Find Academic Supervisors

• Digital Twins
• Smart Cities
• Blockchain Technology
• +5 more

Noel Crespi is a Professor and Director of Studies at Telecom SudParis, part of Institut Polytechnique de Paris. He leads research in the NeSS group and is affiliated with SAMOVAR, a prominent research laboratory focusing on networks, systems, and services. His work spans multiple domains in telecommunications, networking, and smart systems. His primary research interests include digital twins for smart cities, blockchain technologies, Internet of Things (IoT) security and applications, 5G/6G networking, and machine learning applications in network management. He has published extensively on these topics, with over 100 publications in top-tier journals and conferences. His recent work shows a strong focus on digital twin applications for urban management, particularly in traffic and air quality monitoring. He has developed modular frameworks for smart city digital twins that integrate real-time data from multiple sources. His research also explores blockchain applications for network security, access control, and service provisioning in next-generation cellular networks. Dr. Crespi has received significant recognition for his work on digital twins, with his 2020 paper "Digital twin in the IoT context" in Proceedings of the IEEE being highly cited. His current research explores the integration of AI with digital twin technologies for sustainable urban development. He has supervised numerous PhD students and collaborates extensively with researchers across Europe and internationally. His work often involves interdisciplinary approaches, bringing together computer science, networking, urban planning, and environmental science. Dr. Crespi has been instrumental in developing frameworks for network digital twins, with applications in traffic management, air quality monitoring, and resource allocation in smart cities. His research demonstrates practical implementations in cities like Madrid, showing measurable improvements in urban management.

Florian KaltenbergerView profile

Professor

• Wireless Communications
• 5G and 6G Networks
• Massive MIMO
• +10 more

Florian Kaltenberger is a Professor in the Communication Systems department at EURECOM, a leading research institute in digital technology based in France. He actively contributes to research and teaching in wireless communications, with a focus on 5G/6G technologies, massive MIMO, and OpenAirInterface-based prototyping. Research Affiliation: EURECOM - Communication Systems Key Projects: SOLDER FP7, Newcom++, COST 2100 Professional Memberships: IEEE, reviewer for major journals and conferences His research centers on signal processing for wireless communications, MIMO systems, channel modeling, and hardware implementation. He specializes in exploiting channel reciprocity in TDD systems and developing practical testbeds for next-generation networks. Recent publications highlight a strong trend toward AI-integrated RAN, open-source 5G/6G testbeds (e.g., OpenAirInterface, X5G), UAV-aided localization, and real-time control using decentralized applications. His work bridges theoretical innovation with field deployment in programmable living labs. Award Highlights: Neal Shepherd Best Propagation Award (2013) He leads research grants under EU frameworks like FP7 and collaborates internationally on open RAN and 6G innovation. Though no formal student list is provided, his role as project lead and frequent co-authorship suggests active mentorship. He also manages EURECOM’s contributions to large-scale collaborative projects. Kaltenberger is deeply involved in lab development, particularly around OpenAirInterface, where he leads efforts in creating end-to-end, multi-vendor, private 5G O-RAN testbeds with real-time AI control and green networking capabilities.

Yasir ZakiView profile

Assistant Professor

• Communication Networks
• Wireless Networks
• Cellular Communication
• +9 more

Yasir Zaki is an Assistant Professor of Computer Science at New York University Abu Dhabi and a Global Network Assistant Professor at the Courant Institute of Mathematical Sciences, NYU. He leads the Communication Networks Lab, focusing on next-generation communication systems, performance optimization, and digital equity. University: New York University Abu Dhabi School: Courant Institute of Mathematical Sciences Department: Department of Computer Science Academic Rank: Assistant Professor Email: yz48@nyu.edu Dr. Zaki holds an MSc and PhD in Communication and Information Technology from the University of Bremen, graduating with honors. His research centers on communication and wireless networks, cellular systems, congestion control, and enhancing internet access in developing regions. His work bridges theory and real-world impact, especially in digital inclusion and AI's role in education. His recent publications span top venues like PNAS, IEEE TCSS, and ACM IMC, covering topics such as satellite network performance, digital inequality (Lite-Web), AI in education, and Big Tech's global influence. These works reveal a strong trend toward socially impactful computing, network measurement at scale, and algorithmic transparency. Big Tech Dominance Despite Global Mistrust Perception of AI in Education YouTube's Political Bias Lite-Web for Digital Equity Satellite Network Analysis His research has been recognized through high-profile media coverage in Nature and The National , and his PhD student Hazem Ibrahim received the MIT Technology Review Arabia’s Innovators Under 35 MENA 2023 award. This reflects the lab's excellence in computational social science and AI policy. Dr. Zaki mentors students in the Capstone and Research Seminar courses and actively advises PhD and research assistants. He has secured research funding through NYUAD and collaborative projects, enabling field deployments in 56 countries. His lab, the Communication Networks Lab, fosters interdisciplinary work, involving researchers from computer science, social sciences, and policy.

