Find Academic Supervisors

• Machine Learning
• Big Data
• Knowledge Discovery
• +7 more

Dr. Borja Sanz Urquijo serves as a Senior Lecturer at the Faculty of Engineering, University of Deusto, and has been a core researcher at DeustoTech-Computing since 2008, including a tenure as Head Researcher (2015-2018). He holds a cum laude PhD in Information Systems (2012) from the University of Deusto, specializing in Android malware detection. Education PhD in Information Systems, University of Deusto (2012, cum laude) His research spans machine learning, big data, and knowledge discovery, with critical expansion into AI ethics, fairness, accountability, and societal impact. He investigates AI applications in domestic violence intervention, health rights, law enforcement transparency, and Edge Computing optimization, consistently bridging technical innovation with social responsibility. His work demonstrates rigorous methodology in small-dataset machine learning and genomic sequence analysis. Dr. Sanz Urquijo's publication trajectory reveals evolving expertise from foundational cybersecurity (Android malware analysis, spam filtering) to contemporary societal challenges (feminist AI frameworks, quantum software security). Recent articles emphasize interdisciplinary collaboration, particularly in feminist technology studies and ethical AI governance, while maintaining technical depth in Edge Computing and genomic analytics. Advising and Projects He has supervised multiple theses including doctoral work on Edge Computing for digital twins and cybersecurity competency frameworks. As lead researcher in over 50 projects (H2020, national, private), he currently directs BEACON (industrial AI systems) and contributes to EU initiatives like IMPROVE (domestic violence response) and ELKARTEK (Industry 5.0 ethics). His collaborations span social organizations, enterprises, and research centers globally. Research Environment As a pillar of DeustoTech-Computing, he operates within a multidisciplinary unit advancing AI, cybersecurity, and Edge Computing applications. His leadership in projects like AI-Driven Cognitive Robotic Platforms and REal tiME control systems demonstrates integration of theoretical research with industrial implementation in smart manufacturing contexts.

• Algorithm design and analysis
• Cellular networks
• Connected cars
• +11 more

Carla Fabiana Chiasserini is a Full Professor and Deputy Director at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin. She serves as a Component of the CARS@PoliTO Interdepartmental Center - Center for Automotive Research and Sustainable Mobility and acts as a Spoke leader for research and innovation activities. Her academic career spans multiple prestigious institutions and she maintains active collaborations worldwide. Professor Chiasserini's research interests span algorithm design and analysis, cellular networks, connected cars, edge computing, heterogeneous wireless networks, Internet of Things, machine learning, mobile networks, mobile services, and performance evaluation. Her work bridges theoretical algorithm development with practical applications in next-generation telecommunications systems. She leads the TNG research group at DET and focuses on Machine Learning for Networking, with specific research lines in Network Slicing in 5G, Connected autonomous cars, and Opinion dynamics in social networks. Her research aligns with Sustainable Development Goals including Industry, Innovation and Infrastructure; Sustainable Cities and Communities; and Climate Action. Her recent publications demonstrate a strong trend toward integrating machine learning with edge computing, 5G/6G systems, and automotive applications. The research spans from theoretical algorithm development to practical implementations for XR offloading, distributed service provisioning, reliability assessment of AI-based automotive systems, and satellite networking. Her work shows increasing focus on practical implementations with industry applications, particularly in the automotive sector and next-generation telecom infrastructure. Best Paper Award - Wireless Telecommunications Symposium (WTS) 2018 Best Paper Award - IEEE WoWMoM 2016 Best Paper Award Runner-up at ACM MSWiM 2016 Top Paper Award at the ACM CoNEXT 2016 Cloud-Assisted Networking (CAN) Workshop Best Paper Award at SPACOMM 2014 Best Paper Award at AD HOC NOW 2014 2010 Editor of the Year Award for the Ad Hoc Networks journal (Elsevier) IEEE Fellow (2018-) ACM Fellow (2024-) Professor Chiasserini actively advises numerous PhD students working on cutting-edge topics in network systems, with recent graduates focusing on edge services in 5G networks, resource-aware learning in mobile networks, and deployment of microservices at the network edge. She leads multiple significant research grants including O-RAN (2024-2027), CSI-Future (2023-2025), RESTART - Spoke 4 (2023-2025), PREDICT-6G (2023-2025), and several others funded by PNRR, EU Horizon programs, and industry partnerships. Her work has substantial practical impact through numerous patents including OffloaDNN and SEM-O-RAN. She leads the TNG research group within the Department of Electronics and Telecommunications and participates in the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. Her laboratory work focuses on practical implementations of theoretical concepts, particularly in the areas of connected vehicles, edge computing, and 5G/6G systems. She maintains strong industry connections through projects with Intel Corporation and other technology partners, ensuring her research has direct real-world applications.

