Find Academic Supervisors

Xuefu ZhouView profile

Associate Professor

• Deep Learning
• Wireless Communications and Networking
• Internet of Things (IoT)
• +4 more

Xuefu Zhou is an Associate Professor in the Department of Electrical Engineering at the University of Cincinnati, where he joined as an Assistant Professor in 2005 and was promoted in 2010. He holds an M.S. and Ph.D. in Electrical Engineering from the same university. Prior to academia, he worked in industry from 1995 to 2000 as an R&D Engineer, Senior Engineer, and Project Manager, specializing in distributed computer control systems and real-time embedded systems. His research interests span Deep Learning, Wireless Communications, IoT, Biomedical Signal Processing (e.g., ECG analysis), and Non-Destructive Evaluation. He directs the Wireless and Mobile Communication Lab (WMCL) and oversees the Master of Engineering (MENG) Graduate Program. Zhou has received notable awards including the 2011 and 2012 William E. Restemeyer Teaching Excellence Award, and the 2013 and 2018 CEAS Master Educator Award. He is a Senior Member of IEEE. He has led or collaborated on grants totaling over $1M, focusing on topics like ECG screening for cardiomyopathy, smart transportation systems, and edge AI classifiers. Recent projects include collaborations with Procter & Gamble, Medical Interface Solutions, and the Federal Highway Administration.

Giulia MichielettoView profile

Assistant Professor

• Multi-agent Systems
• Aerial Robotics
• Control Theory
• +4 more

Giulia Michieletto serves as an Assistant Professor (RTD-A) at the Department of Management and Engineering, University of Padova, where she leads research in networked control systems and multi-agent robotics. She is a core member of the SPARCS research team and holds the position of publicity and dissemination lead for the IEEE Robotics and Automation Society's Technical Committee on Multi-Robot Systems. Her academic foundation includes a Laurea Degree in Automation Engineering (2014) and a Ph.D. in Information Engineering (2018), both from the University of Padova, supplemented by a Visiting Researcher appointment at LAAS-CNRS (2016-2017) funded by the Eiffel Scholarship Program. Michieletto's research centers on multi-agent system modeling with specialized focus on aerial vehicle formations and nanosatellite coordination . She pioneers thrust-vectoring aerial platform design for enhanced environmental interaction, while advancing theoretical frameworks in bearing rigidity theory. Her work spans wireless sensor networks for environmental monitoring, multi-camera systems for cooperative tracking, and ground robotics for autonomous manipulation, addressing critical challenges in robustness, security, and distributed control. Analysis of her publication trajectory reveals deep integration of bearing rigidity theory with practical aerial robotics applications, evolving toward cybersecurity-enhanced navigation and distributed estimation for sensor networks. Recent work demonstrates increasing sophistication in handling GNSS spoofing attacks, multi-robot formation control under disturbances, and real-time surveillance systems. Her scientific recognition includes: Eiffel Scholarship Program of Excellence (2016) Finalist for IEEE RAS Italian Chapter Fabrizio Flacco Young Author Best Paper Award (2019) As an active educator, Michieletto supervises master's theses on contact-aware aerial robotics and mobile manipulation while securing research leadership as Principal Investigator for the Contact-Aware Robotics (CAR) project and co-PI for formation control research. Her grant portfolio spans national initiatives including TSTARK and INTERACT, plus EU H2020's AEROARMS, frequently as fellowship recipient. She drives innovation within the SPARCS research ecosystem, focusing on networked control solutions for complex robotic systems operating in constrained environments.

Torsten BraunView profile

Professor

• Machine Learning
• Networking and Telecommunications
• Edge Computing
• +3 more

Prof. Torsten Braun is a Professor and Head of the Communication and Distributed Systems (CDS) research group at the Institute of Computer Science, University of Bern. His research focuses on advanced networking technologies, edge computing, and machine learning applications in telecommunications. He leads projects addressing challenges in 5G/6G networks, federated learning optimization, and intelligent systems for smart cities. His work integrates theoretical frameworks with practical implementations, emphasizing distributed systems, service-oriented architectures, and IoT security. Key research areas include edge caching strategies for VR/AR applications, trajectory prediction using reinforcement learning, and resilient network design against jamming attacks. Braun has contributed to innovations in vehicular networks (V2X), RAN intelligence, and decentralized machine learning frameworks. He holds leadership roles in developing adaptive resource management systems for edge-cloud environments and has pioneered solutions for energy-efficient federated learning in heterogeneous IoT ecosystems. Publications span topics like spatial-temporal point cloud sensing, mobility-aware service orchestration, and secure positioning systems. His team explores cross-disciplinary applications such as LoRaWAN-based urban heat monitoring and blockchain-inspired public key infrastructures for IoT (Veritaa-IoT). Braun actively engages in standardization and industry collaborations to advance next-generation network architectures.

