Find Academic Supervisors

• Transport Planning
• Urban Sustainability
• Data Analysis
• +5 more

Roles and Affiliations: Doina Olaru is a Professor in the Department of Management and Organisations at the University of Western Australia (UWA) Business School. She is affiliated with the Planning and Transport Research Centre and holds a visiting position at the University of Burgos, Spain. Her work focuses on transport planning, urban sustainability, and data-driven decision making. Education: PhD in Transport Engineering (University Politehnica of Bucharest, 2000). Prior industry experience includes roles as a railway engineer and Postdoctoral Research Scientist at CSIRO. Research Interests: Urban transport systems, travel behavior modeling, accessibility analysis, environmental impacts of transport, and applications of artificial intelligence. She emphasizes sustainable solutions integrating land-use and transport policies. Grants and Collaborations: Principal investigator on 31 grants, including ARC Linkage Projects and industry partnerships with iMOVE CRC. Collaborates with institutions like the University of Oxford, University of Leeds, and University of Sydney. Awards: Multiple teaching awards (UWA Business School) and recognition for contributions to transport research, including the Dennis Moore Australian Computer Society Orator honor. Teaching: Courses include Data Analysis and Decision Making, and Quantitative Data Analysis. Over 10 teaching excellence nominations. Current Projects: Focus areas include smart transport technologies, roundabout modeling via drone analytics, and hybrid work impacts on transport demand.

Cathy WuView profile

Associate Professor

• Reinforcement Learning
• Machine Learning
• Large-scale Optimization
• +6 more

Cathy Wu is the Class of 1954 Career Development Associate Professor in Civil and Environmental Engineering at MIT, affiliated with the Institute for Data, Systems, and Society (IDSS). Her research bridges machine learning, optimization, and urban systems, with a focus on mixed autonomy systems in mobility. She holds degrees from MIT (B.S., M.Eng in EECS) and a Ph.D. from UC Berkeley (EECS). Education: B.S. and M.Eng in Electrical Engineering and Computer Science, MIT (2012-2013) Ph.D. in Electrical Engineering and Computer Science, UC Berkeley (2018) Research Interests: Reinforcement Learning and Machine Learning Large-scale Optimization and Control Theory Mobility Systems and Urban Infrastructure Implications of AI and Automation Her work emphasizes interdisciplinary collaboration, involving transportation, computer science, and public policy. She founded the Interdisciplinary Research Initiative within the ACM Future of Computing Academy to advance cross-disciplinary computing research. Key Projects: Includes Flow (open-source RL framework for traffic control), eco-driving incentive mechanisms, and mixed autonomy traffic optimization. Her articles address congestion mitigation, autonomous vehicle integration, and scalable supervision strategies. Awards: Recipient of fellowships, best paper awards, and teaching honors (specific names unlisted). Engagement: Collaborations with institutions like Microsoft Research, OpenAI, and Caltrans. Active in policy-oriented initiatives and education through IDSS programs.

Kate WhitefootView profile

Associate Professor

• Sustainable Transportation
• Energy Policy
• Manufacturing Systems
• +5 more

Kate Whitefoot is an Associate Professor in Mechanical Engineering and Engineering and Public Policy at Carnegie Mellon University, with a courtesy appointment in the Heinz College. She leads the Whitefoot Research Group, focusing on sustainable technology development, adoption, and policy. Her roles include Associate Director of the Critical Technology Initiative and Fellow of the Wilton E. Scott Institute for Energy Innovation. She holds joint appointments in two departments and has affiliations with the NextManufacturing Center and the Manufacturing Futures Institute. Education: Ph.D., Design Science (Mechanical Engineering & Economics), University of Michigan (2011) M.S., Mechanical Engineering, University of Michigan (2008) B.S., Mechanical Engineering, University of Michigan (2006) Research Focus: Her work bridges engineering design and economics to address challenges in sustainable transportation, energy systems, and advanced manufacturing. Key areas include product design optimization, policy analysis for decarbonization, and the labor impacts of technological change. She collaborates with industry leaders in automotive, energy storage, and aerospace sectors. Awards & Recognition: Fellow of the Wilton E. Scott Institute for Energy Innovation National Academy of Engineering Frontiers of Engineering Program awardee Advising & Grants: Supervises a team of doctoral researchers and has advised numerous students now in academia and industry. Her grants include seed funding for clean hydrogen production and AI hardware efficiency. She leads initiatives on decarbonizing transportation and advises federal agencies like the Department of Energy. Labs & Partnerships: Director of the Whitefoot Research Group and a thrust leader at the NextManufacturing Center. Partners with AVL AST for advanced simulation technologies, enhancing research in automotive design and manufacturing systems.

