Find Academic Supervisors

Moshe E. Ben-AkivaView profile

Professor

• Transportation Systems Analysis
• Intelligent Transportation Systems
• Demand Modeling
• +6 more

Moshe E. Ben-Akiva is the Edmund K Turner Professor at the Massachusetts Institute of Technology (MIT), affiliated with the School of Engineering and the Department of Civil and Environmental Engineering. He holds a B.S. from Technion-Israel Institute of Technology (1968), and M.S. and Ph.D. degrees in transportation systems from MIT (1971, 1973). His research focuses on transportation systems analysis, intelligent transportation systems, demand modeling, econometrics, and infrastructure management. He has been recognized with prestigious awards, including election to the National Academy of Engineering (2025) for contributions to transportation systems modeling and demand analysis. His work spans theoretical and applied domains, including agent-based microsimulation for freight logistics, tradable credit schemes for congestion management, and behavioral dimensions of transport decarbonization. Ben-Akiva collaborates with industry and policymakers to design sustainable mobility solutions. His notable publications include foundational texts on discrete choice analysis and stated preference elicitation. He advises on transportation policy, urban planning, and emerging mobility technologies such as automated vehicles and urban air mobility. Current research explores impacts of automated mobility-on-demand systems, real-time tolling strategies, and e-commerce delivery demand modeling. His team develops tools like SimMobility Freight, an agent-based urban freight simulator. He remains active in teaching, focusing on demand modeling and econometrics courses at MIT.

Eugene O'BrienView profile

Professor

• Structural Engineering
• Bridge Safety Assessment
• Traffic Load Modeling
• +2 more

Professor Eugene O'Brien serves as Professor of Civil Engineering within the School of Civil Engineering at University College Dublin's College of Engineering and Architecture. His research focuses on critical structural assessment methodologies for long-span bridges, with particular expertise in traffic load modeling and bridge safety evaluation. His research interests center on structural engineering challenges related to bridge infrastructure, specifically traffic load assessment for long-span bridges , structural health monitoring systems , and sustainable infrastructure management . Professor O'Brien pioneered camera-based monitoring techniques to overcome limitations of traditional Weigh-in-Motion sensors during congested traffic conditions, enabling more accurate safety assessments of aging bridge infrastructure. His work addresses the critical gap in quantifying traffic loading on bridges with spans up to 2 kilometers, where conventional methods fail during stop-and-go traffic scenarios. Analysis of his 15 most recent publications reveals a consistent research trajectory focused on probabilistic modeling of traffic loads, with increasing sophistication in handling extreme events and long-term infrastructure performance. His work spans fundamental statistical methods for load effect prediction, practical applications in real-world bridge assessments, and environmental considerations regarding infrastructure carbon footprints. The research demonstrates strong methodological evolution from basic traffic modeling to comprehensive lifetime assessment frameworks incorporating sustainability metrics. As co-founder and director of Roughan O'Donovan's subsidiary Innovative Solutions (ROD-IS), Professor O'Brien has translated research into practice through significant projects including the Malahide Railway Viaduct assessment (2009), EU-funded bridge lifespan simulation tools (2011), vibration reduction systems for bridge cables, and structural assessments for major international projects including the Ting Kau Bridge in Hong Kong, the Forth Road Bridge in Scotland, and the Chacao Channel Bridge in Chile. His consultancy work demonstrates direct application of academic research to critical infrastructure challenges worldwide. Professor O'Brien's research group operates at the intersection of structural engineering and sustainable infrastructure management, with particular emphasis on extending bridge service life through accurate safety assessment. Their work on the Chacao Channel Bridge demonstrates practical implementation of traffic monitoring systems using toll data to manage truck loads, while their environmental impact analysis shows how accurate safety assessments reduce unnecessary bridge replacements, thereby lowering the carbon footprint of transportation infrastructure through extended service life of carbon-intensive materials like concrete and steel.

