Halim Yanikomeroglu is a Full Professor and Chancellor's Professor at Carleton University's Department of Systems and Computer Engineering, part of the Faculty of Engineering and Design. His research focuses on wireless communications, including 5G/6G networks, non-terrestrial systems (HAPS/LEO satellites), MIMO, and cognitive radio. He has supervised numerous graduate students and holds IEEE Fellow status and the Harold Sobol Award. His work integrates machine learning, federated learning, and sustainability into next-generation networks. Affiliations: Carleton University, IEEE Education: Ph.D. (Toronto), M.A.Sc. (Toronto), B.Sc. (Middle East Technical University) Research interests span cellular networks, relay architectures, and energy-efficient systems. He pioneered cell-switching strategies for green networks and contributed to HAPS and UAV-based infrastructure. His recent work addresses NTN integration, AI-driven spectrum management, and 6G innovations. Awards include IEEE Fellow (2017) and multiple Research.com leadership accolades. His 150+ publications span journals like IEEE Transactions and conferences like ICC. Advising over 50 students, he emphasizes interdisciplinary solutions for future wireless challenges.
John C. Doyle is the Jean-Lou Chameau Professor of Control and Dynamical Systems, Electrical Engineering, and BioEngineering at the California Institute of Technology (Caltech), where he holds appointments in the Division of Engineering and Applied Science with primary affiliation in the Control and Dynamical Systems Department. His research bridges theoretical foundations with applications across biological, technological, medical, and ecological networks. He earned a BS and MS in Electrical Engineering from MIT (1977) and a PhD in Mathematics from UC Berkeley (1984), followed by consultancy at Honeywell Systems and Research Center (1976-1990). MIT: BS & MS in Electrical Engineering (1977) UC Berkeley: PhD in Mathematics (1984) Doyle's research centers on universal laws and architectures in complex systems, emphasizing robustness-efficiency tradeoffs, speed-accuracy tradeoffs (SATs), diversity-enabled sweet spots (DeSS), bowtie/hourglass structures, and evolvability. His work pioneers System Level Synthesis (SLS) for control systems with sparse, local, saturating, delayed, noisy, quantized, and distributed (SLSDNQD) components, integrating control theory, computation, communication, and machine learning to address challenges from neural networks to infrastructure resilience. Key concepts include virtualization, horizontal transfer, and virality in multiscale systems. Analysis of his publication trends reveals consistent interdisciplinary impact across neuroscience (brain connectivity modeling), systems biology (metabolic oscillations), network science (internet topology), and physics (turbulence, earthquakes), with recurring themes of robust-efficiency limits and architectural principles governing complex networks. His work demonstrates exceptional translation from abstract theory to practical tools like the Matlab Robust Control Toolbox and Systems Biology Markup Language (SBML). His scientific recognition includes: 1990 IEEE Baker Prize (ranked among top 10 most important mathematics papers 1981-1993) Three IEEE Automatic Control Transactions Awards (1998, 1999, 2021) ACM Sigcomm Paper Prize (2004) and Test of Time Award (2016) IEEE Control Systems Field Award (2004) Multiple early-career honors including IEEE Centennial Outstanding Young Engineer (1984) Doyle has mentored generations of students whose contributions include foundational software tools adopted globally. His research has secured sustained funding from NSF, NIH, and other agencies supporting theoretical advances in control frameworks and their applications to biomedical systems, network infrastructure, and environmental modeling. The SBML initiative exemplifies his group's impact in standardizing computational biology research. He leads a highly collaborative research ecosystem at Caltech that integrates engineers, biologists, neuroscientists, and computer scientists to develop universal principles for complex networks. Current efforts focus on translating theoretical insights into health technologies, resilient infrastructure, and climate-responsive systems through the application of robust-efficiency frameworks to emerging challenges in cyber-physical and biological domains.
