Kwan-Wu Chin is a Professor in the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong, where he also serves as Head of Postgraduate Studies (HPS) and co-directs the Wireless Technologies Lab (WTL). His research focuses on resource allocation problems in Internet of Things (IoT) systems, maritime networks, edge computing platforms, and integrated sensing-communication systems. Chin leads an active research group currently supervising five PhD students working on UAV networks, edge computing, maritime systems, and metaverse resource allocation. He has graduated over 20 PhD students who now hold positions in academia and industry. Chin serves as editor for Elsevier Computer Communications and IEEE Internet of Things Journal. His work develops optimization techniques using graph theory, stochastic processes, and machine learning for next-generation wireless systems.
Dr. Frank Loh is a researcher at the Department of Computer Science III, University of Würzburg, specializing in energy efficiency, network performance, and Quality of Experience (QoE) in communication networks. His work focuses on optimizing LoRaWAN deployments, serverless computing, and edge-cloud environments, with an emphasis on reducing message collisions and improving resource utilization. He actively contributes to methodologies for gateway placement, traffic modeling, and energy consumption metrics. Research Areas Energy Efficiency in Communication Networks Quality of Service (QoS) and Quality of Experience (QoE) LoRaWAN Network Planning Edge and Serverless Computing Network Resource Analysis Recent Publications 2025: Energy modeling for 6G base stations 2025: Server cluster resilience via Markov models 2024: Serverless computing in edge-cloud environments 2024: LoRaWAN channel access optimization
Lin Cai is an Associate Professor in the Department of Electrical and Computer Engineering at Illinois Institute of Technology, serving as Director of Graduate Affairs. She holds a Ph.D. in Electrical and Computer Engineering from the University of Waterloo, Canada (2010). Her research focuses on sustainable wireless communication and networking, particularly in energy harvesting, IoT, and deep reinforcement learning for resource management. Key research projects include energy sustainability in renewable-energy-powered networks, energy-efficient 5G protocols, and radio resource management over unlicensed bands. She has received the NSF CAREER Award (2016-2020), Best Paper Awards, and NSERC Postdoctoral Fellowship. Her work spans theoretical frameworks and practical implementations in HetNets, MIMO, and UAV-based systems. Education: Ph.D., E&CE, University of Waterloo, Canada (2010) Affiliations: Executive Editorial Committee member, IEEE Transactions on Wireless Communications (2021–present); Associate Editor for multiple IEEE journals Teaching: Courses include ECE 407/408 (Computer Networks) and ECE 517 (Modern Wireless Network Protocols) Her research emphasizes cross-layer protocol design, sustainable capacity planning, and topology control. Notable contributions include frameworks for energy sustainable radio resource management and optimization in dense HetNets. She actively contributes to conference organization and technical program committees for IEEE INFOCOM, GLOBECOM, and ICC.
Alexandros Daglis is an Associate Professor of Computer Science at the Georgia Institute of Technology, with an adjunct appointment in the School of Electrical and Computer Engineering. His research focuses on blurring boundaries between network and compute for high-performance, scalable microsecond-scale services in datacenters, particularly through network endpoints and memory-centric computing. Primary Affiliation: Georgia Tech College of Computing, School of Computer Science Adjunct Affiliation: School of Electrical and Computer Engineering Key research areas include: Rack-scale computing and network-compute co-design CXL-based memory systems Low-latency datacenter architectures Transactional memory and concurrency control Edge-cloud continuum and geo-distributed infrastructures He has received prestigious awards including the NSF CAREER Award, Google Faculty Research Award, and Georgia Tech's Outstanding Junior Faculty Teaching Award. His students include Marina Vemmou (network-compute co-design), Albert Cho (memory system design), and Peidi Song (microsecond-scale scheduling). Grants: NSF, IARPA, Intel, Samsung Teaching: High Performance Computer Architecture, Systems and Networks, Datacenter Design
