Find Academic Supervisors

Mark HickmanView profile

Professor

• Transport Engineering
• Public Transit Planning
• Urban Transportation Modelling
• +7 more

Professor Mark Hickman is the TAP Chair and Professor of Transport Engineering at the University of Queensland's School of Civil Engineering. He holds roles as Deputy Head of the School and Affiliate of the Dow Centre for Sustainable Engineering Innovation. His research focuses on public transit planning, sustainable transport innovations, urban transportation modelling, and traffic engineering. He has a PhD from MIT and has authored over 140 publications. Current research includes MaaS trials, electric vehicle infrastructure, and traffic incident prediction using AI. Education: BSc, MSc, and PhD from MIT. Grants include projects on MaaS impact trials, low/zero emission transport strategies, and real-time traffic analytics. Supervised 20+ PhD/Master’s students in areas like autonomous vehicles, transit operations, and sustainable transport policies. Leads grants from Queensland Transport, iMove CRC, and Brisbane City Council. Active in transport policy advising and media commentary on public transport, traffic engineering, and urban planning. Recent work emphasizes decarbonizing road freight, EV charging networks, and integrating MaaS systems. Lab affiliations include the Transport Academic Partnership (TAP) and the Australian Transport Research Cloud (ATRC). Collaborates on projects like the Odin Pass MaaS trial at UQ and Brisbane’s EV readiness assessments.

Salma EmaraView profile

Assistant Professor

• Machine Learning
• Computer Networking
• Natural Language Processing
• +3 more

Salma Emara is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Toronto within the Faculty of Applied Science & Engineering. Her academic journey includes a B.Sc. in Electronics and Communications Engineering from the American University in Cairo (2018) and a Ph.D. in Computer Engineering from the University of Toronto (2022), supervised by Professor Baochun Li. Her research spans two domains: (1) technical work in reinforcement learning for computer networking , including adaptive bitrate selection, edge caching, and congestion control; and (2) pedagogical work focused on debugging skill development for beginner programmers and leveraging natural language processing in engineering education . She emphasizes hands-on learning through in-class activities and problem-solving assignments. Publication trends reveal a focus on reinforcement learning in networking (2018–2023) and a parallel interest in educational technology (2024). Her recent work (e.g., TextCraft ) explores NLP-driven resource recommendation for textbooks, while earlier projects (e.g., Cascade , Pareto ) address network optimization through machine learning. Scientific awards include: Faculty of Applied Science & Engineering Early Career Teaching Award (2025) Departmental Teaching Awards (2022–2024) Shortlisted for TATP Teaching Assistant Excellence (2022)

• Transportation Systems
• Traffic Engineering
• Logistics Optimization
• +5 more

Chiara Colombaroni is a Researcher (Ricercatore a Tempo Determinato di Tipo A) at the Department of Civil, Building and Environmental Engineering at Sapienza University of Rome, within the Faculty of Civil and Industrial Engineering. She holds a PhD in Infrastructures and Transportation from Sapienza (2011) and Master’s and Bachelor’s degrees in Transportation Systems Engineering (2006 and 2003). Colombaroni specializes in transportation engineering, with a focus on traffic modeling, logistics optimization, and intelligent transportation systems (ITS). She has led and contributed to numerous national and international projects, including research on container operations, road safety, and smart mobility solutions through initiatives like ITS Italia 2020. Her work integrates advanced methodologies like machine learning, big data analysis, and simulation-optimization techniques to address urban mobility challenges. She teaches courses such as Programming for Transport Systems and Freight Transport and Logistics at Sapienza, and supervises doctoral research in transportation systems. Her research outputs span over 17 indexed publications, with an H-index of 8 and impactful contributions to journals like Transportation Research Part C and IET Intelligent Transport Systems. Education: PhD in Infrastructures and Transportation, Sapienza University (2011) MSc in Transportation Systems Engineering, Sapienza University (2006) BSc in Transportation Engineering, Sapienza University (2003) Research Focus: Urban traffic simulation and optimization Intelligent transportation systems (ITS) Logistics and supply chain optimization Big data applications in transportation Electric vehicle integration and sustainable mobility Recent Trends in Articles: Her recent work emphasizes leveraging machine learning for traffic pattern analysis, optimizing urban logistics with electric vehicles, and integrating IoT for waste management. Projects like the ‘Two-Echelon Electric Vehicle Routing Problem’ and ‘Industry 4.0 in Waste Management’ highlight her focus on sustainable and tech-driven solutions. She also explores post-COVID mobility trends and smart city infrastructure design. Grants & Projects: Coordinated the Qatar Strategic Transport Model Update project (2017–present) Contributed to the EU-funded MULTITUDE project on traffic simulation validation (2010–2013) Participated in the ‘PASSIAMO’ project for smart mobility in Lazio (POR FESR 2014–2020) Labs/Teams: Member of the Sapienza Transport and Logistics Research Center (CTL) Collaborated with institutions like CNIT, ENEA, and international partners (e.g., University of South California)