• Road Safety
• Connected and Automated Vehicles
• Driver Behaviour
• +5 more

Evita Papazikou serves as a Lecturer in Transport Engineering at the School of Engineering, University of the West of England (UWE Bristol), where she contributes to the Centre for Transport and Society and collaborates with the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre. Her academic qualifications include: Civil Engineering (BEng and MEng) from Aristotle University of Thessaloniki MSc in Planning, Organisation, and Management of Transport Systems, Aristotle University of Thessaloniki PhD in Automated Systems and Driver Behaviour (Road Safety) from Loughborough University, sponsored by the Insurance Institute for Highway Safety with access to SHRP2 NDS data Dr. Papazikou's research focuses on road safety, connected and automated vehicles, driver behaviour analysis, and smart infrastructure. She investigates accident causation through statistical modeling, develops driver monitoring systems, and explores human factors in transportation. Her work integrates traffic simulation with mobility data fusion from vehicles, sensors, and infrastructure to enhance safety in future mobility systems, particularly in cooperative, connected, and automated environments. Her recent publications (2023-2025) reveal a concentrated research trajectory examining safety impacts of dedicated lanes for autonomous vehicles, parking policy implications in automated eras, and driver fatigue management. She consistently employs naturalistic driving data and traffic microsimulation to analyze driver-vehicle-environment interactions, with increasing emphasis on real-world intervention effectiveness and environmental sustainability in mobility systems. Scientific Awards: No specific awards were mentioned in the provided information. Dr. Papazikou has secured significant research funding through competitive programs including Horizon 2020, Innovate UK, and the Department for Transport. Her project portfolio demonstrates substantial industry collaboration, particularly with Ford, and includes: LEVITATE: Assessing societal impacts of Connected and Automated Vehicles SafetyCube: Developing an innovative road safety decision support tool i-DREAMS: Creating a smart driver and road environment assessment system DDRST: Building a data-driven road safety tool for hotspot identification TRIP: Developing a driver culpability assignment tool for road injury prevention She actively contributes to interdisciplinary research through her affiliations with the Centre for Transport and Society and the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre, where she bridges engineering, human factors, and policy development for next-generation transportation systems.

David AbbinkView profile

Professor

• Human-Robot Interaction
• Haptics
• Shared Control
• +7 more

Professor David Abbink is a Full Professor of Haptic Human-Robot Interaction at Delft University of Technology, holding a joint appointment between the Department of Cognitive Robotics in the Faculty of Mechanical Engineering and Industrial Design Engineering since November 2023. He founded the Delft Haptics Lab and co-founded the Cognitive Robotics Department in 2017. Abbink leads the transdisciplinary research and innovation centre FRAIM, which was awarded the prestigious NWO Stevin Premie (Dutch Nobel Prize equivalent) in June 2024. Trained as a mechanical engineer specializing in biomechanics, Abbink's research focuses on human behavior adaptations when interacting with autonomous systems. He has published over a hundred scientific articles on human-robot interaction, haptics, shared control, tele-operation, driver assistance systems, and sensorimotor control. His research has been funded by industry partners (Nissan, Boeing, Renault), RVO (Brightsky project 2022-2026), and the Dutch Science Foundation NWO through personal grants (VENI 2010-2014, VIDI 2015-2019). Abbink's recent work centers on worker-robot relations as an academic focus, collaborating with organizations like Erasmus Medical Centre for nursing work, Schiphol and KLM for baggage handling, and KLM Engine Repair Services for maintenance work. He also serves as scientific director for the Centre for Meaningful Human Control, launched in October 2024. His work bridges engineering, social sciences, and practical applications to responsibly shape the future of work with emerging robotic capabilities. NWO Stevin Premie (2024) Best IEEE SMC journal paper on Cybernetics (2019) Top 25 scientific talents according to New Scientist (2015) Best teacher of Faculty 3mE (2013, 2014) Best teacher of Department of BioMechanical Engineering (seven consecutive years) Abbink has supervised over 110 MSc students and 11 PhD students. His educational contributions include developing the Master Programme in Robotics at TU Delft and receiving international recognition for his course 'The Human Controller.' He is also a prominent science communicator, featured on national television, radio, and major Dutch newspapers, and has delivered lectures at venues like The Royal Institution and Lowlands Festival. Despite his academic commitments, Abbink maintains a drummer persona, having recorded four albums and performed over 400 shows across three continents between 1999-2014.