• Cybersecurity
• Privacy
• IoT Privacy
• +5 more

Ali Padyab is a Senior Lecturer in the Department of Information Technology at the School of Informatics, University of Skövde. He serves as program coordinator for the Master's program in Privacy, Information, and Cybersecurity and leads research projects on cybersecurity economic models (funded by MSB) and socio-economic determinants of cybercrime (funded by VR). His research spans privacy, cybersecurity, IoT privacy, information security management, cloud risk assessment, remote work security challenges, and AI-driven cyber threat intelligence. Key projects include IoTLab, Mobile Shield, USEMP, Privacy Flag, U4IoT, and UNALAB. 2012-2015: TG4NP 2014-2015: IoTLab 2014-2017: USEMP 2015-2018: Privacy Flag 2018-2020: UNALAB 2023-2025: Cybercrime study 2024-2029: Cybersecurity Economic Models His publications analyze cybersecurity challenges in contact tracing systems, IoT privacy, blockchain security, and AI applications in threat intelligence. Current projects focus on socio-economic factors in cybercrime and economic models for cybersecurity adoption.

• Wireless Communications
• Mathematics
• Artificial Intelligence
• +5 more

Keivan Navaie is a Professor of Intelligent Networks at Lancaster University’s School of Computing and Communications. He serves as a member of the Independent Scientific Advisory Committee at the Alan Turing Institute, overseeing the £100 million BridgeAI programme, and previously as Principal AI Technology Advisor to the UK Information Commissioner’s Office (ICO). He is recognized with Fellowships from the Institution of Engineering and Technology (IET), Chartered Engineer status in the UK, Senior Fellowship of the Higher Education Academy (HEA), and the IEEE Young Investigator Award. Research Focus: Wireless communications, mathematics, artificial intelligence, 6G networks, blockchain technology, edge computing, cognitive radio networks, and non-orthogonal multiple access (NOMA). Supervision: Actively supervises PhD students in areas like wireless communications and mathematical modeling. Projects: Involved in distributed learning, blockchain integration, 6G research, and spectrum sharing systems. Awards: IEEE Young Investigator Award, Fellow of IET, Chartered Engineer, Senior Fellow of HEA.

Pradip K SrimaniView profile

Professor

• Parallel and Distributed Computing
• Interconnection Networks
• Self-Stabilizing Systems
• +2 more

Pradip K Srimani is a Professor at the School of Computing , Clemson University , with research focus on Parallel and Distributed Computing , Self-Stabilizing Systems , and Graph Theory Applications . He is an IEEE Life Fellow and ACM Distinguished Scientist with over 250 publications. Research Interests Self-stabilizing algorithms for network graphs Ontology-based biomedical information retrieval High-performance computing resource management Biologically inspired distributed algorithms Network topology computation Recent publications demonstrate expertise in token circulation protocols, genome assembly frameworks, and semantic similarity measurement. He has served on program committees for APDCM , GPC-2018 , and IEEE BigMM conferences, while maintaining editorial roles at International Journal of High Performance Computing and Journal of Big Data . Scientific Awards IEEE Life Fellow ACM Distinguished Scientist