Gary KingView profile

Professor

• Political Methodology
• Statistical Inference
• Quantitative Social Science
• +7 more

Gary King is the Albert J. Weatherhead III University Professor at Harvard University and Director of the Institute for Quantitative Social Science. He is based in the Department of Government within Harvard's Faculty of Arts and Sciences. One of only 22 University Professors at Harvard, this represents the institution's most distinguished faculty position. King received his B.A. from SUNY New Paltz in 1980 and his Ph.D. from the University of Wisconsin-Madison in 1984. His academic journey has led him to become one of the most influential scholars in political methodology and quantitative social science. Professor King's research spans numerous areas of methodological innovation in the social sciences. His work focuses on developing and applying empirical methods across various domains. Key research interests include: Ecological Inference - developing methods to infer individual behavior from group-level data Automated Text Analysis - creating techniques for extracting knowledge from massive text collections Causal Inference - methods for detecting and reducing model dependence in causal effect estimation Missing Data and Measurement Error - statistical approaches to handle incomplete or imperfect data Survey Research - developing methods for more accurate cross-cultural survey comparisons Unifying Statistical Analysis - integrating diverse methodological approaches into coherent frameworks King's recent publications demonstrate a continued focus on methodological innovation with practical applications. His work spans political science, public health, and data science, with particular emphasis on privacy-preserving data analysis, maternal health metrics, survey methodology, and media effects. A notable trend is the increasing interdisciplinary nature of his research, bridging political methodology with public health, computer science, and demography. His work on census data privacy, maternal mortality disparities, and media influence represents cutting-edge applications of social science methodology to critical societal issues. His scientific achievements have been recognized with numerous prestigious awards: Fellow of the National Academy of Sciences (2010) Fellow of the American Statistical Association (2009) Fellow of the American Academy of Arts and Sciences (1998) Guggenheim Foundation Fellow (1994-1995) Career Achievement Award (2010) Warren Miller Prize (2008) Multiple awards for research software and methodology King has mentored numerous students and postdocs, many of whom now hold faculty positions at leading universities. His research has been supported by major funding agencies including the National Science Foundation, Centers for Disease Control and Prevention, World Health Organization, and National Institute of Aging. He has collaborated with over seventy scholars on research publications and served on numerous editorial boards and professional organization councils. His work on the Mexican universal health insurance program represents one of the largest randomized health policy experiments to date, demonstrating his commitment to rigorous evaluation of real-world policy interventions. As Director of the Institute for Quantitative Social Science, King leads a vibrant research community focused on methodological innovation. His work has practical applications in diverse areas including legislative redistricting (used by the U.S. Supreme Court), health policy evaluation (including the largest randomized health policy experiment to date in Mexico), Chinese censorship analysis (revealing government fabrication of 450 million social media comments annually), and automated text analysis (through Crimson Hexagon, a company he co-founded).

Matti MarklundView profile

Assistant Professor

• Nutrition
• Public Health
• Cardiometabolic Epidemiology
• +7 more

Matti Marklund is an Assistant Professor at the Bloomberg School of Public Health , Johns Hopkins University , with additional appointments at The George Institute for Global Health (Australia) and Uppsala University (Sweden). He holds a PhD in Food Science from the Swedish University of Agricultural Sciences (2012) and an MSc in Engineering Biotechnology from Umeå University (2007). His research focuses on nutrition and public health , particularly diet-disease relationships , cardiometabolic epidemiology , and food policy . Key areas include sodium and potassium intake , trans-fatty acids , dietary fat quality , and cost-effectiveness analysis of global health interventions. He has led studies on salt substitution , food pricing policies , and hypertension management . His 15 most recent publications (2025–2019) cover topics such as trans-fatty acid biomarkers in Nigeria , price elasticity of food in Australia , hypertension treatment modeling in India , and diabetes risk from fatty acid intake . These works integrate modeling , cohort studies , and systematic reviews across public health , cardiovascular medicine , and nutritional epidemiology . Scientific awards include: 2022 & 2021: Paul Dudley White International Scholar Award, American Heart Association 2017 & 2016: Dr. P Håkansson’s Foundation Research Award His work has been cited over 3,000 times and referenced in 25 policy documents (WHO, World Bank). He has collaborated with institutions in Kenya , Nigeria , India , and Bangladesh for global health interventions .