Andreas MalikopoulosView profile

Professor

• Cyber-Physical Systems
• Transportation Systems
• Control Theory
• +4 more

Andreas Malikopoulos is a Professor at Cornell University's School of Civil & Environmental Engineering and Director of the Information and Decision Science Lab (IDS Lab). Previously, he held roles as the Terri Connor Kelly and John Kelly Career Development Professor at the University of Delaware (UD) and founding Director of UD's Sociotechnical Systems Center. He also served as the Alvin M. Weinberg Fellow at Oak Ridge National Laboratory (ORNL), Deputy Director of ORNL's Urban Dynamics Institute, and Senior Researcher at General Motors R&D. His research focuses on cyber-physical systems (CPS), stochastic control, and learning-driven approaches for optimizing energy efficiency and sustainable mobility in smart cities and transportation systems. Education: PhD (Mechanical Engineering, University of Michigan, 2008), M.S. (Mechanical Engineering, University of Michigan, 2004), Diploma (National Technical University of Athens, 2000). Research Interests: Analysis and control of CPS, stochastic scheduling, game theory, and mechanism design applied to emerging mobility systems (e.g., autonomous vehicles, electric vehicles). He emphasizes integrating learning and control for socially optimal solutions in transportation networks. Awards: IEEE ITS Young Researcher Award (2019), UD’s Outstanding Junior Faculty Award (2020), Alvin M. Weinberg Fellowship (2010), and recognition as a NAS Kavli Frontiers of Science Scholar (2012). He is an IEEE Senior Member, ASME Fellow, and serves on editorial boards of leading journals. Teaching: Focuses on optimal decision-making, control theory, and emerging mobility systems. Courses include stochastic optimal control and game theory at Cornell. Labs: Leads the IDS Lab, which develops scalable frameworks for CPS and smart city applications. Current projects include coordinated routing for mixed-traffic systems and AI-driven recommendations for autonomous vehicles.

Jyh-Hone WangView profile

Professor

• Transportation Human Factors
• Driving Safety
• Intelligent Transportation Systems
• +5 more

Professor Jyh-Hone Wang holds a faculty position in the Department of Mechanical, Industrial and Systems Engineering at the University of Rhode Island (URI). His research focuses on transportation human factors, driving safety, and intelligent transportation systems, with particular emphasis on variable message sign (VMS) design, driver behavior analysis, and automation technology acceptance in elderly drivers. He has conducted studies on dynamic message sign efficacy, traffic flow management, and roadway safety improvement strategies. Education: Ph.D. and M.S. in Industrial Engineering from the University of Iowa (1989 and 1986), and B.S. in Industrial Engineering from Tunghai University, Taiwan (1980). Recent grants include a 2020 National Institute for Undersea Vehicle Technology grant (Co-PI) on stress monitoring via wearable devices, and a 2017 Rhode Island Department of Transportation grant (PI) assessing sidewalk quality compliance. His work bridges engineering principles with human factors to enhance traffic safety and transportation efficiency. Key research contributions include optimizing VMS message design for clarity, analyzing driver responses to automation levels, and addressing tailgating issues through behavioral interventions. He has advised multiple graduate students and collaborated on interdisciplinary projects involving traffic data analysis and manufacturing process optimization.

Atrisha SarkarView profile

Assistant Professor

• Human-centric multiagent systems
• Human-AI interaction
• Human-robot interaction
• +4 more