• Combinatorial optimization
• Heuristic algorithms
• Scheduling
• +3 more

Marco Ghirardi is an Associate Professor in the Department of Management and Production Engineering (DIGEP) at Politecnico di Torino. His academic work focuses on Operations Research within the broader field of Mathematical and Computer Sciences. His research interests include: Combinatorial optimization Heuristic algorithms Scheduling Professor Ghirardi's work spans multiple domains including industrial automation, traffic systems, and robotics. His research applies mathematical optimization techniques to solve complex real-world problems in manufacturing, transportation, and rehabilitation engineering. His expertise in combinatorial optimization and heuristic algorithms has led to significant contributions in scheduling problems, network optimization, and control systems. His recent publications demonstrate a strong focus on applying operations research to diverse fields: Developing algorithms for fuel treatment scheduling Solving graph theory problems like the maximum happy vertices problem Creating robust traffic assignment models under uncertainty Designing control systems for rehabilitation robotics Professor Ghirardi actively participates in multiple research projects including: NOUS - A catalyst for EuropeaN ClOUd Services (2024-2026) as Research Group Member ESOPO - Exoskeleton for rehabilitation of lower limbs (since 2009) as Scientific Director Design of planning algorithms for production scheduling for SMEs (2022-2023) as Scientific Manager He teaches various courses across different degree programs including: Software architecture for automation Optimization for problem solving Operations Research Industrial Automation Laboratory Heuristics and Metaheuristics for Problem Solving at PhD level

David BoyceView profile

Adjunct Professor

• Metropolitan Transportation Planning
• Urban Travel Forecasting
• Transportation Network Modeling
• +3 more

David Boyce is an Adjunct Professor of Civil and Environmental Engineering at Northwestern University's McCormick School of Engineering. His expertise spans metropolitan transportation planning, urban travel forecasting models, and transportation network analysis. He holds a BS from Northwestern University, an MCP from the University of Pennsylvania, and a PhD in Regional Science from the University of Pennsylvania (1965). BS: Civil Engineering, Northwestern University (1961) MCP: City and Regional Planning, University of Pennsylvania (1963) PhD: Regional Science, University of Pennsylvania (1965) His research focuses on integrating transportation networks with land use, discrete choice theory, and entropy-based methods. Notable contributions include work on the TAPAS traffic assignment model and user-equilibrium route choice problems. Boyce has authored over 50 publications, emphasizing network equilibrium models, historical analyses of transportation theory, and policy applications. His articles highlight advancements in urban travel forecasting, multi-class models, and algorithmic solutions for traffic assignment. Recent work explores the historical foundations of transportation science and computational impacts on planning practices. Robert Herman Lifetime Achievement Award (2003) Fellows Awards from ASCE (2009), INFORMS (2003), and RSAI (2002) Boyce has advised on large-scale transportation projects and contributed to interdisciplinary teams advancing regional science. His research bridges theoretical models with practical urban planning challenges, emphasizing sustainable infrastructure and policy innovation.

Xiaoyu XiaView profile

Lecturer

• System Privacy and Security
• AI Privacy
• Parallel and Distributed Computing
• +4 more