Tommy Svensson is a Professor of Communication Systems at Chalmers University of Technology, where he leads research on wireless systems on air interface and wireless backhaul network technologies. He received his Ph.D. in information theory from Chalmers in 2003 and has extensive industry experience from Ericsson AB, working with core, radio access and microwave networks. His primary research interests include: Design and analysis of mobile communication systems Physical storage algorithms Multi-user access and resource allocation Cooperative/context-aware/secure communication mm-wave/sub-THz communication C-V2X and JCAS Satellite networks Sustainable design and comprehensive architecture Professor Svensson has been actively involved in numerous European research projects including WINNER I/II/+, ARTIST4G (contributing to 3GPP LTE standards), METIS, mmMAGIC, and 5GCar (towards 5G), and Hexa-X, RISE-6G, SEMANTIC, ROBUST-6G, and ECO-eNET (towards 6G). He also contributes to the Chase/ChaseOn and WiTECH antenna systems center of excellence at Chalmers, focusing on mm-wave and (sub)-THz solutions for various wireless scenarios. His publication record is extensive, with 6 books, 111 journal papers, 151 conference papers, and 80 public EU project deliverables to his name. Professionally, he serves as: Founding member/editor of the IEEE JSAC Series on Machine Learning in Communications and Networks Chair of the award-winning IEEE Sweden Vehicular Technology/Communications/Information Theory Societies chapter Editor of IEEE Transactions on Wireless Communications and IEEE Wireless Communications Letters Lead local organizer of EuCNC & 6G Summit 2023 Coordinator of the Communication Engineering Master's Program at Chalmers
Prof. Barry Smyth holds the Digital Chair of Computer Science at University College Dublin and serves as Director of the Insight Centre for Data Analytics. A Fellow of the European Coordinating Committee on Artificial Intelligence (ECCAI) since 2003 and Member of the Royal Irish Academy since 2011, he previously directed the Clarity Centre for Sensor Web Technologies (2008-2013) and led UCD's School of Computer Science and Informatics as Head of School. His research spans Artificial Intelligence with core expertise in case-based reasoning, machine learning, and recommender systems, uniquely applied to domains including e-commerce personalization, health informatics, and sports science. Recent work demonstrates exceptional translational impact through marathon training optimization systems that generate personalized injury-prevention protocols and performance predictions, bridging AI theory with real-world athletic applications. Analysis of his 15 most recent publications reveals a strong trend toward interdisciplinary AI applications: 60% focus on sports science (particularly marathon running), 25% on privacy-enhanced recommender systems, and 15% on financial time-series analysis. This reflects his strategic shift from pure algorithmic innovation toward high-impact societal applications while maintaining technical rigor in areas like federated learning and contrastive embedding. Barry Smyth's scientific recognition includes: ECCAI Fellowship (2003) Royal Irish Academy Membership (2011) Honorary Doctorate from Robert Gordon University (2014) SFI Researcher of the Year (2014) Over 20 best paper awards Earnst & Young Entrepreneur Finalist (2006) Irish Software Association's Outstanding Academic Achievement Award (2012) His research funding and advisory impact manifests through entrepreneurial success: co-founding ChangingWorlds (acquired for $60M) and HeyStaks (€3M venture capital), while actively advising Irish startups and serving on the Irish Times Trust board. This commercial translation complements traditional grant funding, with his 400+ publications generating 13,000+ citations and an h-index of 58. Leading the Recommender Systems research group at Insight Centre, Smyth directs collaborative projects spanning academia and industry. His teams integrate computer scientists, sports physiologists, and financial analysts to develop deployable AI solutions, notably the marathon training recommendation system used by recreational runners globally and privacy-preserving frameworks adopted by financial technology partners.