Joyoung LeeView profile

Associate Professor

• Connected Vehicle (CV) Systems
• Traffic Management
• Autonomous Vehicle Control
• +5 more

Dr. Joyoung Lee is an Associate Professor in the Department of Civil and Environmental Engineering at New Jersey Institute of Technology (NJIT). He previously served as Laboratory Manager at the Federal Highway Administration's Saxton Transportation Operations Laboratory. His research focuses on Connected Vehicle (CV) systems, including applications in traffic management, signal control optimization, and autonomous vehicle infrastructure integration. Dr. Lee holds a Ph.D. (2010) and M.S. (2007) in Transportation Engineering from the University of Virginia, and a B.S. (2000) in Transportation Engineering from Hanyang University. His work emphasizes CV-based solutions for real-time traffic systems, cooperative vehicle-infrastructure systems (CVIS), and autonomous vehicle integration. Notable achievements include the 2019 IEEE CAVS Best Paper Award and multiple best paper recognitions from PTV User Group Meetings. His research also addresses traffic safety through innovations like the Virtual Guide Dog system for visually impaired pedestrians and advanced traffic monitoring frameworks using LiDAR and computer vision. Education: Ph.D., Transportation Engineering, University of Virginia (2010) M.S., Transportation Engineering, University of Virginia (2007) B.S., Transportation Engineering, Hanyang University (2000) Dr. Lee's research interests span smart city infrastructure, edge computing for traffic systems, and sustainable transportation solutions. He has pioneered algorithms for cooperative intersection management, automated platooning systems, and federated learning-based traffic optimization. His work bridges theoretical models with real-world implementation through partnerships with FHWA and industry stakeholders. Key contributions include development of the Cumulative Travel-Time Responsive (CTR) traffic signal control system, smart arrival notification systems for paratransit services, and advanced microsimulation calibration techniques. His lab focuses on translating CV data into actionable strategies for safer, more efficient transportation networks. Awards: IEEE CAVS Best Paper Award (2019) ASCE Grand Challenge Innovation Contest Honorable Mention (2017) PTV VISSIM Best Paper Awards (2012, 2008) Excellence in Research Award (University of Virginia, 2011) Ongoing projects include semi-decentralized graph neural networks for traffic forecasting and low-cost LiDAR-based traffic monitoring systems. His work addresses critical challenges in autonomous vehicle integration, incident management, and infrastructure resilience through interdisciplinary collaborations.

• Transport Modelling
• Economic Analysis of Transport
• Sustainable Transportation
• +3 more

Anders Karlström is a Professor at KTH Royal Institute of Technology, specializing in Transport Modelling and Economics. His research focuses on sustainable transportation systems, emissions reduction, and energy efficiency. Key interests include activity-based modelling, dynamic discrete choice frameworks, and policy analysis for urban mobility. He has contributed to studies on travel behavior, infrastructure planning, and environmental impacts of transport systems across multiple international cities. His work integrates advanced methodologies such as recursive logit models, spatial regression, and machine learning for predictive analytics. Notable research areas involve evaluating weather variability effects on travel patterns, optimizing traffic state estimation with sensor data, and developing scenario-based models for future employment growth. Karlström collaborates with industries to enhance the competitiveness of sustainable transport solutions globally.

