Find Academic Supervisors

• Transportation Engineering
• Urban Planning
• Traffic Management
• +3 more

Dr. Lum Kit Meng is an Associate Professor at the School of Civil and Environmental Engineering, NTU, Singapore. His expertise spans Transportation Engineering, Urban Planning, and Traffic Management. He holds First Class Honors in Civil Engineering (NUS), a Master’s in Industrial Engineering (NUS), and a PhD in Transportation Engineering. Dr. Lum teaches undergraduate/postgraduate courses in Civil Engineering, Maritime Studies, and Logistics, and develops training programs for professionals. His research focuses on urban mobility, active mobility infrastructure, and traffic safety, with over 60 publications. He has provided consultancy services to public/private sectors, emphasizing data-driven analysis. Key research areas include pedestrian behavior, cycling facility design, and shared space dynamics. Recent studies explore 'keep left' regulations, e-scooter speed attitudes, and red-light camera impacts using simulation and VR techniques. His work bridges theoretical models (e.g., cellular automata) with practical infrastructure solutions. No awards or grants are explicitly listed, but his extensive publications and consultancy highlight industry-academic collaboration. He advises on transportation systems with a focus on Singapore’s urban challenges.

Dong NgoduyView profile

Associate Professor

• Connected and Autonomous Vehicles
• Traffic Flow Theory and Simulation
• Data Fusion
• +4 more

A/Professor Dong Ngoduy is the Head of Transport Engineering and an Associate Professor in Transport Engineering at Monash University's Department of Civil and Environmental Engineering. He holds a PhD in Traffic Flow Theory from TU Delft (Netherlands) and an MSc from Linköping University (Sweden). His research focuses on Connected and Autonomous Vehicles (CAVs), Traffic Flow Theory, Data Fusion, and Urban Network Optimization. He received the EPSRC Advanced Fellow Award (2011-2016) and chairs the Connected Traffic Systems Lab. His current work aims to develop smart city platforms for multi-modal transport infrastructure management. Education: MSc in Traffic Engineering, Linköping University PhD in Traffic Flow Theory, Delft University of Technology Research Expertise: Traffic Flow Theory Data Fusion Techniques Urban Network Optimization CAV Dynamics Grants & Awards: EPSRC Advanced Fellow Award (2011-2016) EU Horizon 2020 Project (~$1.2M) Australian Research Council (ARC) Assessor Teaching: Courses include Transport and Traffic Engineering (CIV2282) and Autonomous Vehicle Systems (CIV4100). Labs & Teams: Leads the Connected Traffic Systems Lab and collaborates on projects like Digital Twins for urban networks.

• Artificial Intelligence
• Robotics
• Autonomous Systems
• +2 more

Krister Wolff is an Associate Professor of Adaptive Systems at the Department of Mechanics and Maritime Sciences (M2) at Chalmers University of Technology. He also serves part-time as Vice Head of Department for Education. His research focuses on applying artificial intelligence, machine learning, and bio-inspired methods to robotics, autonomous systems, and self-driving vehicles. He teaches in the international Master's program in Complex Adaptive Systems. His work includes projects such as AI-supported vehicle suspension design, propeller optimization using genetic algorithms, and developing interactive robots for social distancing in healthcare settings. He has contributed to over 39 publications and 9 research projects, collaborating with organizations like VINNOVA and the Swedish Transport Administration. Notable projects include ISOLDE for hospital robots and Tactical Decision-Making in Autonomous Driving funded by the Wallenberg Foundation. Key areas of expertise include reinforcement learning for autonomous vehicles, evolutionary algorithms in design optimization, and driver behavior modeling in critical scenarios. His research bridges theory and practical applications, emphasizing collaboration between academia and industry.

