Find Academic Supervisors

• Transportation Engineering
• Operations Research
• Data Science
• +6 more

Nikola Markovic is an Associate Professor in the Civil & Environmental Engineering Department at the University of Utah, specializing in applications of operations research and data science to transportation problems. His research spans paratransit optimization, work zone safety, airport operations, and disaster response logistics. Dr. Markovic earned his educational qualifications in Transportation Engineering, including a BS from the University of Belgrade, and both MS and PhD degrees from the University of Maryland. His research focuses on applying advanced computational methods to solve practical transportation challenges. Key areas include optimizing paratransit services for individuals with disabilities, improving snowplow routing in Utah, enhancing work zone safety through computer vision, and developing systems for airport operations monitoring at non-towered airports. His work often involves collaboration with transportation agencies and industry partners to ensure practical applicability. Analysis of his recent publications reveals a strong trend toward integrating machine learning techniques with traditional transportation engineering problems. His work frequently employs advanced methods like generative adversarial networks, deep learning, and optimization algorithms to address complex transportation challenges across multiple domains including paratransit, work zones, airports, and disaster response. Nominated for the Early Career Teaching award (2023 and 2021) Ranked among top 15% instructors in the College of Engineering (2022) Winner of Transportation Science and Logistics Best Paper Award from INFORMS (2022) Winner of National ACRP student design competition (2021) Dr. Markovic has advised numerous graduate students through thesis research courses in transportation engineering. His grant portfolio includes significant funding from the Utah Department of Transportation, Utah Transit Authority, and National Science Foundation, supporting research in accessibility, work zone safety, and paratransit service improvement. Current projects include enhancing accessibility for individuals with limited mobility using AI and cycling data, measuring roadside feature impacts on crashes, and developing technology integration for disadvantaged communities. His laboratory work focuses on transportation data analytics, with emphasis on computer vision applications for infrastructure monitoring and optimization algorithms for transportation operations. Current team projects involve developing systems for non-towered airport monitoring, improving paratransit services through technology integration, and optimizing emergency response after seismic events.

Zachary PattersonView profile

Professor

• Transportation Engineering
• Data Science
• Machine Learning
• +5 more

Zachary Patterson is a Professor at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on emerging technologies in transport-related data collection, computational geospatial data processing, and the application of statistical and artificial intelligence techniques to transportation and environmental challenges. He specializes in discrete choice experiments, greenhouse gas emission prediction, and smart mobility solutions. Dr. Patterson's work integrates machine learning, graph neural networks, and geospatial analysis to address complex issues such as public transit optimization, passenger flow prediction, and environmental impact assessment. He has developed frameworks for privacy-preserving data collection and innovative solutions for on-demand transit systems. His interdisciplinary approach bridges computer science, transportation engineering, and environmental science. Notable contributions include the TMS-GNN model for traffic-aware passenger flow prediction, HydroVision for hydrometric forecasting, and frameworks for electric vehicle adoption analysis. His research often emphasizes interpretability of black-box machine learning models and the ethical use of data in urban systems. Dr. Patterson has authored over 50 publications, with a focus on transportation data analytics, sustainability, and smart cities. His work has been applied in real-world contexts such as Montreal’s transportation infrastructure and environmental policy design.

• Natural Language Processing
• Information Retrieval
• Recommender Systems
• +2 more

Dr. Annalina Caputo is an Assistant Professor in the School of Computing at Dublin City University and Academic Lead for the part-time MSc in Artificial Intelligence program. Since 2022, she serves as Assistant Head for Research Management. She is a funded investigator in the ADAPT and I-Form research centres, leading the Proactive Experience & Agency challenge. Her research spans Natural Language Processing, Information Retrieval, and Machine Learning, with applications in personalization systems. Dr. Caputo holds a Ph.D. in Computer Science from the University of Bari Aldo Moro, where she researched Semantics and Information Retrieval. She previously held research positions at Trinity College Dublin as an EDGE COFUND Marie Curie Fellow and at the University of Bari. She has participated in numerous evaluation campaigns including CLEF, SemEval, and WSDM Cup. Her current research focuses on Intelligent Information Access, Text Representation, Temporal Dynamics in IR, Personalized Retrieval, Semantic IR, Quantum IR, Cross-Language Retrieval, Question Answering, and Recommender Systems in NLP and Additive Manufacturing contexts. Dr. Caputo serves as Guest Editor for the Special Issue on Knowledge Graphs for Search and Recommendation and is General Co-Chair for ECIR 2023. Her recent publications demonstrate strong focus on transformer-based recommender systems, NLP applications in healthcare/manufacturing, and interactive retrieval systems.