• Artificial Intelligence
• Machine Learning
• Federated Learning
• +7 more

Shuguang Cui is the X.Q. Deng Presidential Chair Professor in the Department of Electrical and Computer Engineering at the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen. He holds a PhD from Stanford University and has previously served on the faculties of the University of Arizona, Texas A&M University, and UC Davis. His research lies at the intersection of artificial intelligence and communication networks, particularly in AI+Networking , with major contributions in federated learning over wireless systems, intelligent reflecting surfaces, UAV trajectory optimization, and energy-efficient edge computing. His work bridges machine learning theory with practical communication system design. The recent publications reflect a strong trend toward integrating distributed AI with wireless network constraints, focusing on reducing communication overhead, optimizing resource allocation, and enhancing learning efficiency in edge environments. Key themes include federated learning convergence, hybrid VLC-RF systems, and intelligent surface-assisted communications. Award highlights include: IEEE Fellow (2013) IEEE Marconi Prize Paper Award (2023) Fellow of the Royal Society of Canada (2023) Fellow of the Canadian Academy of Engineering (2023) Multiple IEEE best paper awards (Globecom, WCNC, ICC) Thomson Reuters Highly Cited Researcher (2014) Prof. Cui has served in leadership roles such as Vice Chair of the IEEE VT Fellow Evaluation Committee, member of the IEEE ComSoc Award Committee, and currently as Editor-in-Chief of IEEE Transactions on Mobile Computing . He has secured significant research impact through high-visibility publications in top-tier journals and conferences, shaping the future of AI-driven wireless systems. He leads a research group focused on next-generation intelligent networks, supervising graduate students and collaborating across institutions. His team actively contributes to advancing the theoretical and practical foundations of AI-enabled communications.

Jie DingView profile

Associate Professor

• Artificial Intelligence
• Statistics
• Scientific Computing
• +6 more

Jie Ding is an Associate Professor at the University of Minnesota's School of Statistics with graduate faculty appointments in Electrical Engineering, Computer Science, and the Data Science Program. He serves as a core faculty member of the Data Science and AI Hub and holds an Amazon Scholar position with the Amazon AGI Team focusing on foundation model training. His educational background includes a Ph.D. in Engineering Sciences from Harvard University (2017), postdoctoral work at Duke University (2018), and a B.S. from Tsinghua University where he participated in both the Math & Physics Academic Talent Program and Electrical Engineering program. Ding's research sits at the intersection of artificial intelligence, statistics, and scientific computing, with focus areas including Agentic AI for autonomous data science workflows, AI Foundations for interpretability and trustworthiness, Scalable Modeling for broader AI accessibility, Decentralized and Collaborative AI systems, and AI Safety addressing privacy and security concerns. He developed the STAT 8931 Generative AI course with open-source materials available at genai-course.jding.org . His recent publications demonstrate strong activity across multiple AI subfields, particularly in value alignment (MAP framework), AI safety mechanisms, federated learning innovations, and statistical foundations for modern AI systems. The breadth of venues (ICML, ICLR, NeurIPS) indicates significant impact across the AI research community. NSF CAREER Award (2024) Army Early Career Program (Young Investigator) Award (2023) Cisco Research Award (2022-25) AWS Cloud Credits for Research (2021-22) Meta/Facebook Faculty Research Award (2021-22) UMN Thank-A-Teacher Teaching Award (2019-20) Ding leads the Agentic AI for Data Science Benchmark initiative, collaborating with University of Minnesota colleagues and Minnesota industry partners to evaluate AI agent capabilities across healthcare, insurance, retail, energy and other sectors. His research group actively recruits PhD students interested in AI/Statistics intersections, with focus on developing theoretically grounded yet practically impactful AI systems.