Li QinView profile

Professor

• Social Media and Commerce
• Adoption of Information Technology
• Information Security and Privacy
• +3 more

Li Qin is a Chair and Professor of Management Information Systems at the Department of Accounting, Taxation, Law, and Information Sciences in Silberman College at Fairleigh Dickinson University (FDU). She holds a BA and BS from Tianjin University, China, and an MBA and PhD from Rutgers University, USA. Research Focus: Social media and commerce, information security/privacy, cross-cultural studies of information systems. Teaching: Courses include Information Systems for Managers, Strategic Management of Information Systems, and Database Applications in Business. Her scholarly work has been published in journals such as the Journal of Computer Information Systems , Internet Research , and International Journal of Human-Computer Interaction . Globally, she has served as a Visiting Professor at IESEG School of Management in France and taught in FDU’s partnered program in Chengdu, China. Scientific Awards Silberman Global Faculty Fellow

• Wireless Communication
• Edge Computing
• Network Security
• +3 more

Yao Zhu is a Visiting Professor at the Chair of Information Theory and Data Analytics, RWTH Aachen University . His research focuses on advanced wireless communication systems, particularly in Edge Computing , Ultra-Reliable Low-Latency Communication (URLLC) , and Physical Layer Security , leveraging Finite Blocklength Codes for next-generation network optimization. Key research areas include: Optimization of resource allocation and task scheduling in distributed edge learning and fog computing environments Reliability and energy efficiency trade-offs in Industrial IoT and V2X networks Novel applications of NOMA (Non-Orthogonal Multiple Access) and short-packet communication for secure and fresh data transmission Integration of physical layer deception with semantic reliability models His work explores the interplay between telecommunications and computer science principles to address challenges in low-latency, high-reliability networked systems. The Chair of Information Theory and Data Analytics serves as his academic base, focusing on theoretical and practical advancements in data-driven communication frameworks.

Xiaolin HuView profile

Professor

• Modeling and Simulation
• Complex Systems Science
• Agent-Based Systems
• +3 more

Xiaolin Hu is a Professor in the Department of Computer Science at Georgia State University within the College of Arts & Sciences. His research focuses on modeling and simulation theory with applications in complex systems science, agent-based systems, and advanced computing environments. Ph.D. in Electrical and Computer Engineering, University of Arizona (2004) NSF CAREER Award recipient Senior member of IEEE and Society for Modeling and Simulation International (SCS) Associate editor for ACM Transactions on Modeling and Computer Simulation (TOMACS) and other journals SIMULATION: Transactions journal and International Journal of Modeling, Simulation, and Scientific Computing (IJMSSC) Dr. Hu's research spans three major areas: Dynamic Data-Driven Simulation (DDDS): Development of simulation frameworks that assimilate real-time data, particularly applied to wildfire spread prediction and autonomous systems. Multi-Agent Systems: Study of adaptive behaviors and coordination mechanisms for unmanned aircraft and social/public health systems. Advanced Computing: Implementation of parallel and cloud computing solutions for large-scale simulations. His recent publications (2025-2023) demonstrate a strong focus on integrating real-time data from UAVs and satellite systems into wildfire simulations, utilizing Bayesian methods for sequential data assimilation, and developing cloud-based simulation services. These works bridge computational modeling with environmental science applications. Scientific recognitions include: National Science Foundation (NSF) CAREER Award Dr. Hu has chaired multiple international conferences in modeling and simulation and leads the SIMS Lab at Georgia State University, which specializes in simulation technologies and their applications in diverse domains.