Jay AikatView profile

Research Professor

• Computer Networking
• Data Science Education
• Cloud Computing Security
• +3 more

Jay Aikat is the Vice Dean of the School of Data Science and Society at the University of North Carolina at Chapel Hill since July 2022, and a Research Professor in the Department of Computer Science. She previously served as Chief Operating Officer at RENCI (2016–2022) and held leadership roles in IT at UNC-Chapel Hill’s School of Information and Library Science. Aikat holds a Ph.D. in Computer Science from UNC-Chapel Hill, with earlier degrees in Electrical and Electronics Engineering and Computer Science. Her research focuses on experimental methods in networking, Internet traffic modeling, cloud security, and data science education. Notable contributions include work on airborne network topology management, cloud computing security frameworks, and pedagogical innovations in big data training. She has collaborated with institutions like NIEHS (National Institute of Environmental Health Sciences) and contributed to national-scale research infrastructure projects through GENI and COMBINE initiatives. Her publication trends reflect deep engagement with network experimentation, cybersecurity challenges in cloud environments, and scalable solutions for dynamic wireless systems. Aikat has also authored foundational work on web traffic evolution and protocol benchmarking, emphasizing reproducible methodologies in networking research. Her professional trajectory includes bridging academic research with applied IT leadership, fostering interdisciplinary collaborations across computer science, environmental health, and data science domains. Current efforts focus on expanding data science education and driving innovation through the School of Data Science and Society.

Trang CaoView profile

Research Fellow

• Magnetic Resonance Imaging (MRI)
• Neuroimaging
• Computational Neuroscience
• +5 more

Dr. Trang Cao is a Research Fellow at the School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Australia. She completed her PhD in Engineering (2020), M.Eng in Electronics and Radio Engineering (2015), and B.Eng in Electronics and Telecommunications (2012) from the University of Melbourne, Kyung Hee University, and Posts and Telecommunications Institute of Technology (Vietnam), respectively. PhD in Engineering (2020) - University of Melbourne M.Eng in Electronics and Radio Engineering (2015) - Kyung Hee University B.Eng in Electronics and Telecommunications (2012) - Posts and Telecommunications Institute of Technology Her research focuses on neuroimaging and molecular communication , particularly on understanding brain anatomy and function using MRI and designing molecular communication systems for biomedical applications. She integrates computational neuroscience with signal processing to derive functional biomarkers in neurodegenerative diseases like Friedreich Ataxia. Recent publications highlight trends in neuroimaging techniques (e.g., mode-based morphometry for brain mapping) and molecular communication optimization (e.g., chemical detection mechanisms, equalization techniques). Her work bridges neuroscience and engineering to address both theoretical and applied challenges. Scientific Awards: Best Poster Award (2019) Diane Lemaire Scholarship (2018) Student Travel Grant (2019) She contributes to peer review for journals like IEEE Transactions on Network Science and Engineering and conferences such as the Organization for Human Brain Mapping (OHBM) . Current projects include deriving fMRI biomarkers for Friedreich Ataxia using structural MRI data alone.