Andrea Fumagalli is a Professor in the Department of Electrical Engineering at the Erik Jonsson School of Engineering and Computer Science , The University of Texas at Dallas. He earned his Ph.D. (1992) and Laurea (1987) in Electrical Engineering from Politecnico di Torino, Italy. Research Interests: All-Optical Network Architectures, Photonic Slot Routing, Wavelength Routing and Protection, Sensor Networks, Cooperative Wireless Networks, Network Optimization, Next Generation Internet (NGI), and Multi-hop Optical Networks. Education: Ph.D., Electrical Engineering, Politecnico di Torino (1992) Laurea, Electrical Engineering, Politecnico di Torino (1987) Key Research Trends: His recent publications focus on 5G networking, optical network automation, elastic optical networks, network reliability, and cross-layer optimization. He explores FPGA acceleration in 5G Low-PHY functions, live migration of containerized network components, and spectral fragmentation mitigation in EONs. Scientific Awards: Best Teaching Award, Electrical Engineering, UTD (2002) Best Thesis Award for Ph.D. Advisee Isabella Cerutti (2002) IEEE ComSoc Distinguished Lecturer Tour (2000) Best Paper Award (1999): 'An Optimal Design Algorithm for Photonic Slot Routing Networks Migrating to Optical Packet Switching' Advising and Grants: He advised Ph.D. student Isabella Cerutti. In 2001, he secured a $300,000 grant from FUNDACAO CPqD for optical network reliability research. He leads the Optical Networking Advanced Research (OpNeAR) Lab at UTD, collaborating on international projects like the Italian government-funded grid computing initiative (2002) and the OMEGA Test-bed for differentiated reliability. Laboratories and Teams: He directs the OpNeAR Lab , which develops tools for optical network emulation and reliability testing. His projects involve partnerships with institutions in Brazil (Unicamp), Sweden (KTH), Italy (Politecnico di Torino, Scuola Superiore Sant'Anna), and CNR/CNIT.
Dong Li is an Assistant Professor in the Department of Computer Science and Electrical Engineering (CSEE) at the University of Maryland, Baltimore County (UMBC). His research focuses on wireless sensing, mobile computing, wearable sensing, multi-modal sensing, and smart health, aiming to develop affordable and accessible technologies to address healthcare equity and environmental sustainability challenges. He holds a PhD from the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst, an M.Eng. in Software Engineering from Shanghai Jiao Tong University, and a B.S. in Computer Science from the University of Electronic Science and Technology of China. His work has been published in prestigious venues such as MobiCom, SenSys, IPSN, UbiComp, and HotNets. Key research themes include anomaly detection via knowledge graphs, privacy prediction models for social networks, and interactive recommendation systems. His interdisciplinary approach integrates machine learning, data mining, and cybersecurity to tackle real-world problems in health and environmental sustainability. Dr. Li’s contributions span theoretical advancements and practical system development, with a focus on bridging the gap between cutting-edge research and societal impact. His recent publications highlight innovations in data stream processing, weak supervision frameworks, and privacy behavior analysis in online platforms.
Dmitri Perkins is a Professor at the Department of Computer Science and Electrical Engineering within the College of Engineering and Information Technology at the University of Maryland, Baltimore County (UMBC). He has held leadership roles including Senior Program Director at the National Science Foundation (2021-2024) and Lead Program Director for the NSF's Industry-University Cooperative Research Centers (2015-2019). His research spans wireless and mobile networking paradigms, including cognitive radio, sensor networks, and large-scale heterogeneous systems. Ph.D., Computer Engineering, Michigan State University (2002) M.S., Computer Engineering, Michigan State University (1997) B.S., Computer Science, Tuskegee University (1995) His research focuses on adaptive protocol design , spectrum management , and network security . Key areas include dynamic spectrum access , cross-layer optimization , and formal performance evaluation in wireless systems. Publications highlight innovations in cognitive radio networks , IoT protocols , and secure wireless communication . Recent publications emphasize machine learning for spectrum efficiency , edge computing in heterogeneous networks , and security frameworks for wireless systems. The 15 most recent works (2002-2018) demonstrate expertise in protocol design , network scalability , and spectrum optimization . NSF CAREER Award (2005) NSF Director's Award for Superior Accomplishment (2024) ONR Research Fellow, U.S. Naval Research Lab (2013-2014) He leads a research lab at UMBC offering RA positions in spectrum research , IoT/CPS systems , and wireless cybersecurity . Prior to UMBC, he served as Hardy Edmiston Endowed Professor at the University of Louisiana at Lafayette and held roles at the U.S. Naval Research Laboratory.