Atrisha Sarkar is an Assistant Professor in the Department of Electrical and Computer Engineering at Western University , Canada, and heads the Humans and Autonomous Agents Lab . She is also a faculty member of the Rotman Institute of Philosophy and a Faculty Affiliate at the Schwartz Reisman Institute for Technology and Society . Her research integrates empirical and behavioral game theory with software engineering to design human-centric AI systems that prioritize safety and societal well-being. Education: Atrisha holds a PhD and has previously served as a postdoctoral fellow at the Schwartz Reisman Institute for Technology and Society at the University of Toronto under the supervision of Prof. Gillian Hadfield. Research Focus: Her work centers on human-centric multiagent systems , combining methods from: Behavioral and empirical game theory Software engineering Human-AI and human-robot interaction AI safety and reliability She applies these to domains such as autonomous driving, cooperative AI, and social media dynamics, aiming to ensure AI systems align with human values and societal norms. Publications and Impact: Atrisha has published extensively in top-tier venues including AAAI , AAMAS , ICRA , NeurIPS , and EC . Her work spans from theoretical models of strategic behavior to practical frameworks for validating autonomous systems, with a strong emphasis on real-world applicability. Labs and Teams: She leads the Humans and Autonomous Agents Lab at Western University, where her team focuses on designing AI agents that can cooperate effectively with humans in complex, dynamic environments.

Otto LappiView profile

Research Fellow

• Cognitive Science
• Human Performance
• Gaze Control
• +3 more

Dr. Otto Lappi is a Research Fellow at the University of Helsinki's Department of Digital Humanities, Faculty of Arts. His work bridges cognitive science and human performance in complex dynamic tasks, particularly focusing on predictive processing in visuomotor control. PhD in Cognitive Science Title of Docent at University of Helsinki Academy Research Fellow (2020-2025) His research explores: Cognitive mechanisms in high-speed sports and driving Predictive gaze strategies and steering control Flow states in skill acquisition VR and eye-tracking applications in archaeomusicology Neural substrates of domain expertise Recent publications analyze: Flow-state dynamics in visuomotor learning Predictive gaze behavior in automated driving Computational models of attention in distracted driving Chunking mechanisms in high-speed sports performance Scientific contributions include: Academy Research Fellow (Research Council of Finland) Editorial work on high-performance cognition Organizing cognitive science workshops As doctoral supervisor, he has guided: Samuel Tuhkanen (Predictive Gaze and Steering) Jesse Kuokkanen (Mechanistic Computationalism) Ida Maasalo (Driver Behavior) Markus Mattsson (Psychometrics)

• Soil Biogeochemistry
• Carbon Cycling
• Mineral-Soil Interactions
• +3 more

Dr. Marion Schrumpf is a Group Leader in the Soil Biogeochemistry research group at the Max Planck Institute for Biogeochemistry, affiliated with the Department of Biogeochemical Processes. Her work focuses on soil carbon dynamics, mineral-organic matter interactions, and climate change impacts on soil systems. Research areas: Soil biogeochemistry, carbon cycling, mineral-soil interactions, nutrient stoichiometry, microbial ecology, and climate modeling. Email: mschrumpf@... Phone: +49 3641 57-6182 Office: B2.015 Her recent publications address themes like mineral control over soil carbon stabilization, drought effects on soil processes, microbial stoichiometric adaptation, and the Jena Soil Model's role in simulating carbon-nutrient interactions. She leads efforts to disentangle the complex relationships between land use, mineralogy, and soil organic matter turnover across diverse ecosystems.

Sanchayan BanerjeeView profile

Associate Professor

• Behavioral Economics
• Environmental Economics
• Experimental Economics
• +3 more

Sanchayan Banerjee is an Associate Professor of Economics & Public Policy at King’s College London’s Policy Institute, with a dual appointment as Visiting Professor at Grenoble-IAE (Université Grenoble Alpes). He previously held a tenured position as Assistant Professor of Environmental and Behavioral Economics at Vrije Universiteit Amsterdam (2022-2024). His research focuses on citizen-oriented, participatory behavioral public policies, tested through experiments in food, energy, health, and charitable policy domains. He co-developed the NUDGE+ framework emphasizing citizen agency in policy design. Affiliations: Visiting Fellow, London School of Economics Affiliate, Amsterdam Sustainability Institute & Institute for Environmental Studies Academic Lead for Professional Education, Policy Institute Research Interests: Behavioral economics, environmental economics, experimental methods, and policy effectiveness. His work bridges behavioral insights with real-world policy challenges, emphasizing participatory approaches and ethical considerations. Recent Article Trends: Recent work analyzes public support for pandemic policies, vaccine uptake drivers across G7 nations, and the ethical implications of behavioral nudges. He explores how experimental methods (field, lab, online) validate policy impacts while addressing equity concerns. Awards: Three consecutive LSE Teaching Awards Teaching Innovation Grants (VU Amsterdam) FHEA (UK Higher Education Academy Fellow) Grants & Leadership: Co-leads NWO ALIGN4energy (€5.7M), a Netherlands-based energy sustainability project. Serves on editorial boards for Scientific Reports , PLOS One , and Humanities & Social Sciences Communications . Previously co-edited Behavioral Public Policy ’s New Voices section. Labs/Teams: Leads King’s Policy Institute’s behavioral policy research group and collaborates across institutions on interdisciplinary projects like the NUDGE+ toolkit development.