• Sustainable Transportation Systems
• Shared Mobility
• Public Transit Planning
• +7 more

Dr. XiaoYue Cathy Liu is an Associate Professor in the Department of Civil & Environmental Engineering at the University of Utah. She holds a PhD in Transportation Engineering from the University of Washington and advanced degrees in Transportation Planning and Electronics Engineering. Her research focuses on sustainable transportation systems, shared mobility, public transit optimization, managed lanes, and intelligent transportation systems. She actively serves on committees including the Transportation Research Board's Highway Capacity Quality of Service (HCQS) Committee and chairs its Technology Transfer Subcommittee. She also advises the Utah Model Advisory Committee and previously served on Salt Lake City’s Transportation Advisory Board. Dr. Liu is a licensed professional engineer in Utah. Education: PhD, Transportation Engineering, University of Washington (2013) MA, Transportation Planning & Management, Texas Southern University BS, Electronics & Electrical Engineering, Beijing Jiaotong University Graduate Certificate, Global Trade & Logistics, University of Washington (2011) Research Interests: Electric vehicle infrastructure and charging networks Smart transportation systems and agent-based modeling GIS-based asset management for transportation infrastructure Snowplowing operations optimization and winter maintenance Managed lanes and high-occupancy toll (HOT) lane analysis Public transit equity and accessibility Her recent publications emphasize data-driven approaches to transportation challenges, including EV demand forecasting, drone delivery networks, and resilience in interdependent transit systems. She collaborates on projects addressing Utah’s unique transportation needs, such as optimizing snowplow routes and integrating renewable energy into public transport systems. Professional Contributions: Board member, Utah Model Advisory Committee Former Chair, Salt Lake City Transportation Advisory Board (2013-2016) TRB Managed Lane Committee member TRB Transit Capacity & Quality of Service (TCQS) Committee member (2016-2019) Dr. Liu’s work bridges transportation engineering with computational methods, focusing on equity, sustainability, and operational efficiency. She leads research initiatives involving large-scale modeling, geospatial analytics, and interdisciplinary solutions for modern mobility challenges.

• Automated Transportation Systems
• Connected Vehicles
• Electric Vehicles
• +3 more

Dr. Xiaopeng Li is the Harvey D. Spangler Professor in the Department of Civil and Environmental Engineering at the University of Wisconsin-Madison, with an affiliation in the Department of Electrical and Computer Engineering. He leads the USDOT Rural Autonomous Vehicle Program and previously directed the National Institute for Congestion Reduction. He earned his B.S. in Civil Engineering from Tsinghua University (2006), M.S. in Civil Engineering (2007), M.S. in Applied Mathematics (2010), and Ph.D. in Civil Engineering (2011) from the University of Illinois at Urbana-Champaign. His research focuses on modeling and field experiments for connected, electric, and automated vehicles (CAVs), infrastructure systems analysis, and interdependent network modeling. He has pioneered physics-enhanced machine learning frameworks for vehicle control and developed simulation tools for CAV deployment. His 2025-2024 publications highlight advancements in Connected vehicle trajectory modeling Energy consumption optimization Edge computing for autonomous operations Residual learning control systems Equity analysis in AV deployment Communication technologies for V2X Awards include: TRB Best Paper Award (2025) NSF CAREER (2015) ASCE Fellow (2024) IEEE Senior Member (2022) Multiple institution-specific fellowships He has advised 15+ graduate students, secured $35M+ in grants from NSF, USDOT, and industry partners, and chairs the IEEE ITSS Emerging Transportation Technology Testing committee. His work addresses real-world AV implementation, safety validation, and sustainable transportation systems.

Olivia AdairView profile

Researcher

• Health Economics
• Colorectal Cancer Screening
• Cost-Effectiveness Analysis
• +3 more

Olivia Adair is a researcher in the School of Mathematics and Physics , focusing on health economics and colorectal cancer screening. Her work integrates microsimulation modeling, systematic reviews, and cost-effectiveness analysis to evaluate public health policies in Northern Ireland and internationally. Research Trends : Her recent publications emphasize comparative modeling methods, economic evaluations of screening programs, and systematic reviews of healthcare interventions. Key themes include cost-effectiveness , population-specific screening , and health policy validation . Scientific Awards : William and Betty MacQuitty Travel Scholarship (2023) Grants & Collaborations : She collaborates with experts like Dr. Felix Lamrock, Professor Mark Lawler, and Dr. Emma McFerran, focusing on regional cancer screening challenges. Her thesis project highlights interdisciplinary teamwork in healthcare modeling.