Yi PanView profile

Professor

• Parallel and Cloud Computing
• Wireless Networks
• Bioinformatics
• +3 more

Dr. Yi Pan is a Distinguished University Professor and Chair of the Department of Computer Science at Georgia State University. He holds a B.Eng. and M.Eng. from Tsinghua University (China) and a Ph.D. from the University of Pittsburgh (USA). His research focuses on parallel computing, wireless networks, bioinformatics, and machine learning, with over 330 publications and 39 authored/edited books. Dr. Pan has organized international conferences and delivered over 40 keynote speeches globally. Education: B.Eng., Computer Engineering, Tsinghua University, 1982 M.Eng., Computer Engineering, Tsinghua University, 1984 Ph.D., Computer Science, University of Pittsburgh, 1991 Research Interests: Dr. Pan’s work spans parallel and cloud computing, wireless networks, and bioinformatics. His contributions include scalable algorithms for functional module discovery in protein networks, self-defense mechanisms for cyber threats, and efficient routing protocols for sensor networks. Recent efforts integrate AI into healthcare, such as lesion localization in OCT imaging and autism spectrum disorder diagnosis via EEG analysis. Awards & Recognition: IEEE Distinguished Speaker (2000–2002) Yamacraw Distinguished Speaker (2002) Listed in Who’s Who in America and Who’s Who in Computational Science Awards from NSF, AFOSR, IBM, and Mellon Foundation Advising & Leadership: As department chair, Dr. Pan oversees interdisciplinary collaborations between Computer Science and Computer Information Systems. He has advised numerous students and holds editorial roles in 15 journals, including several IEEE Transactions. His grants focus on advancing AI-driven healthcare, cybersecurity, and computational biology. Labs & Teams: Leads research initiatives in bioinformatics, medical AI, and parallel computing, collaborating with industry partners like IBM and Shell Oil. Active in organizing conferences such as the IEEE International Conference on Bioinformatics and Biomedicine.

Xiaoyin WangView profile

Associate Professor

• Natural Language Processing
• Program Analysis
• Software Engineering
• +6 more

Xiaoyin Wang is an Associate Professor in the Department of Computer Science at the University of Texas at San Antonio, with affiliations to the College of AI, Cyber and Computing. She previously held a PostDoc position at UC Berkeley's Department of Electrical Engineering and Computer Science. Ph.D. in Computer Science, Peking University (2012) B.Eng. in Computer Science, Harbin Institute of Technology Her research focuses on Natural Language Processing , Program Analysis , Software Engineering , and Software Security . Key sub-areas include: Software migration and compatibility Build system automation Testing and debugging methodologies Privacy policy enforcement in mobile apps Deep learning for software analysis Augmented/Virtual Reality testing Recent publications (2022-2024) emphasize automated oracle prediction for AR/VR testing, data-sensitive analysis, and DevOps toolchain optimization. Trends include: Adaptation of program analysis to immersive environments Privacy-preserving software engineering Empirical studies on testing frameworks Academic accolades include: NSF CAREER Award (2019) President's Research Achievement Award (UTSA, 2019) Multiple best paper awards at ICSE, TOSEM She has advised 7 graduate students, including: Current: Rodney Rodriguez, Xueling Zhang, Sunzhou Huang Graduated: Xue Qin (Villanova), Foyzul Hassan (UM-Dearborn), Shaikh Mostafa (Amazon/Microsoft) Laboratory work involves tools like: TranStrL: Software internationalization Hima: API mapping for framework evolution NetworkProfiler: Android app fingerprinting DOVAR: AR/VR visualization for education Uniloc: CI failure diagnosis