Hao YangView profile

Assistant Professor

• Trustworthy Machine Learning
• Transportation Safety
• Transportation Equity
• +4 more

Hao Yang is an Assistant Professor in the Department of Civil and Systems Engineering at Johns Hopkins University, with dual affiliations at the Johns Hopkins Data Science and AI Institute and the Johns Hopkins Institute for Assured Autonomy. His research develops Trustworthy Machine Learning methods to enhance urban mobility systems, focusing on traffic safety, equity, and sustainability through ethical AI and human-machine cooperative systems. Yang earned dual bachelor's degrees in Electrical and Computer Engineering from Beijing University of Posts and Telecommunications and the University of London, followed by a Ph.D. in Civil Engineering (Transportation) from the University of Washington. His educational background bridges telecommunications, electrical engineering, and transportation systems. His research integrates spatio-temporal modeling, assured autonomous systems, and multimodal representation learning to address transportation equity and safety. Key projects include edge-AI-powered traffic surveillance, real-time crash identification, and cooperative signal assistance for vulnerable road users. His work emphasizes ethical AI deployment in cyber-physical infrastructure to create sustainable urban mobility solutions. Recent publications reveal a strategic shift toward large language models and multimodal AI for transportation challenges, with strong emphasis on explainability, reliability, and equity in traffic crash prediction, flow forecasting, and autonomous driving systems. This evolution demonstrates his commitment to adapting cutting-edge AI for real-world transportation problems. Yang's scientific contributions have earned significant recognition: Michael Kyte Outstanding Student of the Year Award (2022) High-Value Research Award from AASHTO (2022) Best Paper Award from TRB Information Systems Committee (2023) Best and Outstanding Dissertation Awards (2024) IEEE DTPI Outstanding Paper Award (2022) TRANSFOR22 Data Competition 2nd place (2022) ASCE Bridges Photo Contest First Place (2021) He actively mentors graduate researchers and seeks 2-3 PhD students for Fall 2025 to advance trustworthy AI in transportation. His research is supported by NSF, USDOT, and AASHTO grants including the Real-Time Truck Parking Information System project that received the High-Value Research Award. Current work focuses on edge-AI for traffic safety and multimodal data integration. Yang leads research within Johns Hopkins' Data Science and AI Institute and Institute for Assured Autonomy, collaborating with Transportation Research Board committees. His lab develops real-time perception systems using edge computing and representation learning, with active projects on non-motorized user safety and equitable traffic management for people with disabilities.

Dubravko RadicView profile

Professor

• Service Management
• Price Management
• Applied Microeconometrics
• +5 more

Dubravko Radic serves as Professor of Service Management at the University of Leipzig's Faculty of Business and Economics since 2009, while simultaneously holding the position of Deputy Head of the Price and Service Management group at the Fraunhofer Center for International Management and Knowledge Economics IMW since 2013. His academic career spans multiple institutions including the University of Wuppertal where he completed his habilitation, and the University of Frankfurt am Main where he earned his doctorate in statistics and econometrics. Doctorate (Dr. rer. pol. summa cum laude): Johann Wolfgang Goethe-Universität Frankfurt a.M. (2004) Habilitation: Bergische Universität Wuppertal (2009) Diplom-Volkswirt: Johann Wolfgang Goethe-Universität Frankfurt a.M. (1999) Research Stay: University of California Davis (2008) Professor Radic's research centers on the intersection of empirical methods and business management, with particular emphasis on service pricing modeling, applied microeconometrics, and social interactions in service contexts. His work bridges theoretical econometric approaches with practical business applications, especially in the healthcare sector where he has led multiple Fraunhofer IMW projects including ASARob, NurMut, and ATMoSPHÄRE. His research methodology combines quantitative modeling with real-world case studies to address strategic and operational decisions in service organizations. His recent publications demonstrate a consistent focus on discrete choice modeling, game theory applications in marketing, and service innovation frameworks. The 2025 paper "Discrete Games in Marketing Research" presented at the Global Marketing Conference in Hong Kong exemplifies his approach of applying advanced econometric techniques to practical marketing problems, particularly in digital service contexts. His work shows an evolving trajectory from foundational service management concepts toward increasingly sophisticated modeling of strategic interactions in service markets. Professor Radic has extensive experience advising major corporations including Metro AG, Lilly Deutschland, IMS Health, Berlin Chemie, and Augustinum gGmbH. His practical projects at Fraunhofer IMW focus on translating academic research into actionable business solutions, particularly in healthcare digitization and service innovation. He has led the TRAIN@MINE project developing training tools for Vietnam's mining sector and contributed to studies on Big Data applications in health insurance. At the University of Leipzig, he leads research activities through the Institute for Service and Relationship Management, supervising multiple research projects that connect academic inquiry with industry applications. His team collaborates with international partners including the University of California Davis, University of Maryland, Northwestern University, and the Technion Israel Institute of Technology, creating a robust research ecosystem focused on service management innovation.