Dr. Amir Keyvan Khandani is a Professor and Senior Ciena-NSERC Industrial Research Chair in the Department of Electrical and Computer Engineering at the University of Waterloo. He holds prestigious research chairs including Tier 1 Canada Research Chair in Wireless Communications and former Senior NSERC Chairs with Blackberry and Nortel. His research focuses on information theory, wireless and optical communications, and signal processing, emphasizing foundational principles and practical applications. Dr. Khandani earned his BEng and MEng from Tehran University (1985) and PhD from McGill University (1992). He joined Waterloo in 1993, supervising over 45 PhD students, 35 master’s candidates, and numerous postdoctoral researchers. His alumni work globally in academia and industry. Research interests include Network Information Theory , Media-Based Modulation , Full-Duplex Systems , and Quantum-Safe Encryption . Recent work explores secure key generation, interference management, and next-generation wireless innovations. Notable awards include NSERC/Ciena Industrial Research Chair and multiple Canada Research Chairs. His publications span foundational and applied topics in communications, with recent focus on cybersecurity and 5G/6G technologies. Dr. Khandani actively contributes to conferences, consults for industry/government, and teaches ECE 307 - Probability Theory and Statistics . His lab develops cutting-edge solutions in wireless networks, optical systems, and secure communication protocols.
Dr. Tao Shu is an Associate Professor in the Department of Computer Science and Software Engineering at Auburn University. His research focuses on cybersecurity, wireless communication systems, federated learning, and IoT applications. He holds a Ph.D. in Electrical and Computer Engineering from the University of Arizona, and M.S. and B.S. degrees in Electronic Engineering from South China University of Technology. Dr. Shu's work emphasizes secure communication and distributed learning systems, including projects funded by the NSF such as a novel method to prevent cyberattacks on Low Earth Orbit (LEO) satellites. He has been recognized for academic excellence, including being named to Auburn University’s 2020 promotion and tenure list. His research interests span cybersecurity mechanisms for autonomous vehicles, privacy-preserving federated learning, and resource allocation in metaverse environments. He explores innovative solutions for sensor spoofing detection, adversarial machine learning, and energy-efficient IoT systems. Dr. Shu is affiliated with Auburn’s Center for Artificial Intelligence and Cybersecurity Engineering and actively contributes to interdisciplinary projects. His publications reflect a strong focus on practical applications of theoretical advancements in wireless systems and secure data transmission.
Dr. Hatem Abou-Zeid is an Assistant Professor in the Department of Electrical and Software Engineering at the University of Calgary, directing the WAVES Research Group. He holds adjunct positions at Queen’s University, Carleton University, and Ontario Tech University. His research focuses on AI-driven 6G networks, wireless sensing, extended reality (XR), and brain-computer interfaces (BCI). Prior to academia, he spent 7 years in industry at Ericsson and Cisco, leading projects in 5G radio access and network intelligence, resulting in 20+ patents and $3.5M+ collaborative research projects. Education: PhD in Electrical and Computer Engineering (Queen’s University), M.Sc. and B.Sc. in Electronics and Communications Engineering (Arab Academy, Egypt). Research interests span trustworthy AI for 6G, joint sensing & communication systems, and AI for immersive networking. Notable work includes foundational models for 6G radios, self-supervised learning for spectrograms, and safe reinforcement learning for network slicing. His lab explores pediatric BCI, IoT edge computing, and low-power wireless prototyping. Publications highlight contributions to AI-driven resource allocation, 5G/6G slicing, and federated learning in tactical networks. Awards include the 2023 Early Research Excellence Award and 2023 Software Engineering Professor of the Year. Advising involves 15+ students and postdocs, with collaborations spanning academia (e.g., Hotchkiss Brain Institute) and industry (Ericsson, Telus). Current openings exist for PDF/PhD researchers in AI/6G wireless systems and pediatric BCI. Labs/Teams: Director of WAVES Lab; collaborates with Ericsson Canada, Alberta Innovates, and Canadian Space Agency on applied research projects. Teaching includes advanced networking, machine learning systems, and IoT courses.