Michael McGarryView profile

Associate Professor

• Communication Networks
• Machine Learning
• Internet
• +6 more

Michael McGarry is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso (UTEP). His research focuses on communication networks, particularly mechanisms for improving network efficiency through machine learning and optimization. He leads UTEP's Communication Networks Laboratory (NetLab), which explores fault localization, automated network management, and bandwidth forecasting. McGarry's work has garnered over 2100 citations, with an h-index of 16 and an Erdős number of 2. He has mentored three Ph.D. students, including Rami Haddad, Salvador Melendez, and Christopher Mendoza, who now hold prominent roles in academia and industry. His research interests span machine learning applications in networking, video networking, cloud computing, and medium access control (MAC) protocols. Notable contributions include techniques for network fault localization using unsupervised machine learning and innovations in hybrid PON/xDSL access networks. McGarry has also developed methodologies for optimizing bandwidth distribution and reducing energy consumption in communication systems. Awards: 2009 IEEE Communications Society Best Tutorial Paper Award Grants: Recent funding focuses on network management automation and fault detection. McGarry's collaborative projects include integrating OpenTap with quantum entanglement testbeds and advancing SDON (Software Defined Optical Networks) architectures. His lab’s work emphasizes practical solutions for real-world network challenges, from enterprise systems to military applications.

Kartik GopalanView profile

Professor

• Cloud computing
• Virtualization
• Cybersecurity
• +3 more

Kartik Gopalan is a Professor in the School of Computing at Binghamton University (State University of New York), serving as Interim Associate Dean for Research, Corporate Engagement, and Entrepreneurship within the Thomas J. Watson College of Engineering and Applied Science. He holds a PhD from Stony Brook University, an MS from IIT Madras, and a BE from Delhi Institute of Technology. Education - BE: Delhi Institute of Technology - MS: Indian Institute of Technology, Chennai - PhD: State University of New York at Stony Brook Research Interests His work focuses on experimental computer systems, including virtualization, cybersecurity, cloud computing, operating systems, and networks. Key projects include the OSNET Group's VirtuOSNet initiative, exploring advancements in virtual machine migration, hypervisor management, and privacy-preserving technologies. Notable contributions include Directvisor (bare-metal cloud virtualization), Span Virtualization (multi-hypervisor ecosystems), and privacy-preserving VMs. Professional Service - Associate Editor, IEEE Transactions on Parallel and Distributed Systems (2022–present) - Associate Editor, IEEE Transactions on Cloud Computing (2017–2024) - TPC roles at USENIX ATC, HPDC, and ICDCS Awards Recipient of the National Science Foundation CAREER Award (2013). Over 60 refereed publications and 8 U.S. patents reflect his research impact. Advising & Teams Mentor of numerous PhD/Masters students (e.g., Roja Eswaran, Mingjie Yan) and leads the OSNET Group, dedicated to advancing operating systems, networks, and cloud systems. His research bridges theoretical innovation with practical implementations in data center environments.

Lutz EcksteinView profile

Professor

• Automotive Engineering
• Automated Driving Systems
• Vehicle Dynamics
• +4 more

Univ.-Prof. Dr.-Ing. Lutz Eckstein is the Head of the Institute of Automotive Engineering (ika) at RWTH Aachen University and a leading expert in automotive engineering. He concurrently serves as President of the VDI Association of German Engineers, President of the VDI Scientific Advisory Board for the Federal Ministry of Digital and Transport (BMDV), and Scientific Director of the NRW Competence Network for Automated and Connected Mobility. His professional background includes senior roles at BMW and DaimlerChrysler, focusing on vehicle safety, driver assistance systems, and ergonomics. Eckstein holds a Doctorate from the University of Stuttgart (2000) and received the Artur Fischer Prize (1995) for academic excellence. His research interests span automated driving systems, human-machine interfaces, scenario-based testing, and mobility infrastructure. He leads high-profile projects like UNICARagil and coordinates the Mobility and Transport profile at RWTH Aachen. Over 80 patents and publications reflect his contributions to automotive innovation, including advancements in sensor fusion, digital twins, and cooperative intelligent transport systems (C-ITS). His recent work emphasizes safety assurance for automated vehicles, scenario databases, and scalable simulation frameworks. Eckstein's interdisciplinary approach bridges academia and industry, driving transformative solutions for future mobility challenges.

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.