• Game Research
• Serious Games
• Extended Reality (VR/AR/MR)
• +7 more

Elif Surer is an Associate Professor and Associate Director at Middle East Technical University's Graduate School of Informatics, Department of Multimedia Informatics. She leads the Entertainment Computing and Interactive Systems Laboratory (ECISLab) and actively contributes to METU's entrepreneurship initiatives through GIMER (Entrepreneurship Research Center). Her academic leadership extends to international projects including EU Horizon Europe initiatives and collaborations with institutions like Stanford University's University Innovation Fellows program. Dr. Surer's research focuses on the intersection of game technologies, extended reality, and practical applications across diverse domains. Her work spans serious games for CBRNe (Chemical, Biological, Radiological, Nuclear, and Explosive) training, virtual reality applications for mining safety, archaeological visualization, and educational technology. She has developed frameworks for heterotopias as discursive playgrounds, modular serious game development for virtual laboratories, and advanced techniques in persona building for game design. Her interdisciplinary approach bridges computer science with fields like archaeology, healthcare, and occupational safety, creating innovative solutions that address real-world challenges through immersive technologies. Her publication record demonstrates consistent contributions to top journals including IEEE Transactions on Games, Virtual Reality, and JMIR Serious Games. Recent work shows increasing focus on biological network visualization in XR environments, advanced testing frameworks for deep learning systems, and sophisticated persona modeling techniques that go beyond traditional approaches. Her research trajectory reflects growing integration of AI with immersive technologies, particularly in specialized training applications and scientific visualization. METU Performance Awards (2020, 2021) Best Poster award at METU Graduate School of Informatics Open Research Day TÜBİTAK Above-Threshold-Awards Featured in Researchers Active in Technical Games Research list Dr. Surer actively supervises numerous graduate students across multiple projects, with recent completions including theses on clickbait detection, VR for mining safety, and adaptive serious games for children with learning difficulties. She leads significant research funding including EU Horizon Europe projects like eNOTICE-2 (focused on CBRNe training), the MR4MS project for mine safety, and the Quantum Flagship project QuTE4E. Her laboratory environment fosters collaboration between computer science, architecture, and other disciplines, creating opportunities for students to engage in cutting-edge research with practical applications. As director of ECISLab, she maintains strong connections with industry partners including METU Teknokent, and actively participates in entrepreneurship initiatives through METU GIMER. Her work with the University Innovation Fellows program demonstrates commitment to developing entrepreneurial skills among students, while her research on virtual reality applications continues to expand into new domains including healthcare, archaeology, and emergency response training.

• Multimedia Networking
• Telecommunications
• Edge Computing
• +3 more

Prof. Gabriel-Miro Muntean is a Professor at the School of Electronic Engineering, Dublin City University (DCU), Ireland. He holds a Ph.D. (2003) from DCU and B.Eng./M.Sc. degrees in Software Engineering from Politehnica University of Timisoara, Romania. He co-directs the DCU Performance Engineering Laboratory and is a Principal Investigator with Insight and Lero National Research Centres. His research focuses on multimedia networking, wireless/energy-aware communications, and technology-enhanced learning. Education: B.Eng. Software Engineering (Politehnica University of Timisoara, 1996) M.Sc. Software Engineering (Politehnica University of Timisoara, 1997) Ph.D. Electronic Engineering (DCU, 2003) Research Interests: Quality-oriented adaptive multimedia streaming Energy-efficient networking Personalized learning technologies 5G/6G network architectures Edge computing optimization Publications & Grants: Over 450 papers, 4 books, and 26 book chapters (H-index=53) EU Horizon 2020 projects: Coordinator of NEWTON, Lead in TRACTION Awards: IEEE Fellow (202X) IEEE Broadcast Technology Society Fellow Advising & Labs: Supervised 25 PhD students and 15 postdocs Co-director of DCU Performance Engineering Lab