Dr. Xiaoyu Xia is a Lecturer (equivalent to Assistant Professor in North America) in Cybersecurity & Software Systems at RMIT University's School of Computing Technologies. He received his PhD with the prestigious Alfred Deakin Medal from Deakin University, Australia, and has established himself as a leading researcher in distributed systems and cybersecurity with over 50 peer-reviewed publications in top-tier venues including IEEE S&P, ACM WWW, and IEEE Transactions. Dr. Xia's research spans critical areas at the intersection of computing and security: System Privacy and Security Distributed Systems and Edge Computing AI Privacy and Machine Learning Systems Sustainable Computing Cybersecurity and Privacy-Preserving Technologies His recent work demonstrates a clear trajectory toward developing practical privacy-preserving frameworks for emerging technologies, particularly in edge computing environments and large language models. Dr. Xia has made significant contributions to machine unlearning, secure data management in distributed systems, and energy-efficient edge computing solutions that balance performance with sustainability concerns. Dr. Xia has received notable recognition for his scholarly impact: World's Top 2% Scientists by Stanford University (2022-2024) Alfred Deakin Medal for PhD research excellence (2021) Teaching Excellence Award from Swinburne University of Technology (2021) As an active researcher, Dr. Xia currently leads multiple funded projects including an ARC Discovery Project grant worth over $500,000 for developing privacy-aware intelligent digital twins for secure critical infrastructures. He is open to supervising motivated PhD students with interests in system security and privacy, and distributed ML systems. Dr. Xia serves the academic community through editorial roles as Associate Editor for IEEE Transactions on Dependable and Secure Computing and as a Review Board Member for IEEE Transactions on Parallel and Distributed Systems, and regularly participates in program committees for major conferences including ACM WWW and IEEE ICDCS.

Tamás TettamantiView profile

Professor

• Road Traffic Control
• Intelligent Transportation Systems
• Traffic Simulation
• +3 more

Tamás Tettamanti is a Professor at Budapest University of Technology and Economics, serving as Deputy Head of the Department of Control for Transportation and Vehicle Systems. He holds a PhD (2013), Habilitation (2023), and DSc (2023) in Transportation Engineering, with expertise in road traffic modeling and control. 2007–2010: PhD Student 2010–2013: Assistant Lecturer 2014–2018: Senior Lecturer 2019–2024: Associate Professor 2025–present: Full Professor Education: High School Graduation (2001), DEUG (2004), MSc in Transportation Engineering (2007), Jazz Trumpet Graduate (2008) PhD (2013), Habilitation (2023), DSc (2023) Research focuses on road traffic modeling, intelligent transportation systems (ITS), autonomous vehicle integration, and emission-aware traffic control. His work bridges theoretical developments with real-world applications, including wireless traffic light systems and deep learning for urban mobility peaks. Scientific Awards: BME PhD Research Prize (2012) Literary Awards from Hungarian Scientific Association for Transport (2013, 2017, 2021, 2023) Bolyai János Research Scholarship (2017–2020) Michelberger Master Prize (2022) BME Jubilee Medal (2023) He has led major projects such as Dynamic Adaptive Traffic Control Services (2020–2024) and Deep Learning Anticipated Urban Mobility Peaks (DARUMA) (2021–2024), with industry collaborations including Google-BME Traffic Lab.

Maurice GagnaireView profile

Professor

• Optical Networks
• Cloud Computing
• Internet of Things (IoT)
• +7 more

Maurice Gagnaire is a Full Professor at Télécom Paris in the Computer Science and Networks (Infres) department, affiliated with the Networks, Mobility and Services (RMS) research team and the Information Processing and Communication Laboratory (LTCI). He has contributed extensively to optical network design, cloud computing, and network virtualization. Education: Engineering degree from Télécom SudParis, Master's in Computer Systems (Paris VI), Ph.D. (Télécom ParisTech), HDR (University of Versailles) Research Interests : His work focuses on translucent WDM networks , green networking , dynamic resource allocation , and physical layer impairments . Key projects include traffic grooming , failure detection , and energy-aware routing . Publications & Awards : He co-authored Springer's Traffic Grooming for Optical Networks and received the IBM Faculty Award 2014 . His research spans optical access systems , cloud brokering , and multi-layer traffic engineering . Scientific Honors: IBM Faculty award, Chevalier de l'Ordre des Palmes Académiques Academic Service : He served as expert for NSF (USA), IEEE, and ARCEP. His leadership includes coordinating the RMS research group and leading the Optimization and Networking Cluster.

Marc Jochen UetzView profile

Professor

• Operations Research
• Computer Science
• Artificial Intelligence
• +11 more

Marc Jochen Uetz is a Full Professor at the Mathematics of Operations Research department and affiliated with the Digital Society Institute. His research spans operations research and computer science, focusing on scheduling, game theory, and optimization problems. PhD in Mathematics from Technische Universität Berlin Research Interests: Active in algorithmic game theory and stochastic scheduling, he investigates equilibrium models, price of anarchy, and efficient resource allocation in transportation and network systems. His work contributes to UN Sustainable Development Goals related to education and infrastructure. Publication Trends: Recent work combines game theory with two-stage facility location, network routing, and stochastic scheduling of Bernoulli-type jobs. Key keywords include Nash equilibrium, approximation algorithms, and dynamic programming. Scientific Recognition: Excellent Reviewer Award (2017) Teaching Award (2018) Academic Activities: Currently chairs Platform Wiskunde Nederland, contributes to editorial work, and delivers invited talks at international conferences like IJCAI 2024.