• Antenna Design
• Evolutionary Algorithms
• Wireless Communications
• +7 more

Sotirios K. Goudos is a Professor at the Department of Physics, Aristotle University of Thessaloniki (AUTH), Greece, and Director of the ELEDIA@AUTH lab within the ELEDIA Research Center Network. His research focuses on antenna design, evolutionary algorithms, wireless communications, machine learning, and IoT applications. He holds a B.Sc. in Physics (1991), M.Sc. in Electronics (1994), Ph.D. in Physics (2001), and additional qualifications in Information Systems and Electrical Engineering. Prof. Goudos is a Senior Member of IEEE and serves as Editor-in-Chief of the Telecom open access journal (MDPI) and Associate Editor for IEEE Transactions on Antennas and Propagation, IEEE Access, and IEEE Open Journal of the Communication Society. He has organized multiple special issues in journals like EURASIP Journal on Wireless Communications and Networking and has authored/edited books on antennas and AI in networks. His awards include multiple IEEE Access Outstanding Associate Editor recognitions (2019–2023) and inclusion in Stanford University's top 2% scientists list (2020–2024). He teaches courses on telecommunications, Java programming, and microwave systems, and has supervised over two dozen master's students since 2009. His work spans antenna optimization, AI-driven communications, and IoT security, with contributions to 5G/6G, RIS systems, and smart agriculture. Prof. Goudos actively contributes to IEEE Greece Section leadership roles, including Secretary (2022) and Vice-Chair (2023–2024). His labs and teams focus on ELEDIA's research in electromagnetics, optimization, and AI applications.

Nicolas ZuffereyView profile

Professor

• Operations Management
• Supply Chain Management
• Optimization
• +4 more

Nicolas Zufferey is a Full Professor of Operations Management at the University of Geneva, Switzerland, where he has served since 2008. He leads research in optimization methods for complex systems, focusing on applications in supply chain management, production planning, inventory control, and transportation logistics. His affiliations include the Research Institute of Management and collaborations with CIRRELT (Transportation & Logistics) and GERAD (Decision Analysis). Education: PhD in Operations Research (EPFL, 2002), MSc/BSc in Mathematics (EPFL) Prior Experience: Postdoc at University of Calgary (2003–2004), Assistant Professor at Université Laval (2004–2007) Research Interests: His work emphasizes developing advanced metaheuristics (e.g., VNS, Tabu Search, PSO) for challenging optimization problems. Key domains include: Multi-objective scheduling with resource constraints Inventory deployment under uncertainty Network design for supply chains and transportation systems Publications: Over 150 peer-reviewed articles across journals like European Journal of Operational Research , Transportation Research , and INFORMS Journal on Computing . Recent work addresses electric vehicle routing, drone integration in delivery systems, and robust decision-making under uncertainty. Collaborations: Engaged with 35+ universities and 27 private companies globally. Active in applying operations research to industrial problems (e.g., Swiss railways, luxury watch production, pharmaceutical networks).

Bjorn BirgissonView profile

Professor

• Civil Engineering
• Transportation Infrastructure
• Materials Science
• +3 more

Bjorn Birgisson is the Chair of the School of Environmental, Civil, Agricultural and Mechanical Engineering and holds the Georgia Power E-Mobility Distinguished Professorship at the University of Georgia. His research focuses on infrastructure resilience, pavement engineering, materials science, and novel construction technologies. He has pioneered work on asphalt mixture performance, autonomous vehicle impacts on roadways, and extraterrestrial construction materials using lunar regolith. His interdisciplinary approach integrates computational modeling, experimental testing, and environmental sustainability. Educational Background: Ph.D., P.E. credentials are highlighted but formal education details are not provided in the text. His professional appointments emphasize practical application of research to real-world infrastructure challenges. Research Interests include: Transportation infrastructure resilience to climate change Advanced material characterization for pavements Additive manufacturing for space exploration Non-destructive evaluation techniques His recent publications (2020-2025) address: Moisture variation in clayey soils Pavement crack initiation modeling Autonomous truck infrastructure impacts Lunar regolith utilization Scientific Awards: Georgia Power E-Mobility Distinguished Professorship recognizes his contributions to sustainable transportation infrastructure. Advising/Grants: While student names are not listed, his research teams focus on doctoral-level projects in geotechnical engineering and materials science. Grant activities likely include federal/state transportation initiatives and space exploration partnerships. Labs/Teams: Active in the Boyd Research and Education Center, collaborating with industry partners on pavement testing and additive manufacturing technologies.