Chamitha De AlwisView profile

Senior Lecturer

• AI Security
• Cybersecurity
• Network Security
• +5 more

Dr. Chamitha De Alwis is a Senior Lecturer in the School of Computer Science & Technology at the University of Bedfordshire, within the Faculty of Creative Arts, Technologies & Science. He holds a B.Sc. (First Class Honors) in Electronic and Telecommunication Engineering from the University of Moratuwa, Sri Lanka, and a Ph.D. in Electronic Engineering from the University of Surrey, UK. He is a Senior Member of the IEEE and a Fellow of the Higher Education Academy. Research Interests: Dr. De Alwis focuses on AI Security, Cybersecurity, Network Security, 5G/6G technologies, Blockchain, and Edge Computing. His work spans cutting-edge areas such as quantum technologies for next-gen networks, smart grid security, and healthcare applications of edge computing. He has secured competitive research grants and contributes to high-impact projects in collaboration with industry and academia. Teaching Areas: Cybersecurity, Network Security, and Mobile Communication. He actively supervises PhD students in these domains, including Mr. Mohammad Ahmad, Mr. Ahmad Kanbour, and Ms. Charithri Nanayakkara. Publications: His recent work explores Edge AI, 6G architectures, blockchain in energy systems, and eHealthcare innovations. Notable trends include integrating AI with edge computing for real-time applications and addressing security challenges in 6G networks. Awards/Honors: Fellow of the Higher Education Academy (2024) Senior Member, IEEE (2021) Grants & Collaborations: Secured multiple research grants supporting projects in Edge Computing, 6G technologies, and Smart Grid applications. Engaged with interdisciplinary teams in the Institute for Research in Applicable Computing (IRAC) and the Institute for Research in Engineering and Sustainable Environment (IRESE). Labs & Teams: Affiliated with the School’s research institutes, contributing to initiatives in robotics, AI, and sustainable engineering. Involved in collaborative projects with industry partners to advance edge computing and cybersecurity solutions.

Senem VelipasalarView profile

Professor

• Machine Learning
• Computer Vision
• Wireless Smart Camera Networks
• +8 more

Senem Velipasalar is a Professor in the Department of Electrical Engineering and Computer Science (EECS) at Syracuse University, affiliated with the Smart Vision Systems Laboratory and the Aging Studies Institute. She holds a Ph.D. and M.A. from Princeton University, an M.S. from Brown University, and a B.S. from Bogazici University. Her research focuses on machine learning, computer vision, and wireless smart camera systems, with applications in human activity classification, driver behavior analysis, and defense against adversarial attacks. Her honors include the NSF CAREER Award (2011), 2021 IEEE Technological Innovation Award, and multiple doctoral prizes for her advisees. She leads grants totaling over $4M, including ARPA-E projects on occupancy detection and DOE-funded research on aerial energy modeling. Research interests span embedded vision, distributed multi-camera tracking, and energy-efficient algorithms. Her lab develops technologies like wearable camera-based fall detection and autonomous UAV navigation. Notable publications include works on adversarial attacks, fNIRS brain activity analysis, and thermal pedestrian detection.

Waylon BrunetteView profile

Assistant Professor

• Mobile Computing
• Computing for Development
• Ubiquitous Computing
• +5 more

Waylon Brunette is an Assistant Professor in the Department of Computer & Cyber Sciences at Augusta University. His research focuses on mobile computing, computing for development, ubiquitous computing, and edge computing, with an emphasis on creating systems that integrate seamlessly into users' environments to support global health and humanitarian efforts in resource-constrained settings. He leads the development of the Open Data Kit (ODK) framework, designed to simplify mobile application development for disconnected environments. Education: Ph.D. (Computer Science, University of Washington, 2020), MS (Computer Science, UW, 2012), BSE (Computer Engineering, UW, 2002). Research interests include wireless sensor networks, sensor-enhanced systems, and frameworks for non-programmers to deploy robust applications in low-resource areas. He serves as Chair of the Research Computing Infrastructure Committee (RCIC) and Editor for the ACM Journal on Computing and Sustainable Societies. Previously, he was a co-founder of the ODK Project at UW's Allen School. Service activities include mentoring junior researchers and organizing the Southeastern Collegiate Penetration Testing Competition. His work emphasizes practical, deployable solutions for global challenges in healthcare, logistics, and international development.

• Distributed Systems
• Cybersecurity
• Data Privacy
• +6 more

Ashiq Anjum is a Professor of Distributed Systems at the College of Science and Engineering. His research focuses on cybersecurity, privacy-preserving technologies, blockchain applications, machine learning, and IoT systems. He has contributed to advancements in distributed systems, vehicular networks (VANETs), smart grids, and federated learning frameworks. His work emphasizes integrating blockchain for secure data aggregation and leveraging AI techniques for data interpretation and privacy protection. Key research areas include secure communication in drone networks, privacy in vehicular systems using IOTA ledgers, and federated learning with differential privacy. He explores graph models for genomic data analysis and healthcare applications. His publications span journals like Elsevier Information Sciences , Future Generation Computer Systems , and Neurocomputing . Collaborations include projects on data imputation for environmental sensing, deep learning pipelines in cloud computing, and optimizing video analytics for smart cities. His work bridges theoretical computer science with practical applications in IoT, healthcare, and urban sustainability.