Wei XiangView profile

Adjunct Professor

• Internet of Things
• Machine Learning for IoT
• Big Data Analytics
• +3 more

Wei Xiang is an Adjunct Professor and Founding Chair of Electronic Systems and Internet of Things Engineering at James Cook University. He leads the development of Australia's first accredited IoT Engineering program and conducts research at the intersection of IoT, machine learning, and big data analytics. Research encompasses: IoT systems for environmental monitoring Machine learning applications for sensor data Edge computing architectures Wireless communication protocols Smart agriculture technologies Publication analysis reveals focus areas: Smart transportation systems (25%) Agricultural IoT (20%) Medical AI applications (15%) Industrial IoT (15%) Network optimization (25%) Honors include Pearcey Entrepreneurship Award, Engineers Australia Cairns Engineer of the Year, and TNQ Innovation Award for establishing Australia's first IoT Engineering degree. Current projects include closed-loop irrigation systems for sugarcane farms and marine monitoring using distributed deep learning.

Yuhong LiuView profile

Associate Professor

• Trustworthy Generative AI
• Blockchain Security
• IoT Anomaly Detection
• +3 more

Yuhong Liu is an Associate Professor in the Department of Computer Science and Engineering at Santa Clara University's School of Engineering. She holds a B.S. and M.S. from Beijing University of Posts and Telecommunications (2004, 2007) and a Ph.D. from the University of Rhode Island (2012). Her research focuses on trust, security, and privacy in emerging technologies including Generative AI, IoT, blockchain, and social media. She leads the Trustworthy Computing Lab, which develops solutions for IoT security, misinformation detection, and energy-efficient systems. Her research spans: Generative AI : Trustworthy synthetic data generation and multi-agent collaboration Blockchain : Multi-signature schemes and decentralized consensus IoT Security : Anomaly detection and lightweight cryptography Social Media : Misinformation mitigation and privacy preservation Recent publications emphasize blockchain-enabled security, IoT anomaly detection, and AI fairness, reflecting a trend toward practical, cross-domain solutions for cyber-physical systems. Her work frequently integrates machine learning with cryptographic techniques to address real-world vulnerabilities. Awards & Honors: IEEE Rising Star Service Award (2023) APSIPA Distinguished Lecturer (2021-2022) Researcher of the Year, Santa Clara University (2019) Best Paper Awards at IEEE SocialCom 2010 & UMEDIA 2016 She advises 7+ graduate students on IoT security, blockchain, and social media analytics. She co-leads the NSF-funded EuReCa Global Center for clean energy research and has organized panels on AI ethics and disinformation. Her lab collaborates with industry partners to deploy secure edge computing solutions.

Behnam DezfouliView profile

Associate Professor

• Internet of Things (IoT)
• Networking
• Cyber-Physical Systems
• +6 more

Behnam Dezfouli is an Associate Professor in the Department of Computer Science and Engineering at Santa Clara University, USA, and Director of the IoT Research Lab (SIOTLAB). His research focuses on IoT systems, edge/fog computing, network security, and software-defined networking. He teaches courses on IoT, computer networks, and programming. Affiliations: IEEE Senior Member, IEEE Communications Letters Associate Editor. Research: IoT protocols, energy-efficient communication, AI-driven network optimization, and humanitarian tech applications like flood monitoring (Flomosys). Publications: Over 60 papers in journals like IEEE Transactions and conferences such as INFOCOM and GLOBECOM, emphasizing IoT security, edge computing, and wireless protocols. Projects: Developed platforms like the Fog Development Kit (FDK), MonFi for network monitoring, and Sensifi for ultra-high-rate sensing. Grants & Recognition: Senior Member of IEEE, leading industry collaborations and litigation consulting.