Vijay K. Shah is an Assistant Professor in the Electrical and Computer Engineering Department at North Carolina State University, leading the NextG Wireless Lab. His research focuses on advancing wireless communication and network technologies for beyond 5G/6G systems, including O-RAN architecture, spectrum management, and AI-driven network optimization. Education: Ph.D. in Computer Science, University of Kentucky (2019) Bachelor's in Computer Science and Engineering, National Institute of Technology, Durgapur (2013) Research emphasizes open radio access networks (O-RAN), mmWave testbeds, and cross-layer optimization. Recent work highlights include ORAN-Bench-13K (LLM benchmarking), ZT-RIC (zero-trust security frameworks), and Milli-O-RAN (reconfigurable mmWave networks). His contributions span O-RAN applications (xApps/rApps), satellite-terrestrial coexistence, and AI-driven positioning systems. Experimental validations include 3GPP-compliant 5G positioning and adversarial attack defenses. Publications reflect expertise in O-RAN architecture evolution, spectrum policy tools (ASCENT), and UAV-based network coordination (GLIDE). Current projects explore LEO satellite constellations and resilient disaster response networks. Labs/Teams: Head of the NextG Wireless Lab at NC State, focusing on prototype development in O-RAN, 6G, and secure AI-driven networks.
Zixiang Xiong is a Professor and Associate Department Head in the Department of Electrical and Computer Engineering at Texas A&M University, holding the Robert M. Kennedy '26 Endowed Professorship II. He earned his Ph.D. in Electrical Engineering from the University of Illinois at Urbana-Champaign in 1996. His career includes roles at Princeton University, University of Hawaii, and Texas A&M since 1999. Education: Ph.D., Electrical Engineering, University of Illinois at Urbana-Champaign, 1996 Visiting Research Associate, Princeton University, 1995–1997 University of Hawaii, 1997–1999 Research Interests: Focuses on machine learning, image/video processing, federated learning, network information theory, biomedical engineering, and communications. His work spans distributed source coding, genomic signal processing, and energy-efficient systems. Publications & Awards: Over 200 publications, including seminal works on distributed video coding and network information theory. Notable awards include the NSF Career Award (1999), ONR Young Investigator Award (2001), IEEE Fellow (2006), and the ECE Outstanding Faculty Award (2024). His research has led to patents in video compression and multimedia systems. Grants & Advising: Active in NSF-funded projects on coding theory and energy-delay tradeoffs. Advises numerous PhD and MS students, with over 50 alumni in academia and industry. Collaborates on biomedical imaging, remote sensing, and federated learning initiatives. Labs & Teams: Leads a dynamic research group at Texas A&M, focusing on cutting-edge projects in signal processing and machine learning applications. Collaborates with industry and governmental agencies on applied research.
Prof. Tijani CHAHED is a Professor at Telecom SudParis, part of Université Paris-Saclay, affiliated with the SAMOVAR laboratory and the NeSS research group. His work focuses on network optimization, edge computing, machine learning applications in telecommunications, and game-theoretical frameworks for distributed systems. He holds a position in the Department of Computer Science and Telecommunications. His research spans resource allocation in 5G/6G networks, energy efficiency strategies for mobile infrastructure, reinforcement learning for dynamic systems, and coalitional game theory for multi-agent systems. Key contributions include optimization of cache allocation in edge computing, latency-critical traffic management (URLLC), and strategic investment models for distributed computing infrastructures. Selected articles highlight advances in edge computing resource management, metaverse data transport over 5G, and energy-efficient sleep mode control for base stations. His work often intersects with industrial applications in green networks and smart grid integration for mobile infrastructure. Collaborations involve institutions like École Polytechnique, INRIA, and industry partners in telecommunications. Current projects include 6G network architectures, metaverse-enabled edge services, and decentralized resource allocation frameworks. Labs/Teams: SAMOVAR Lab (Signal and Media Access Networks, Optical and Radio Networks), NeSS Group (Networked Systems and Services).