Chicheng Zhang is an Assistant Professor in the Computer Science Department at the University of Arizona, where he conducts research in the theory and applications of interactive machine learning. He earned his Ph.D. in Computer Science from the University of California, San Diego (UCSD) in 2017 under the supervision of Professor Kamalika Chaudhuri, and was previously an undergraduate student at Peking University working with Professor Liwei Wang. From 2017 to 2019, he was a postdoctoral researcher at the Machine Learning Group at Microsoft Research NYC. His research lies at the intersection of learning theory and practical algorithm design, focusing on interactive machine learning paradigms such as reinforcement learning, contextual bandits, active learning, and imitation learning. He aims to develop algorithms that are data-efficient, computationally tractable, and robust, with applications in healthcare, wireless communication, and fair AI systems. His work emphasizes principled algorithm design with theoretical guarantees and empirical validation. The most recent publications reflect a strong trend in developing efficient, theoretically grounded methods for sequential decision-making and interactive learning. Key themes include sample efficiency, robustness to noise, fairness in algorithmic decisions, and application-driven research in domains like oral cancer detection and mmWave network optimization. His work frequently bridges theoretical analysis with real-world deployment considerations. While no scientific awards are mentioned in the provided text, Dr. Zhang actively mentors prospective PhD students and encourages collaboration. He has contributed to interdisciplinary projects involving fairness-aware bandit algorithms for network coexistence, interpretable classifiers for cancer detection, and LLM-based initialization for reinforcement learning. His lab focuses on developing intelligent agents that actively learn from environments and human experts. He can be reached at chichengz@arizona.edu .
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. Sie Teng Soh is an Associate Professor at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences. With qualifications including a PhD from Louisiana State University, he specializes in computer networks, wireless systems, and algorithm design. Research focuses on: Network topology optimization for UAV systems Energy-efficient IoT task scheduling Reliable wireless communication protocols Game-theoretic network management Green computing in software-defined networks Publication trends show advancing work in UAV network optimization, with recent articles addressing max-min rate optimization, energy harvesting in IIoT, and machine learning approaches for coverage prediction. His research consistently addresses practical challenges in wireless network deployment under real-world constraints. Teaching areas include advanced courses in network reliability and traffic engineering. Professional service includes editorial roles for IEEE Transactions on Parallel and Distributed Systems and program committee memberships for major conferences including FAST and EuroSys.
David B. Johnson is a tenured full Professor of Computer Science and Electrical and Computer Engineering at Rice University. He leads the Monarch research group, focusing on mobile networking architectures. Previously, he served as an Associate Professor at Carnegie Mellon University (1992–2000). His research emphasizes network protocols, distributed systems, and operating systems, with notable contributions to Mobile IP standards and wireless ad hoc networks. He holds a PhD, MS, and BA from Rice University (1990, 1985, 1982). Education: PhD in Computer Science, Rice University (1990) MS in Computer Science, Rice University (1985) BA in Computer Science and Mathematical Sciences, Rice University (1982) Research Interests: Johnson's work centers on adaptive wireless/mobile networking protocols, including Mobile IP, multihop wireless systems, and security protocols. His Dynamic Source Routing (DSR) protocol for ad hoc networks is an IETF standard. He has been deeply involved in IETF standards development for over 15 years, particularly in Mobile IP and MANET working groups. Awards & Leadership: ACM SIGMOBILE Chair (2005–2009), Treasurer (1997–2005) Conference leadership roles: General Chair for IEEE MASS 2012, COMSNETS 2011, and others Editorial roles: IEEE Pervasive Computing (Founding Board), Ad Hoc Networks, and more Labs & Teams: Monarch Group at Rice University, previously at Carnegie Mellon, develops next-generation mobile networking architectures.