Renuka MohanrajView profile

Assistant Professor

• Mobile Ad Hoc Networks
• Design and Analysis of Algorithms
• Software Engineering
• +2 more

Renuka Mohanraj is an Assistant Professor of Computer Science specializing in Mobile Ad Hoc Networks (MANET), with research interests in Design and Analysis of Algorithms, Software Engineering, Web Technology, and Wireless Application Protocol. She holds a PhD from Mother Teresa University and has contributed significantly to network security and optimization through her publications and a book. Education includes: BSc, Madras University MCA, Bharathidasan University MPhil, Periyar University PhD, Mother Teresa University Her research focuses on enhancing security and efficiency in MANET through innovative routing protocols and collision control mechanisms. Recent work extends to IoT and healthcare applications, addressing challenges like secure data transmission and energy efficiency. Earlier contributions centered on MANET’s reliability and multi-path data integrity. No scientific awards or grants are listed. No advisees or lab affiliations are mentioned in the provided information.

• Wireless Communications
• Internet of Things (IoT)
• Edge Computing
• +7 more

Zheng Chang is a Professor at the Institute of Computing Technology, School of Computer Science and Technology, University of Chinese Academy of Sciences in Beijing, China. With a PhD from the University of Jyväskylä (2013), Chang has established a prolific research career with over 240 publications spanning from 2011 to 2025. Chang maintains strong collaborative ties with researchers at the Chinese Academy of Sciences' Shenyang Institute of Automation and has developed significant international collaborations, particularly with Finnish researchers including Timo Hämäläinen. Chang's research focuses on cutting-edge areas at the intersection of wireless communications, artificial intelligence, and edge computing. Their work prominently features federated learning, UAV networks, resource allocation, and privacy-preserving techniques for IoT applications. Recent publications demonstrate a strong emphasis on vehicular edge intelligence, split learning architectures, and RIS-assisted communications. The research output shows consistent growth with 42 publications in 2024 alone, indicating an active and expanding research program. Chang's 15 most recent publications reveal a clear research trajectory toward addressing the challenges of resource-constrained edge environments through innovative learning architectures. The work spans theoretical frameworks for privacy preservation in federated learning to practical implementations for UAV networks and vehicular systems. A notable trend is the integration of AI-generated content techniques with traditional federated learning approaches to overcome data scarcity issues in edge environments. While specific awards aren't documented in the provided text, Chang's extensive publication record in top-tier IEEE journals including IEEE Transactions on Wireless Communications, IEEE Internet of Things Journal, and IEEE Transactions on Vehicular Technology demonstrates significant scholarly impact. The research has been widely cited, with multiple highly cited co-authors including Timo Hämäläinen (66 co-authored papers), Zhu Han (38 papers), and Geyong Min (31 papers). Chang's work shows strong practical applications across multiple domains including intelligent transportation systems, smart agriculture, healthcare IoT, and next-generation 6G networks. The research program appears well-funded through collaborations with major institutions and demonstrates clear translational potential for real-world deployment in edge computing environments.

Alfa NyandoroView profile

Associate Professor

• Wireless Network Protocols
• Medium Access Control (MAC) Protocols
• Technology for Development
• +3 more

Dr. Alfa Nyandoro is an Associate Professor of Computer Science and IT at Lipscomb University, Nashville, Tennessee, where he recently served as Interim Associate Dean of the College of Computing & Technology and Chair of the Information Technologies Department. With a 22+ year career spanning Zimbabwe, South Africa, Australia, and the United States, he has held roles in academia (University of Johannesburg, Abilene Christian University) and industry (Diamond Insurance, Anglo American Corporation). His research focuses on wireless network protocols, technology for development, and healthcare informatics. Education: Ph.D. in Computer Science (details not specified) 1st Class Honors B.Sc. Computer Science, National University of Science and Technology (Zimbabwe, 1996) NUST Vice-Chancellor’s Book Prize for Computer Science (1996) Research Interests: Medium Access Control (MAC) protocols in wireless networks Applications of technology for socio-economic development Healthcare informatics systems Networking infrastructure optimization Awards: Dean’s Award for Excellence (2019-20) Teacher of the Year (2012-13) UIPRS Scholarship (2001-05) Professional Affiliations: Member of IEEE and ACM. Prior roles include tenure at Abilene Christian University and senior research positions at SIRDC (Zimbabwe) and NICTA/UNSW (Australia).