Klaus Ingemann PedersenView profile

Professor

• Wireless Communication Networks
• Dependable Wireless Communications
• 5G-Advanced Technology
• +10 more

Klaus Ingemann Pedersen is a Professor in the Department of Electronic Systems at the Technical Faculty of IT and Design, Aalborg University, Denmark. His research focuses on wireless communication networks and dependable wireless communications with substantial contributions to 5G-Advanced and 6G technologies. His research interests include: Wireless Communication Networks Dependable Wireless Communications 5G-Advanced Technology 6G Networks Radio System-Level Simulations Ultra-Reliable Low Latency Communication Heterogeneous Networks Professor Pedersen's recent work demonstrates cutting-edge research in next-generation wireless systems, with particular emphasis on deep reinforcement learning applications, link adaptation techniques, and system-level simulations. His publications show consistent high-impact output with 152 total publications spanning from 2012 to 2025, reflecting ongoing productivity and relevance in the rapidly evolving field of wireless communications. His notable achievements include: 5G-prisen (The 5G Award) received on October 23, 2019, shared with E. Mogensen and I.R. Larrad Professor Pedersen has supervised 8 PhD students according to institutional records. His research has practical applications in wireless communication, as evidenced by his involvement in patented technology 'Method and apparatus for wireless communication' which delivers social impact and quality of life improvements. His work shows strong international collaboration across multiple countries as indicated by the research network visualization.

Huubinh LeView profile

Associate Professor

• Industrial Organization
• Microeconomics
• Real Estate Economics
• +2 more

Huubinh Le serves as Associate Professor of Economics and Finance within the Economics and Finance Department at the University of South Alabama's Mitchell College of Business. His academic base is located in MCOB 312 at 5811 USA Drive South, Mobile, AL 36688. His research focuses primarily on Industrial Organization , with specialized expertise in spatial econometric applications to real estate markets. Current investigations examine infrastructure impacts on property valuation through advanced quantitative methodologies. His sole documented publication trend centers on spatial econometric analysis in real estate finance, specifically exploring wireless tower effects on home values. This work demonstrates methodological innovation in property valuation frameworks. Professor Le actively teaches ECO 315 - Intermediate Microeconomics, contributing to the department's core curriculum in economic theory. He maintains professional engagement through standard university communication channels including dedicated office hours and departmental contact information.

László LengyelView profile

Professor

• Model-Driven Engineering
• Internet of Things (IoT)
• Software Obfuscation
• +7 more

László Lengyel is a Professor at the Budapest University of Technology and Economics (BME), affiliated with the Department of Automation and Applied Informatics . His work bridges theoretical and applied computer science, focusing on industrial automation, IoT systems, and model-driven engineering. Research interests include Model transformations and domain-specific languages IoT device management and multi-domain integration Software obfuscation and cybersecurity Graph algorithms and distributed computing (MapReduce) Real-time data analysis in manufacturing Automotive sensor networks His recent publications reflect expertise in model-driven IoT architectures , granule manufacturing automation , and MapReduce-based graph analysis , with a focus on industrial and automotive applications. He contributes to open-source frameworks like SensorHUB and explores gamification in driver behavior systems.

Iain John BateView profile

Lecturer

• Scheduling and Timing Analysis
• Real-Time Systems
• Systems Engineering
• +4 more

Iain Bate is a Lecturer in Real-Time Systems and Head of the Department of Computer Science at the University of York. His research focuses on scheduling and timing analysis, systems engineering with optimization of design trade-offs, design assurance, component-based engineering, and managing emergent behavior, particularly in critical systems. University of York, Department of Computer Science Research areas: Real-Time Systems, Mixed-Criticality Scheduling, Multi-Core Architecture Departmental Roles: Head of Department, Research Group Lead (Real-Time Systems) His recent research explores cache-aware scheduling, fault tolerance, and resource stress management in multi-core environments. He has contributed to journals like Microprocessors and Microsystems as an editor and collaborated on projects funded by EPSRC and industry partners such as Rolls Royce. He actively supervises PhD students and leads research initiatives related to wireless sensor networks, task allocation, and system certification for critical applications.