Omprakash Gnawali is an Associate Professor in the Department of Computer Science at the University of Houston, with expertise in Internet of Things, wireless sensor networks, and artificial intelligence. His research focuses on advanced networking protocols, mobility analysis, and safety monitoring systems. Postdoctoral work at Stanford University PhD in Computer Science from University of Southern California Masters and Bachelors from Massachusetts Institute of Technology His research interests include Ultra-Wideband (UWB) localization, network protocol design, edge computing for monitoring systems, and mobile sensor networks. He leads the Networked Systems Laboratory , where he develops frameworks like the Collection Tree Protocol and CodeDrip for efficient data dissemination. Recent publications highlight trends in UWB-based safety monitoring, routing optimization in dual-radio networks, and deception detection in cybersecurity. He has secured NSF Student Travel Grants for ACM SenSys conferences in 2016 and 2017. Scientific Awards NSF Student Travel Grant (2017) NSF Student Travel Grant (2016) He actively mentors students in research projects and teaches courses such as Research Methods in Computer Science and Computer Networks . His service roles include Technical Program Committee memberships and chairing the TinyOS Network Protocol Working Group.
Dr. Mohammed Elamassie is an Assistant Professor at Özyeğin University's Graduate School of Science and Engineering, Department of Electrical and Electronics Engineering. He co-directs the Centre of Excellence in Optical Wireless Communication Technologies (OKATEM) and holds senior memberships in IEEE and Optica. PhD in Electrical and Electronics Engineering (Özyeğin University, 2020) MSc in Electrical and Electronics Engineering (Islamic University of Gaza, 2011) BSc in Electrical and Electronics Engineering (Islamic University of Gaza, 2006) Dr. Elamassie's research focuses on optical wireless communication systems, with specific expertise in underwater visible light communication (UVLC), vehicular visible light communication (V2V), airborne free space optical (FSO) networks, and turbulence mitigation techniques. His work addresses atmospheric channel modeling, diversity techniques, and MIMO communication challenges across multiple mediums. Analysis of his 15 most recent publications reveals critical trends in UVLC turbulence modeling, FSO UAV optimization, RIS-aided systems, and vehicular communication reliability. These works demonstrate his leadership in developing practical solutions for channel degradation and mobility-induced challenges. Best Paper Award, IEEE Black Sea Conference (2019) IEEE Turkey PhD Thesis Award (2020) Senior Member, IEEE Senior Member, Optica Optica Traveling Lecturer/Speaker Dr. Elamassie serves as Review Editor for Frontiers in Communications and Networks, covering 'Non-Conventional Communications' and 'Wireless Communications' sections. He contributes to OKATEM's research on optical wireless technologies, focusing on practical implementations across underwater, vehicular, and airborne domains.
Montserrat Ros is an Associate Professor and Associate Dean (Education) at the School of Electrical, Computer and Telecommunications Engineering within the Faculty of Engineering and Information Sciences at the University of Wollongong, Australia. She has been with the university since 2006, initially joining as a Lecturer in Computer Engineering and progressing to her current senior academic and leadership roles. Her educational background includes: B.E.(Hons1)/B.Sc. double degree majoring in Computer Systems Engineering and Mathematics from the University of Queensland (2000) Ph.D. degree in Computer Engineering from the University of Queensland (2007) Professor Ros's research focuses on the intersection of embedded computing systems and practical engineering applications. Her work spans several key areas including embedded systems design, sensor network data fusion, cyber-physical systems development, and innovative approaches to engineering education. She has particular expertise in sensor-based localization techniques, computer architecture optimization, and code compression methodologies for resource-constrained environments. More recently, her research has expanded into machine learning applications for constrained systems and Internet of Things implementations. Analysis of her recent publication record reveals a strong emphasis on Internet of Things networks, UAV-based systems, and applications of artificial intelligence in both engineering education and manufacturing processes. Her work demonstrates a consistent pattern of bridging theoretical computer engineering concepts with practical real-world applications across diverse domains including healthcare, environmental monitoring, and industrial automation. Her significant contributions to academia have been recognized through numerous prestigious awards: 2019: AAUT Citation for Outstanding Contribution to Student Learning 2018: IEEE TALE 2018 Meritorious