• Winter Road Maintenance
• Snow and Ice Engineering
• De-icing and Anti-icing Technologies
• +3 more

Professor Alex Klein-Paste is affiliated with NTNU's Department of Civil and Environmental Engineering, focusing on winter operations of roads and airports. His research emphasizes snow and ice engineering, anti-icing strategies, and friction dynamics. He leads the NTNU SnowLab, a specialized facility supporting education and research in snow engineering. Klein-Paste teaches courses on road planning, maintenance in cold climates, and infrastructure management. His research spans experimental studies on de-icing chemicals, snow compaction, and winter maintenance optimization. Key contributions include developing regression models for maintenance efforts and analyzing cross-country ski friction mechanics. He collaborates widely, with recent work addressing automated vehicle infrastructure needs and bicycle rolling resistance in winter conditions. Labs/Teams: Director of NTNU SnowLab, part of the roads, railways, and transport research group. His work bridges experimental engineering and real-world applications, influencing both academic and industrial sectors.

Mogens FosgerauView profile

Professor

• Transport Economics
• Discrete Choice Modeling
• Travel Behavior
• +7 more

Mogens Fosgerau is a Professor in the Department of Technology, Management and Economics at the Technical University of Denmark (DTU), where he conducts research in transport policy and transportation science. His work spans econometrics, travel behavior modeling, and transport economics, contributing to sustainable urban mobility and policy design. Institution: Technical University of Denmark Department: Department of Technology, Management and Economics Email: mogens.fosgerau@econ.ku.dk ORCID: https://orcid.org/0000-0002-6452-5215 His research focuses on discrete choice modeling, travel time valuation, scheduling preferences, and congestion pricing. He develops theoretical and empirical models to understand how individuals make travel decisions under uncertainty and how these behaviors affect urban transport systems. His work integrates economic theory with data-driven methods, often using large-scale datasets and advanced econometric techniques. The recent trend in his publications highlights innovations in perturbed utility models for route choice, stochastic traffic assignment, and the analysis of induced demand for cycling. His research bridges transportation science, behavioral economics, and operations research, with applications in urban planning and policy evaluation. Scientific awards received include: The International Choice Modeling Conference (ICMC) award for Most Innovative Application (2022) Best Overall Paper Award, ITEA Conference (2015) Best Paper Awards from BIVEC-GIVET (2007), Kuhmo-Nectar (2008) Hedorfs Fonds Pris for Transportforskning (2011) Mogens Fosgerau has supervised PhD students such as Fentie Abegaz and has been involved in multiple externally funded research projects, including URBAN (Innovation Fund Denmark), IRUC (Danish Council for Strategic Research), and Horizon 2020 initiatives. He has also served on review panels, including for the Norwegian Research Council, and contributed to peer review and editorial duties. He is actively engaged in research networks and has presented his work at international conferences. His projects often involve interdisciplinary collaboration with researchers in economics, engineering, and urban planning.

Malcolm HeywoodView profile

Professor

• Genetic Programming
• Coevolution
• Reinforcement Learning
• +12 more

Dr. Malcolm Heywood is a Professor in the Faculty of Computer Science at Dalhousie University, Halifax, Canada. He leads the Network Information Management and Security (NIMS) Lab and is actively involved in research on genetic programming, coevolution, reinforcement learning, and big data analytics. His research interests span: Genetic Programming and Evolutionary Computation Coevolution and Competitive Learning Problem Decomposition and Hierarchical Models Streaming Data Analysis and Anomaly Detection Network Security and Insider Threat Detection Reinforcement Learning in Games (Atari, ViZDoom, Dota 2) Dr. Heywood's recent publications focus on emergent behaviors in reinforcement learning using Tangled Program Graphs (TPG), benchmarking genetic programming for streaming data, and applications in cybersecurity and computational finance. His work demonstrates a strong trend toward scalable, efficient evolutionary models for complex, real-world problems. His scientific awards include: Silver placed at Human-Competitive (Humies) Competition (2018) Best Paper at EuroGP (2017) Best Paper at DETA track, ACM GECCO (2017) Best Paper at RWA track, ACM GECCO (2018) Nomination for Best Paper at DETA track, ACM GECCO (2019) He has supervised numerous graduate students, including PhD and Master's candidates, many of whom have continued research in evolutionary computation. His lab has developed open-source code distributions for Tangled Program Graphs and Symbiotic Bid-Based GP. Dr. Heywood teaches courses in Computer Organization, Introduction to AI with Gaming Applications, and Genetic Algorithms and Programming.