Alan BovikView profile

Professor

• Image and Video Processing
• Digital Television
• Digital Cinema
• +5 more

Alan Bovik is a Professor at The University of Texas at Austin, holding the prestigious Cockrell Family Endowed Regents Chair in Engineering. He serves as Director of the Laboratory for Image and Video Engineering (LIVE) and maintains dual faculty appointments in the Department of Electrical and Computer Engineering and the Institute for Neuroscience. His extensive contributions have established him as a leading authority in visual information processing with global impact. Dr. Bovik's research spans multiple domains with a primary focus on image and video processing, digital television and digital cinema, computational vision, and visual perception. His work has fundamentally advanced the understanding of human visual perception, leading to practical applications in video quality assessment and image processing systems. With over 800 technical publications cited more than 75,000 times and an H-index above 100, his research has had extraordinary impact across academia and industry. He is recognized as a Highly-Cited Researcher by Clarivate Analytics, placing him among the most influential researchers globally. Analysis of Dr. Bovik's recent publications reveals a strong emphasis on video quality assessment for emerging applications like user-generated content, high-motion streaming, and adaptive video delivery. His work seamlessly integrates deep learning approaches with traditional signal processing techniques to develop perceptually accurate models. There's a clear trend toward addressing practical challenges in video streaming quality, compression artifacts, and the unique characteristics of modern video content. His research bridges theoretical foundations with real-world applications, making significant contributions to both academic understanding and industry standards. Dr. Bovik's exceptional contributions have been recognized with numerous prestigious awards: IEEE Fourier Award (2019) for seminal contributions to perception-based image and video processing Edwin H. Land Medal (2017) from The Optical Society Primetime Emmy Award for Outstanding Achievement in Engineering Development (2015) Norbert Wiener Society Award (2013) Claude Shannon / Harry Nyquist Technical Achievement Award (2005) Multiple best paper awards from IEEE, EURASIP, and Picture Coding Symposium As an educator and mentor, Dr. Bovik has guided numerous students through his leadership at LIVE. His professional service includes founding and serving as Editor-in-Chief of the IEEE Transactions on Image Processing (1996-2002) and chairing the inaugural IEEE International Conference on Image Processing in 1994. His industry impact is substantial, evidenced by his Primetime Emmy Award and frequent consultation with major institutions. Dr. Bovik is also a registered Professional Engineer in Texas, demonstrating his practical engineering expertise alongside theoretical contributions. Dr. Bovik leads the Laboratory for Image and Video Engineering (LIVE), which maintains strong affiliations with multiple research centers including the Wireless Networking and Communications Group (WNCG), Center for Perceptual Systems, Telecommunications and Signal Processing Research Center, and Institute for Computational Engineering and Sciences. These interdisciplinary connections enable research that bridges engineering, neuroscience, and computer science to advance our understanding of visual perception and processing.

Tuğçe BilenView profile

Assistant Professor

• Artificial Intelligence
• Computer and Communication Networks
• Digital Twin
• +4 more

Tuğçe Bilen is an Assistant Professor at Istanbul Technical University's Department of Artificial Intelligence and Data Engineering, within the School of Computer and Informatics. Her research focuses on Artificial Intelligence and Computer and Communication Networks, particularly Digital Twin technologies, 6G wireless systems, and smart IoT applications. PhD in Computer Engineering (2017-2022), Istanbul Technical University Master's in Computer Engineering (2016-2017), Istanbul Technical University Licence in Computer Engineering (2010-2015), Istanbul Technical University Her research explores Digital Twin middleware for smart farms, energy-aware task scheduling in 6G edge networks, aeronautical ad-hoc network optimization, and cloud-based protocol enhancements. Recent work addresses metaverse-driven supply chain optimization and secure routing for aircraft networks. Key publication trends show strong focus on: Digital Twin integration across domains 6G wireless network architectures Adaptive routing algorithms Energy-efficient IoT systems Security in airborne communication Machine Learning for network management Scientific recognition includes: Serhat Özyar Young Scientist of the Year Honorary Award (2023) Doctoral Thesis Award from Istanbul Technical University (2023) TÜBA Doctoral Science Awards-Teknofest (2023) She serves as Principal Investigator for the Unsupervised Learning-Based Management of Ad Hoc Airborne Network Topology project (2024-2026) and holds a patent for Parametric Parsing Based Routing System in Content Delivery Networks (2021). As IEEE member since 2015, she contributes to telecommunications standards.

