, including notable advisees such as Nunzio A. Letizia, Davide Righini, and Babak Salamat. He has led over 10 institutional and multiple industrial research projects with a total funding exceeding 20 million euros. He played a key role in promoting international academic collaboration, including Erasmus agreements, joint PhD programs with INSA Rennes and Ecole Polytechnique de Grenoble, and a joint master’s program with the University of Klagenfurt. He founded and led the WiPLi Lab at the University of Udine, which received around 3 million euros in funding and involved over 60 researchers and students. He also founded WiTiKee s.r.l., a spin-off company specializing in PLC for smart grids. Currently, he chairs the Embedded Communication Systems Lab at the University of Klagenfurt, focusing on next-generation networked and embedded communication technologies.
Thuan Van Do is a Lecturer at the Department of Computer Science , Faculty of Technology, Art and Design , Oslo Metropolitan University. His research focuses on Cybersecurity , 5G Networks , and Software Engineering , particularly in the context of Welfare Technology and Network Security . Research Groups: Autonomous Systems and Networks (ASN) Key Topics: Threat modeling for mobile and 5G networks, zero-trust cybersecurity, secure welfare technology solutions for elderly care, FPGA cryptographic offloading, and anomaly detection in IoT using ML. Collaborations: Active participant in international conferences like MobiWIS, IWCMC, and GOODTECHS, often collaborating with researchers such as Boning Feng, Niels Jacot, and Bernardo Santos.
Dr. Muhammad Khan is a Senior Lecturer in Computer Science at the University of the West of England, Bristol, affiliated with the School of Computing and Creative Technologies and the Department of Computer Science and Creative Technologies within the College of Arts, Technology and Environment. Educational Background : First Class Honours in Engineering (2008) PhD in Electronic & Computer Engineering (2013–2018) Research Interests : Dr. Khan specializes in cutting-edge telecommunications and computer science domains, including: Artificial Intelligence and Machine Learning for network optimization Congestion Control and Load Balancing in 5G and Beyond Networks Cloud Radio Access Networks and Data Analysis for next-generation communication systems Scientific Awards : Awarded a prestigious PhD scholarship under the Higher Education Commission Faculty Development Program in 2013 for his academic excellence. Academic Career : Dr. Khan began his teaching journey in 2009 as a Lecturer in Computer Science and later conducted postdoctoral research on 5G congestion control at New York University (2020–2022). Currently, he mentors students at the University of the West of England, focusing on advancing telecommunications technology through collaboration and innovation.
Kevin Lu is a Teaching Professor and Associate Dean for Undergraduate Studies at the Charles V. Schaefer, Jr. School of Engineering and Science at Stevens Institute of Technology . He holds a D.Sc. in Systems Science and Mathematics from Washington University in St. Louis and has over 40 years of experience in telecommunications R&D, academia, and standards development. Lu's career spans roles at Bellcore/Telcordia, Broadcom, and Stevens Institute of Technology. IEEE Life Senior Member since 1980 2018 transition from industry to academia after 28 years at Bellcore/Telcordia 2024 recipient of IEEE Standards Association Distinguished Service Award Research Interests: Focus on optical networks , telecommunications infrastructure , and Internet of Things education. His work explores network survivability , data integrity in AI systems , and passive optical network deployment . Current teaching includes courses on Digital System Design and Internet of Things . Standards Leadership: Lu chairs the IEEE Standards Board Industry Connections Committee and has served on multiple IEEE SA committees since 2005. His 2024 award recognized governance leadership in industry-standard development processes. Academic Contributions: Lu transitioned to full-time academia in 2018 after serving as Adjunct Professor at Stevens since 2015. His teaching philosophy emphasizes lifelong learning and soft skill development alongside technical knowledge. He received Stevens' Henry Morton Distinguished Teaching Professor Award and departmental teaching/service awards.