Krishna RamamoorthyView profile

Assistant Professor

• Wireless Communication and Networking
• Non-Orthogonal Multiple Access (NOMA)
• Machine Learning for Network Optimization
• +5 more

Dr. Krishna Ramamoorthy is an Assistant Professor of Computer Science and Engineering at Santa Clara University (SCU), serving since Fall 2024. He directs the Wireless Intelligent Networks (WIN) Lab, focusing on next-generation wireless systems, including NOMA, 6G, and QoE-driven network optimization. He holds a Ph.D. in Computational Science from UC Irvine (2023), with prior degrees from California State University, Northridge and Amrita Vishwa Vidyapeetham, India. His research emphasizes network economics, machine learning for wireless protocols, and user-centric communication. He teaches courses in programming, data structures, and computer networks. Recent grants include the 2FURS Grant (2024) for undergrad research at WIN Lab, and he actively serves on TPCs for IEEE ICC, WCNC, and Globecom. Professional service includes reviewing for IEEE Communications Magazine and mentoring students in senior design projects and directed research. Beyond academia, he enjoys aquascaping, fostering kittens, and board games like Catan.

Chong YuView profile

Assistant Professor

• Wireless Networks
• Internet of Things
• Federated Learning
• +2 more

Dr. Chong Yu is an Assistant Professor in the Department of Computer Science at the University of Cincinnati's College of Engineering and Applied Science. His research focuses on wireless networks, data analytics, IoT systems, and federated learning architectures. He obtained his PhD in Electrical and Computer Engineering from the University of Nebraska-Lincoln. Research interests span secure federated learning frameworks, privacy-preserving data querying, and efficient communication protocols for distributed systems. Applied domains include e-health, agricultural IoT, and aerial computing networks. Recent investigations address model poisoning attacks in federated environments and encrypted anomaly detection for blockchain-based data trading. Publications demonstrate consistent focus on security and efficiency trade-offs in distributed systems, with emerging work on large language models for code comprehension and runtime monitoring for JavaScript security. Methodologies emphasize lightweight cryptographic schemes for resource-constrained devices.

Fiona FangView profile

Assistant Professor

• Machine Learning for Wireless Communications
• Non-Orthogonal Multiple Access (NOMA)
• Reconfigurable Intelligent Surfaces (RIS)
• +4 more

Fiona Fang is an Assistant Professor in the Department of Electrical and Computer Engineering and Department of Computer Science at Western University, Canada. She holds a Ph.D. from the University of British Columbia (2017) and has prior academic experience at Durham University (2020–2022) and the University of Manchester (2018–2020). Her research focuses on machine learning for intelligent wireless communications, NOMA, RIS, MEC, and Edge AI. She serves as an editor for IEEE Transactions on Wireless Communications and has received awards including the IEEE SPCC Early Achievement Award (2023) and the 2024 Junior Faculty Award of Excellence in Research. Education: Ph.D. (UBC), M.Sc. and B.Sc. (Lanzhou University). Research emphasizes interdisciplinary applications of machine learning in wireless systems, with contributions to energy-efficient resource allocation and network design. Key publications include surveys on multi-access edge computing and RIS-assisted NOMA networks. She actively organizes conferences like IEEE Globecom and ICC, and her work bridges theoretical advancements with practical network implementations.

Yu WangView profile

Professor

• Wireless Networks
• Smart Sensing
• Distributed Computing
• +6 more

Yu Wang is a Professor and Chair in the Department of Computer and Information Sciences at Temple University, leading the Wireless Networking and Sensing Lab (Wang Lab). His research focuses on wireless networks, smart sensing, distributed computing, and security/privacy, with notable contributions to federated learning, quantum networks, and edge computing. He has received prestigious awards including the IEEE Benjamin Franklin Key Award and Fellow of IEEE. Currently advising PhD students Jiyao Liu and Xuanzhang Liu, he has mentored 11 graduated PhD students now in academia and industry. Education: PhD from Illinois Institute of Technology (2004). Key roles include Editor for IEEE Transactions, organizing major conferences (e.g., IEEE IPCCC, IEEE MASS), and serving on NSF review panels. Funded by NSF, DoT, Microsoft, and others. His lab's research integrates emerging technologies to advance human-device interactions in smart environments. Recent research trends emphasize quantum-assisted computing, federated learning optimization, and wearable health monitoring. Over 300 publications span networking journals/conferences like IEEE/ACM Transactions and INFOCOM. Awards highlight contributions to vehicular networks and data placement strategies.