Service Award 2018: Featured in UOW Leadership in Education Booklet 2017: UOW Vice Chancellor's Award for Outstanding Contribution to Teaching and Learning 2016: UOW Women of Impact for inspiring young women in STEM 2015: UOW Vice Chancellor's Interdisciplinary Research Excellence Award 2012 & 2007: UOW Vice Chancellor's Awards for Teaching Excellence 2011: UOW Vice Chancellor's Award for Community Engagement Senior Fellow of WATTLE (Wollongong Academy for Tertiary Teaching & Learning Excellence) Professor Ros has secured substantial research funding across multiple projects spanning from 2006 to the present. Her grant portfolio demonstrates a consistent focus on engineering education innovation, sensor network development, and practical applications of embedded systems. Notable projects include "The AI Tutor: Enabling 24x7 student support across engineering" (2024), "AI/IoT-powered Airborne System for Monitoring Water Level and Tidal Floods" (2023), and "Smart Eye: Airborne and AI-Driven Assessment Solution of Sugarcane" (2022). She actively supervises HDR students and has completed multiple successful candidatures. Her leadership extends beyond research and teaching, as evidenced by her role as Associate Dean (Education) for the Faculty of Engineering and Information Sciences. She is also actively involved in community engagement through volunteering with the State Emergency Service (Wollongong SES) and Athletics Wollongong Club.
Scott F. Midkiff is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on networking, telecommunications, and cybersecurity, with particular emphasis on 5G, O-RAN, edge cloud computing, and interference management in wireless networks. He holds a Ph.D. from Duke University (1985), an M.S.E.E. from Stanford University (1980), and a B.S.E. from Duke University (1979). Midkiff’s work spans theoretical and applied domains, including stochastic optimization for RAN intelligent controllers, network slicing, and wireless control plane design. He has contributed to advancements in interference alignment, MIMO systems, and secure spectrum sharing. His awards include the ORBIE Award and Capital CIO of the Year. Awards: ORBIE Award, Capital CIO of the Year Service: Member at Large, IEEE Committee on Engineering Accreditation Activities; ABET Program Evaluator His research group explores cutting-edge topics like software-defined cellular networks, distributed scheduling in underwater networks, and energy-efficient routing in sensor networks. Midkiff is affiliated with Virginia Tech’s research initiatives in pervasive computing and sustainable wireless systems.
Birsen Sirkeci is a Professor in the Department of Electrical Engineering at San Jose State University (SJSU), San Jose, CA. She holds a PhD from Cornell University (2006), an MSc from Northeastern University (2000), and a BSc from Middle East Technical University, Turkey (1998). Prior to joining SJSU, she was a postdoctoral researcher at UC Berkeley. Her educational background includes: PhD in Electrical Engineering, Cornell University, Ithaca, NY (2006) MSc in Electrical Engineering, Northeastern University, Boston, MA (2000) BSc in Electrical Engineering, Middle East Technical University, Ankara, Turkey (1998) Professor Sirkeci's research spans wireless communications , sensor networks , statistical signal processing , and machine learning . Her work focuses on developing advanced algorithms for cognitive radio networks, spectrum sensing, and cooperative communication systems. She has pioneered applications of neural networks in materials science (e.g., stress prediction in porous ceramics) and medical imaging (e.g., colon cancer detection), demonstrating exceptional interdisciplinary innovation. Analysis of her 2013-2021 publications reveals a dominant trend at the intersection of wireless communications and deep learning. Key themes include spectrum sensing via convolutional neural networks, cooperative broadcast strategies in dense networks, and physics-informed machine learning for materials engineering. Her work consistently addresses real-world constraints like channel estimation errors and hardware limitations using USRP SDRs. Her scientific contributions have been recognized with: Best Paper Awards at MILCOM 2005, WCECS 2010, and ICETEC 2013 IEEE ICME Outstanding Organizing Committee Member (2013) Applied Materials Teaching Award at SJSU (2014) As an advisor, she co-led the SJSU Spartans team to the DARPA Spectrum Challenge finals in 2013. While specific grants aren't detailed in source material, her award-winning publications and competition success indicate sustained research funding. She actively mentors students through capstone projects and competitive teams, emphasizing hands-on implementation. Professor Sirkeci leads wireless communications research within SJSU's Electrical Engineering department, with strong ties to industry through awards like Applied Materials. Her DARPA Spectrum Challenge involvement underscores leadership in translating theoretical research into competitive, real-world systems.