Shamik SenguptaView profile

Professor

• Wireless Networking & Mobile Computing
• Unmanned Autonomous Systems
• Cognitive Radio
• +28 more

Shamik Sengupta is the Ralph E. and Rose A. Hoeper Professor at the University of Nevada, Reno (UNR) , where he serves as Professor in the Department of Computer Science & Engineering and Executive Director of the Cybersecurity Center . He holds a PhD in Computer Science from the University of Central Florida (2007) and a BE in Computer Science from Jadavpur University (2002). IEEE Senior Member Director, UNR Cybersecurity Center NSF CAREER Award Recipient

• Cryptography
• Cybersecurity
• Authentication Protocols
• +5 more

Zheng Yang is a Professor at Tsinghua University's School of Software, with significant research contributions in cryptography, cybersecurity, and privacy-preserving systems. His work spans multiple institutions including collaborations with University of Helsinki's Secure System Group and Chongqing University of Technology. He maintains active research in both theoretical and applied security domains, with particular focus on industrial applications. Professor Yang's research interests center on cryptographic protocols, authentication mechanisms, and security for emerging technologies. His work addresses critical challenges in Cyber-Physical Systems security, Industrial Internet of Things protection, and privacy-preserving computation. He has made significant contributions to secure key exchange protocols, authentication systems, and defenses against sophisticated network attacks including DDoS mitigation strategies. His research bridges theoretical cryptography with practical implementations for resource-constrained environments. Analysis of Professor Yang's recent publications reveals a strong trend toward practical security solutions for industrial and embedded systems. His work increasingly focuses on balancing security with performance constraints in Cyber-Physical Systems and Industrial IoT environments. Key research themes include lightweight cryptography for resource-constrained devices, privacy-preserving location services, and novel authentication mechanisms that maintain security while minimizing computational overhead. His publications demonstrate consistent innovation in adapting cryptographic techniques to real-world security challenges. Professor Yang has established himself as a leading researcher through his extensive publication record in top security venues including IEEE Security & Privacy, USENIX Security, and ACM conferences. His work has been published consistently in high-impact journals and conferences, demonstrating sustained research productivity and influence in the security community. Professor Yang maintains active research collaborations with numerous institutions globally, evidenced by his extensive co-authorship network. His research has attracted significant funding for projects addressing critical security challenges in emerging technologies. His work on secure authentication protocols and privacy-preserving systems has practical applications across multiple industry sectors. Professor Yang leads research initiatives focused on secure Cyber-Physical Systems and Industrial IoT security. His laboratory work emphasizes practical implementations of cryptographic protocols for real-world systems, with particular attention to performance constraints in embedded environments. Current research directions include secure communication for programmable logic controllers, privacy-preserving location services, and adaptive defenses against sophisticated network attacks.

• Transportation Engineering
• Sustainable Transportation
• Urban Mobility Systems
• +3 more

Alejandro Henao is a Researcher in Civil Engineering at the National Renewable Energy Laboratory (NREL), specializing in on-demand mobility systems. His work focuses on optimizing emerging transportation modes, curb management, and performance metrics for mobility and energy efficiency. He has presented extensively at national and international conferences. Current Research Areas: On-demand mobility, ride-sourcing, ride-hailing (e.g., Uber/Lyft), curb management, mobility optimization, energy efficiency metrics Geographic Focus: Texas (Houston, Arlington, Austin), Denver, Colorado Methodologies: Case studies, spatial-temporal modeling, behavioral analysis, policy frameworks His publications and presentations demonstrate a consistent focus on understanding transportation network companies' impacts on urban mobility, vehicle ownership, and energy consumption. Henao also explores sustainable public transport solutions using clean energy technologies. Recent research outputs (2023-2025) emphasize automated and electrified on-demand mobility, curb space allocation optimization, and energy productivity metrics for transit systems. Key trends include integration of renewable energy in transportation, resilience planning for mobility networks, and behavioral responses to shared mobility services. Henao's work combines empirical studies with analytical modeling to provide actionable insights for cities seeking to reduce auto dependence and improve mobility efficiency. His collaborations span academic institutions, municipal governments, and transportation agencies across the United States. At NREL, he leads technical reports and presentations on mobility innovation, focusing on sustainable infrastructure adaptation for evolving transportation needs. His research often involves multi-disciplinary approaches to transportation challenges.