Susmit ShannigrahiView profile

Assistant Professor

• Network Protocols
• Future Internet Architectures
• 5G Mobile Networks
• +8 more

Susmit Shannigrahi is an Assistant Professor in the Department of Computer Science at Tennessee Tech University. His work focuses on advanced networking protocols, future internet architectures, and big data management. He leads research in areas like 5G networks, IoT security, and decentralized data replication algorithms. His research interests include optimizing network protocols for data-intensive applications, securing vehicular and smart grid systems, and developing frameworks like CLEDGE and Hydra for edge computing and distributed storage. He has contributed to projects such as NDN-based data distribution for genomics and climate research, and has pioneered solutions like AquaCam for environmental monitoring. Shannigrahi's recent work emphasizes hybrid networking approaches (e.g., NDN-IP integration), proactive routing strategies using AI, and scalable decentralized systems. His projects often involve collaboration with domain scientists to address real-world challenges in big data transfer and storage. He holds a strong record of innovation in testbed deployments, protocol design, and cross-disciplinary applications of networking principles. His lab focuses on practical implementations of theoretical networking concepts in fields like smart grids, autonomous vehicles, and genomics.

Martin Agelin-ChaabView profile

Professor

• Aerodynamics
• Turbulent Flows
• Thermal Systems
• +4 more

Dr. Martin Agelin-Chaab holds the dual role of Department Chair and Professor in the Department of Mechanical and Manufacturing Engineering at Ontario Tech University's Faculty of Engineering and Applied Science. His expertise spans aerodynamics, thermal systems, and sustainable energy. He earned his PhD in Mechanical Engineering from the University of Manitoba, with prior degrees from institutions in Canada and Ghana. His research focuses on bluff body aerodynamics, turbulent flows, vehicle and battery thermal management, and sustainable energy systems. Notable projects include aero-thermal testing of race cars and thermal analysis of lithium-ion batteries. He has authored over 20 peer-reviewed publications in journals like Applied Energy and the ASME Journal of Fluids Engineering. Awards: Best Instructor Award (2013), NSERC Postgraduate Scholarship (2008-2010), and multiple fellowships from the University of Manitoba. Teaching: Courses include Fluid Mechanics, Energy Systems, and Dynamics. Dr. Agelin-Chaab's work bridges theoretical and experimental approaches, with applications in automotive engineering and renewable energy integration. His lab (AAER) explores cutting-edge solutions for thermal and aerodynamic challenges in modern systems.

Omar Abdul WahabView profile

Assistant Professor

• Cybersecurity
• Artificial Intelligence
• Internet of Things
• +3 more

Omar Abdul Wahab is an Assistant Professor at the Department of Computer Engineering and Software Engineering, Polytechnique Montréal. He holds a PhD in Information Systems Engineering from Concordia University (2017) and completed postdoctoral research at École de technologie supérieure (2017-2018) in collaboration with Rogers and Ericsson. PhD: Concordia University, Montréal, Canada Master's: Lebanese American University, Beirut, Lebanon Bachelor's: Lebanese University, Tripoli, Lebanon His research focuses on Cybersecurity , Artificial Intelligence , and Internet of Things , with expertise in cloud computing security , federated learning , and game-theoretic security models . He has developed frameworks for threat intelligence coalitions , IoT intrusion detection , and trust-aware client selection in distributed systems. His recent publications emphasize federated learning security , IoT anomaly detection , and trust modeling in collaborative environments. Current supervised students include PhD candidates Sarhad Arisdakessian and Osama Wehbi, and Master's student Ranim Rahali.