• Social Network Analysis
• Artificial Intelligence
• Knowledge Graphs
• +4 more

Irene Kilanioti is a Teaching Professor at the National Technical University of Athens (NTUA), affiliated with the Division of Communication, Electronic and Information Engineering under the School of Electrical and Computer Engineering. She holds a Ph.D. in Computer Science from the University of Cyprus and has extensive experience as a PostDoc researcher at Ludwig-Maximilians-Universität München. Her career includes roles as an informatics teacher in Greece and Germany, software engineer at Vodafone, and teaching assistant in tertiary education. Dr. Kilanioti specializes in knowledge graphs, social media analytics, sustainable development goals, and AI-driven education technologies. Education: B.Sc. in Informatics and Telecommunications (NKUA), M.Sc. in Advanced Information Systems (NKUA with best student award), Ph.D. in Computer Science (University of Cyprus). She completed German teaching licensure studies at Friedrich-Alexander-Universität (Erlangen) and holds a translator’s diploma from the Institute of Linguists (London). Fluent in English and German, she is a member of the Cyprus Scientific and Technical Chamber. Research focuses on knowledge graph optimization, social media misinformation detection, and IoT applications in transportation. Notable achievements include the Best Paper Award at the 2022 IEEE International Conference on Knowledge Graphs and contributions to IEEE/UL Standard 2933™ for Clinical IoT Interoperability. She co-leads the EU-funded cHiPSet initiative for big data simulation and serves as an editor for Frontiers in Digital Education. Awards include a Greek State Scholarship Foundation PhD grant (2012-2015) and the Best Student Award for her M.Sc. Her work bridges technical innovation with societal impact, spanning education technology, healthcare IoT, and global sustainable development.

Razvan StanicaView profile

Associate Professor

• Wireless Networking
• Cellular Networks
• Energy Efficiency
• +6 more

Razvan Stanica is an Associate Professor at the Telecommunications department of INSA Lyon and a member of the CITI laboratory and Inria Agora team. His research focuses on wireless networks, cellular architectures, energy efficiency, and mobile data analytics. He holds a PhD from the National Polytechnic Institute of Toulouse and has supervised numerous PhD and master's students in areas like vehicular networks and IoT. Education: Bachelor's and Master's from Politehnica University of Bucharest and National Polytechnic Institute of Toulouse (2008) PhD in Vehicular Networks from National Polytechnic Institute of Toulouse (2011) Research Interests: 5G/6G cellular networks, IoT, and energy-efficient designs Mobile data analytics and urban mobility modeling Vehicular networks (VANETs) and disaster communication systems Network slicing and privacy-preserving technologies Awards: Recognized as one of France's best junior researchers in computer networks (2021). His PhD was nominated for the Léopold Escande Prize (2011). Key Projects: ECOMOME (CHIST-ERA-funded project on energy consumption in cellular networks) SafeCityMap (Inria-funded pandemic mobility analysis) PEPR NAI (self-deployable mobile networks) Labs/Teams: CITI Lab and Inria Agora team at INSA Lyon, collaborating with institutions like ETS Montreal and Nokia Bell Labs.

Andrea DettiView profile

Professor

• Computer Networks
• Information-Centric Networking (ICN)
• Cloud Computing
• +3 more

Andrea Detti is a Professor at the Department of Electronic Engineering, University of Rome Tor Vergata. His research focuses on computer networks, particularly Information-Centric Networking (ICN), Cloud Computing, and Software Defined Networks (SDN). He has coordinated major EU projects like Fed4IoT and BONVOYAGE, addressing IoT and Intelligent Transport Systems. He serves as Associate Editor for IEEE Transaction on Network and Service Management and has guest-edited special issues on ICN. His teaching includes courses on Internet Technologies, Mobile Wireless Networks, and Cloud Computing, emphasizing hands-on labs with Linux, Cisco routers, and OpenStack. Key projects include leadership roles in EU initiatives such as ICN2020, GreenICN (energy-efficient ICN), and OFELIA (ICN over SDN). He coordinates industrial projects with Telecom Italia and SSI/Finmeccanica on publish-subscribe paradigms in MANET and DTN. His research spans ICN scalability, adaptive video streaming, and satellite communication optimizations. Publications (80+) cover ICN architecture, SDN integration, and network performance modeling. He actively participates in conferences and standardization efforts, contributing to the evolution of future Internet architectures.