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete Optimization
• +7 more

Nikhil Bansal holds the prestigious Patrick C. Fischer Professorship of Theoretical Computer Science in the Department of Computer Science & Engineering at the University of Michigan's College of Engineering. His research program has established him as a leading figure in theoretical computer science, with significant contributions to algorithm design and analysis, particularly in discrete optimization problems. Bansal's research focuses on theoretical computer science with emphasis on design and analysis of algorithms for discrete optimization problems. His work spans multiple areas including discrepancy theory, approximation algorithms, randomized algorithms, combinatorial optimization, complexity theory, machine learning theory, and probability. He has made significant contributions to understanding the limits of approximation algorithms and developing novel techniques for combinatorial optimization problems. Analysis of Bansal's recent publications reveals a strong focus on discrepancy theory, online algorithms, and combinatorial optimization. His work often bridges theoretical computer science with discrete mathematics and probability theory. A recurring theme across his publications is the development of novel algorithmic techniques for solving NP-hard problems with provable guarantees. His research has evolved from foundational work in approximation algorithms to more recent contributions in quantum computing complexity and stochastic optimization. Patrick C. Fischer Professor of Theoretical Computer Science Bansal has advised numerous PhD students including Marek Elias, Shashwat Garg, and Greg Koumoutsous, as well as mentoring several postdoctoral researchers. He has served on editorial boards for top journals including Journal of the ACM, Theory of Computing, and Stochastic Models, and has been active on program committees for major conferences such as STOC, FOCS, SODA, and ICALP, including serving as chair for ICALP 2021. Bansal has organized multiple academic workshops including the STOC 2020 Workshop on Recent Advances in Discrepancy and Applications, several SDP Days at CWI Amsterdam, and the Semester on Bridging Continuous and Discrete Optimization at UC Berkeley in Fall 2017.

Jorg LiebeherrView profile

Professor

• Computer Networks
• Network Calculus
• Internet of Things (IoT)
• +6 more

Jorg Liebeherr is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto, holding the Nortel Chair of Network Architecture and Services. His research focuses on computer networks , particularly network calculus , self-organizing networks , protocol design , and traffic scheduling . Education: Diplom-Informatiker (with distinction), University of Erlangen (Germany), 1988 PhD, Computer Science, Georgia Institute of Technology, 1991 His recent work includes low-cost LoRa mesh networks for environmental sensing and mathematical frameworks for traffic control in 5G and IoT systems. Publications span journals like IEEE Internet of Things Journal and conferences such as IEEE Infocom and ACM Sigmetrics . Scientific Awards: IEEE Fellow (2008) Outstanding Service Award, IEEE ComSoc TC on Computer Communications (2006) ACM Sigmetrics Best Student Paper Award (2005) NSF CAREER Award (1996) Advising and Grants: Supervised 15+ theses (MASc/PhD) and secured grants from NSF, Virginia Engineering Foundation, and industry partners. Labs: Leads the Network Research Lab and HyperCast projects, an open-source platform for application-layer internetworking.

Hatem Abou-ZeidView profile

Assistant Professor

• 5G/6G Wireless Communications
• Artificial Intelligence
• Immersive Communications
• +4 more

Hatem Abou-Zeid is an Assistant Professor at the Department of Electrical and Software Engineering in the Schulich School of Engineering , University of Calgary. He holds Adjunct Professor appointments at Queen’s University, Carleton University, and Ontario Tech University, Canada. With a Ph.D. in Electrical and Computer Engineering from Queen’s University (2014), his academic journey includes 7 years of industry research at Ericsson and Cisco , where he led R&D projects resulting in 15+ patents. Queen's University (Ph.D., Electrical and Computer Engineering) Arab Academy for Science, Technology and Maritime Transport (B.Sc. and M.Sc., Electronics and Communications Engineering) His research focuses on 5G/6G wireless networking , immersive communications , and robust machine learning for networks. Recent projects explore trustworthy AI , joint sensing and communication , and pediatric brain-computer interfaces (BCI) . He has published extensively in top venues like IEEE JSAC , GLOBECOM , and IEEE Transactions on Networking , with over 60 publications and 19 patent filings. His scientific awards include the Research Excellence Award 2023 (UCalgary), Early Research Excellence Award 2023 (Schulich), and Best Paper Awards at EMBC 2024 (as advisor) and IEEE ICC 2022 . He leads the WAVES Research Group , mentoring 10+ graduate students and postdocs. Collaborations span institutions like the Hotchkiss Brain Institute and industry partners such as Ericsson and European Space Agency .