• Control Engineering
• Networked Control Systems
• Multi-Agent Systems
• +6 more

Qinglong Han is the Pro-Vice Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology in Melbourne, Australia. He previously held academic and leadership roles at Griffith University and Central Queensland University. His research focuses on networked control systems, multi-agent systems, time-delay systems, smart grids, and unmanned vehicles. He is a Fellow of IEEE, IFAC, and multiple other institutions, and has received prestigious awards including the IEEE Dr.-Ing. Eugene Mittelmann Achievement Award (2024) and Norbert Wiener Award (2021). His research interests span control engineering, applied mathematics, and artificial intelligence. Notable contributions include secure platooning control for autonomous vehicles, resilient control under cyber-physical threats, and optimization of industrial systems. He leads editorial roles in journals like IEEE Transactions on Industrial Informatics and IEEE/CAA Journal of Automatica Sinica. His work emphasizes interdisciplinary applications in smart grids, robotics, and industrial automation. Dr. Han has supervised numerous PhD students in areas like networked control and vehicle dynamics. He has secured grants from ARC and NSFC for projects on networked control systems and renewable energy integration. His achievements include multiple best paper awards and recognition as a Clarivate Highly Cited Researcher in Engineering and Computer Science.

Otto Anker NielsenView profile

Professor

• Transport Modelling
• Public Transport
• Road Pricing
• +7 more

Prof. Otto Anker Nielsen is a Full Professor and Head of the Transport Modelling Division at the Technical University of Denmark (DTU), within the Department of Technology, Management and Economics. He specializes in transport modelling, with 27 years of expertise across passenger and freight transport, and has led over 55 projects at national and EU levels. His work focuses on route choice models, road pricing, public transport optimization, and sustainable mobility. Education: Ph.D. in Transport Modelling, DTU (1992–1994) M.Sc. in Civil Engineering, DTU (1987–1991) Research Management Education, Copenhagen School of Business (CBS) (2008) Research Interests: His research spans transport modelling methodologies, including dynamic traffic assignment, bicycle route choice, and integrated transport systems. He emphasizes sustainable development goals, electrification, and automation in transport. Recent work includes studies on transit-oriented development (TOD), travel time reliability, and crowdshipping optimization. Grants & Projects: Over the last five years, he has secured €9.5 million in grants, leading projects like Quantra (quantum computing in transport) and IPTOP (public transport optimization). He oversees DTU’s inter-departmental transport center and advises international transport models (e.g., Sweden, Norway). Awards: INFORMS Railway Application Section 2016 Student Paper Award (2016) Member of the Danish Academy of Technical Sciences Advising: Supervised 25 PhD students (14 since 2010), 100+ MSc, and 70+ BSc theses. Active in academic leadership, including editorial roles and international conference committees. Labs/Teams: Leads the Transport Modelling Division at DTU and collaborates with global institutions on projects like the European TransTools model. His team develops tools such as the OTM model and Copenhagen-Ringsted Transport Model.

• Real-Time Systems
• Parallel Computing
• Cyber-Physical Systems
• +3 more

Jing Li is an Assistant Professor at the Department of Computer Science in the Ying Wu College of Computing at New Jersey Institute of Technology. She holds a Ph.D. in Computer Science from Washington University in St. Louis (2017), advised by Chenyang Lu and Kunal Agrawal. Ph.D. in Computer Science, Washington University in St. Louis (2017) M.S. in Computer Science, Washington University in St. Louis (2014) B.S. in Computer Science, Harbin Institute of Technology, China (2011) Her research spans Real-Time Systems , Parallel Computing , Reinforcement Learning for System Design , and Scheduling Theory . Current projects include NSF-funded work on real-time systems with parallel resources and ARPA-E/IBM collaborations on reinforcement learning for converter design. Recent publications focus on AI-driven scheduling , parallel task optimization , and reinforcement learning applications in traffic control and circuit design. Key venues include AAAI, RTSS, PPoPP, and RTAS. Outstanding Achievement in Research (2022) Outstanding Paper Awards at RTSS (2018), RTAS (2016), ECRTS (2013) Turner Dissertation Award (2017) She advises graduate students in real-time systems and parallel computing, mentors NSF/ARPA-E projects, and leads professional services as TPC member and workshop organizer.