Zhibin ChenView profile

Assistant Professor

• Transportation Network Modeling and Optimization
• Intelligent Transportation Systems
• Discrete Optimization
• +4 more

Zhibin Chen is an Assistant Professor of Engineering at NYU Shanghai and concurrently a Global Network Assistant Professor within the broader New York University system. Since January 2019 he has led research and teaching activities at the Division of Engineering and Computer Science in Shanghai, while maintaining university-wide collaborations through his Global Network appointment. Education Ph.D. in Transportation Engineering, University of Florida (2017) Research Interests Dr. Chen’s scholarship centres on Transportation Network Modeling and Optimization , Intelligent Transportation Systems , and Discrete Optimization . He integrates operations research, data science, and engineering to address emerging challenges in electric mobility, autonomous vehicles, and large-scale urban networks. Recent thrusts include: Data-driven analytics of electric-vehicle charging behaviour under usage heterogeneity. Optimization of charging and swapping infrastructure for electric buses and trucks. Network-level deployment and control strategies for connected and automated vehicles. Day-to-day traffic dynamics and equilibrium models with elastic demand. Pricing, policy, and incentive design for sustainable transportation systems. Scientific Awards Stella Dafermos Best Paper Award – awarded at the 95th Transportation Research Board Annual Meeting. Ryuichi Kitamura Paper Award – also conferred at the 95th TRB Annual Meeting. Editorial & Professional Service Dr. Chen currently serves on the Editorial Advisory Board of Transportation Research Part C: Emerging Technologies , shaping the editorial direction of the leading journal in his field. Grants & Collaborations While specific grant identifiers are not disclosed in the provided text, Dr. Chen’s extensive publication record in top-tier journals ( Transportation Science , Transportation Research Parts B, C, D , IEEE ITS , Applied Energy ) and his editorial role indicate sustained research funding and active collaboration with international partners across North America and China. Laboratories & Teams Operating within the Division of Engineering and Computer Science at NYU Shanghai , Dr. Chen leads a research group focused on next-generation mobility analytics, leveraging the university’s interdisciplinary ecosystem and NYU’s Global Network resources to advance smart and sustainable transportation.

Craig HancockView profile

Research Professor

• Geospatial Engineering
• Structural Health Monitoring
• Global Navigation Satellite Systems (GNSS)
• +3 more

Dr. Craig Hancock is a Research Professor in Geospatial Engineering with 15 years of research experience in Surveying and Geodesy. His expertise spans GNSS error mitigation, structural monitoring, and geospatial techniques for digital construction. He has supervised 10 PhD students and published over 80 academic papers. Education: BSc and PhD in Surveying/Geomatics Key Projects: Principal Investigator for projects on GNSS error mitigation, structural health monitoring, and marine economy technology. His research focuses on three core areas: GNSS error categorization and mitigation (particularly ionospheric effects), structural and environmental change monitoring, and geospatial data acquisition for BIM and digital construction. Recent work includes improving 3D modeling accuracy, UAV-based GNSS spoofing detection, and BIM-enabled facility management in healthcare infrastructure. His articles explore topics like sensor optimization, structural dynamics, and geospatial data fusion. Grants include £150k for bridge deformation studies and £9k for ionospheric error analysis. He actively contributes to teaching and enterprise initiatives, integrating geospatial technologies with industry needs.