Manuel Jesus Espinosa GaviraView profile

Researcher

• Power Quality Analysis
• Wireless Sensor Networks
• Smart Grid Technologies
• +3 more

Manuel Jesus Espinosa Gavira is a researcher at the Department of Automation, Electronics, Architecture and Computer Networks Engineering at the University of Cádiz, Spain. He is affiliated with the TIC168 Computational Instrumentation and Industrial Electronics research group under the Information and Communication Technologies PAIDI area. Research Focus: His work centers on power quality analysis, wireless sensor networks, and smart grid technologies. Key contributions include developing instrumentation systems for voltage supply characterization, cloud-induced photovoltaic transient analysis, and synchronized sensor networks for industrial applications. His PhD thesis (2023) explored sensor networks for short-term solar prediction in microgrids and smart cities. Publications Trends: Recent work focuses on higher-order statistics (HOS) for power quality monitoring, photovoltaic plant optimization using weather forecasts, and frequency domain analysis for grid stability. These publications reflect expertise in computational instrumentation, renewable energy integration, and real-time monitoring systems.

• Internet of Things (IoT)
• Machine Learning
• Smart Agriculture
• +9 more

Laura Belli is a Researcher at the Department of Engineering and Architecture , University of Parma, with a focus on interdisciplinary projects bridging IoT, Machine Learning, and Smart Systems . Her work spans smart agriculture, vehicular networks, and urban mobility. Research Interests: Internet of Things (IoT) in agriculture and transportation Machine Learning for predictive modeling and data analysis Edge Computing and network optimization Blockchain applications in data integrity Driver health and stress monitoring Recent Publications highlight her contributions to privacy-preserving vehicular systems , smart farming datasets , and adaptive IoT protocols . She collaborates on projects like OPEVA and DistriMuse , emphasizing data-driven innovation.

Ahmed AhmedView profile

Associate Professor

• Computer Science
• Artificial Intelligence
• Machine Learning
• +5 more

Ahmed Ahmed, an associate professor in the Department of Computer Science at Prairie View A&M University (PVAMU) , shapes tech leaders through innovative teaching and research. His work spans IoT, AI, and ML applications across agriculture, infrastructure monitoring, and healthcare. Key research areas include: IoT and AI for sustainable agricultural practices LoRa-based location tracking in constrained environments Secure blockchain-federated learning systems Geofencing for community safety With over 50 peer-reviewed publications and a $300k NSF grant (2023), Ahmed develops hands-on learning tools like a Special Interest Group for IoT and live programming demonstrations. His global journey—from Cairo University to a PhD at the University of Saskatchewan—fuels his commitment to empowering underrepresented students. Scientific awards include the PVAMU Faculty Service Award . He advises students like Kritika Singh (2022 graduate) and advocates for continuous refinement of teaching as a craft.

• Computer Security
• 5G Networks
• Privacy Preservation
• +6 more

Philip Ginzboorg is a Professor of Practice at the Department of Computer Science, Aalto University. His research focuses on advanced security and privacy challenges in modern networking systems, with a particular emphasis on 5G, edge computing, and disruption-tolerant networks. His recent work explores AKMA (Authentication and Key Management for Access) protocols for secure mobility in 5G edge computing environments, privacy-preserving authentication mechanisms , and fragmentation algorithms for disrupted links . Collaborations with Valtteri Niemi, Jörg Ott, and other researchers highlight his interdisciplinary approach. Key publication trends span 5G security , privacy in pervasive networks , DTN (Disruption-Tolerant Networking) , and cryptographic protocols for constrained systems . Notable contributions include defenses against downgrade attacks on identity privacy and novel approaches to IMSI-based routing.