• UAV trajectory planning
• Autonomous systems
• Medical imaging
• +5 more

Xinwei Wang is a Professor at Nanjing University of Aeronautics and Astronautics with an extensive publication record spanning over two decades. Their research primarily focuses on autonomous systems, UAV trajectory planning, medical imaging, and computer vision applications. Wang has established significant collaborative networks with researchers including Yan Zhou, Liang Sun, Xichao Su, and Lei Wang across multiple Chinese institutions. Wang's research interests center on the intersection of robotics, artificial intelligence, and practical engineering applications. Their work demonstrates particular expertise in UAV coordination systems, medical diagnostic technologies, and underwater imaging solutions. Recent publications reveal a growing emphasis on explainable AI systems for medical applications and safety-critical trajectory planning for autonomous vehicles. The publication trends show a consistent output of high-impact research, with recent work increasingly focusing on practical implementations of AI systems in medical diagnostics, autonomous vehicle navigation, and aerospace applications. Wang's research bridges theoretical control systems with real-world engineering challenges, particularly in safety-critical domains requiring precise motion planning and reliable decision-making. Wang has contributed significantly to both theoretical frameworks in optimal control and practical implementations in medical imaging and autonomous systems. Their work on UAV cooperative task assignment and flight deck operations demonstrates strong connections to aerospace engineering applications, while medical imaging research shows interdisciplinary collaboration with healthcare professionals.

Rainer KolischView profile

Professor

• Airport Operations Management
• Health Care Operations Management
• Project Management and Scheduling
• +2 more

Rainer Kolisch is a Professor of Operations Management at the TUM School of Management, Technical University of Munich , where he has held a chair since 2002. He currently serves as Head of the Operations & Technology Department (since 2024) and previously as Dean of the QTEM Masters Network (2016–present) and Vice Dean of International Affairs (2007–2020). His career includes academic roles at Technical Universities of Dresden (Full Professor, 2002) and Darmstadt (Associate Professor, 1999–2002). Affiliations: TUM School of Management, Technical University of Munich Editorial Roles: Editor-in-Chief of OR Spectrum (2014–2020), Member of editorial boards for journals like International Journal of Production Research Research Interests focus on Airport Operations Management , Health Care Operations Management , Project Management and Scheduling , and Engineer-to-Order Manufacturing . His work addresses dynamic scheduling, resource allocation, and robust optimization in transportation and healthcare systems, with recent studies on electric vehicle charging networks and agile project management. Scientific Awards include: Best Teaching Award (2022) Excellence in Reviewing (2022) OMEGA Best Paper Award (2021) Handelsblatt Research Recognition (2005) DFG Habilitation Fellowship Advising spans numerous PhD and Master’s students , including Christopher Bersch, Robert Brachmann, and Giacomo Dall'Olio. His grants likely include DFG funding, though specifics are not detailed here.

• Transport Planning
• Traffic Simulation
• Intelligent Transport Systems (ITS)
• +3 more

Dr. Mark Raadsen is a Postdoctoral Research Fellow at the University of Sydney's Institute of Transport and Logistics Studies (ITLS) within the Business School. His research focuses on the supply side of transport, particularly dynamic/static traffic assignment methods, traffic flow theory, and algorithm design. He co-founded the open-source transport planning tool PLANit . Mark holds an MSc from Twente University (Netherlands) and a PhD from the University of Sydney. **Education:** MSc in Computer Science, Twente University, Netherlands PhD in Transport Planning, University of Sydney **Research Interests:** Combines academic rigor with practical applications, emphasizing aggregation/decomposition methods in multi-scale/multi-modal transport contexts. His work integrates sustainability aspects into transport models to aid policy-making. Key areas include variable speed limits, traffic simulation, and intelligent transport systems. **Teaching:** Contributes to courses such as Strategic Transport Planning, Traffic and Mobility Management, and Quantitative Methods in Transport. His teaching bridges theoretical frameworks with real-world applications. **Awards & Recognition:** While no explicit awards were listed, his work has led to commercial adoption and tangible impacts in transport systems globally. **Labs/Projects:** Co-lead of the PLANit project, an open-source platform for transport planning. His research has influenced both academic discourse and industry practices through models like the link transmission framework.