Dr. Liqiang Zhang is a Professor at the Department of Computer and Information Sciences, Indiana University South Bend. He holds a Ph.D. in Computer Science from Wayne State University (2005). His research focuses on wireless networks, mobile computing, resource allocation, IoT, cognitive radio networks, and network security. His work is supported by IU and the National Science Foundation. He has organized multiple conferences including ICCCN 2013 (Track Chair), GLOBECOM 2010 (Publicity Co-Chair), and founded/co-chaired WiMAN workshops. He serves as a Guest Editor for journals like ACM Transactions on Autonomous and Adaptive Systems and Elsevier's Computer Communications. He reviews for top journals including IEEE Transactions on Mobile Computing and IEEE Transactions on Parallel and Distributed Systems. Dr. Zhang teaches courses such as Computer Structures, Mobile App Development, and Network Security. Recent publications (2019-2009) include advancements in network scheduling, cognitive radio protocols, radar positioning, and digital design education. His research spans both theoretical and applied aspects of networking and distributed systems.
Muhammad Jaseemuddin is a Professor and Program Director of Computer Networks at Toronto Metropolitan University since 2002. He holds a Ph.D. from The University of Toronto (1997), an M.S. from The University of Texas at Arlington (1991), and a B.E. from N.E.D. University of Engineering & Technology, Karachi, Pakistan (1989). Research Interests: IP Networking Mobile Wireless Networks Network Automation Smart Grid Communication Internet of Things Mobile and Cloud Computing Publications Trends: His selected works (2010–2012) focus on wireless network protocols, directional antenna applications, and network performance optimization in ad hoc and mesh architectures. Academic Roles: He has contributed to network protocol design through collaborations with researchers like O. Bazan, A. Anpalagan, and others, while teaching courses in Software Systems and Computer Networks.
Wanqing Tu is an Associate Professor in Computer Science at Durham University, specializing in wireless networks and IoT systems. She serves as Editor for IEEE Internet of Things Journal and holds leadership positions in IEEE technical committees. Her research explores next-generation wireless technologies with focus areas including: Reconfigurable intelligent surfaces IoT security frameworks Multihop UAV networking Wireless protocol optimization Edge computing architectures Recent publications address critical challenges in IoT security and wireless performance optimization, particularly examining jamming detection methods and efficient resource utilization strategies. This work combines theoretical modeling with practical system implementations. Tu teaches advanced networking courses and supervises doctoral candidates in wireless communication systems. She leads international collaborations through IEEE initiatives and has organized technical committees for major conferences including IEEE MetaCom.
Saim Ghafoor is a Lecturer in the Department of Computing at Atlantic Technological University, Ireland. He holds a PhD in Engineering and Technology from University College Cork (2018), an MEng from Hanyang University (2010), and a BEng in Computer Systems Engineering from Mehran University (2005). His research focuses on advanced wireless communications, including Terahertz networks, green machine learning, and emergency communication systems. He is actively involved in the review process of top-tier journals and conferences. Education: PhD, University College Cork, 2018 MEng, Hanyang University, 2010 BEng, Mehran University, 2005 His work spans Terahertz communications , intelligent radio systems , and 5G/6G network protocols , with contributions to cybersecurity and automation. Notable outputs include a 2023 book on Green Machine Learning Protocols and a 2020 IEEE Communications Surveys review on Terahertz MAC protocols. He leads the WiSAR research group and serves as Associate Editor for Elsevier's Computers & Electrical Engineering . Grants & Labs: Active in the WiSAR (Wireless Sensor Applied Research Gateway) unit at ATU. Collaborates on projects involving THz networks and disaster response systems.