• 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.

Gina Crocenzi (Masterson)View profile

Professor

• French Literature
• Literary Theory
• 20th Century Philosophy
• +5 more

Gina Crocenzi (Masterson) serves as a Professor in the Department of Modern and Classical Languages at George Mason University, teaching French literature and related disciplines. She maintains prior faculty appointments at Georgetown University and Princeton University, with active teaching responsibilities confirmed for Fall 2025 courses. Her academic foundation includes a summa cum laude B.A. in Philosophy/History from Georgetown University and a Ph.D. in Modern French Literature and Literary Criticism from the Catholic University of America. Professional certifications encompass Hybrid Learning (American University, 2018) and Online Instruction (NOVA, 2020). Research spans dual domains: French literary studies focusing on Kristeva, Bachelard, 20th-century philosophy, and theology; alongside computational geospatial work in traffic simulation and ZIP code systems. This unusual interdisciplinary range reflects publications in both humanities (e.g., Literature and the Science of the Unknowable ) and computer science venues. Scientific recognition includes: Excellence in Teaching Award, Northern Va Community College, Office of the Dean (Spring 2021) No verifiable information exists regarding graduate student mentorship, research grants, or laboratory leadership. Her professional background additionally incorporates international business project management within the US federal government.

Michael GerfinView profile

Professor

• Health Economics
• Labor Economics
• Public Policy
• +3 more

Prof. Dr. Michael Gerfin is a Professor of Public Economics at the University of Bern, affiliated with the Center for Regional Economic Development (CRED). His research focuses on health economics, labor economics, and tax-benefit models. He holds an office at A315 and can be reached via email. His work examines topics such as healthcare demand, physician incentives, and policy design, with recent contributions analyzing drug pricing, pandemic response strategies, and educational interventions in developing countries. Key themes in his publications include understanding how financial mechanisms influence provider behavior and designing effective social policies. Gerfin's research spans empirical studies on healthcare utilization, wage dynamics, and household decision-making. His analysis often integrates microsimulation techniques to evaluate policy impacts, such as in-work benefits and active labor market policies. Collaborations with Swiss statistical agencies highlight his engagement with real-world data, such as studies on adverse healthcare events and nursing staff ratios. His work bridges theoretical economic models with practical policy applications, emphasizing evidence-based solutions for public welfare challenges. Labs/Teams: Core member of the Center for Regional Economic Development (CRED), contributing to interdisciplinary projects on regional economic trends and public policy evaluation.

Yogi VidyattamaView profile

Associate Professor

• Spatial Microsimulation
• Economic Growth
• Income Distribution
• +5 more

Yogi Vidyattama is an Associate Professor at the Canberra School of Politics, Economics and Society, University of Canberra. He specializes in spatial microsimulation modeling, economic growth, income distribution, and fiscal decentralization. Previously affiliated with the University of Indonesia, he contributed to regional economic analysis in Indonesia. His research focuses on linking economic policies with spatial outcomes, including corruption determinants, healthcare access, and disaster resilience. Education: PhD in Patterns of Provincial Economic Growth from Australian National University (2008), Master's from ANU (2003), and Bachelor's in Fiscal Decentralisation from University of Indonesia (2000). Research interests include microsimulation modeling, regional economic disparities, and policy impacts. He has led 49 projects, including studies on electric vehicle policy, disaster capability mapping, and regional fast rail economic impacts. His work contributes to UN SDGs related to economic growth, inequality reduction, and disaster resilience. Publications span over 117 outputs, analyzing topics like Indonesia's regional corruption, Australian housing crises, and pandemic policy effects. Awards and recognitions are unspecified, but his roles in executive councils of ANZRSAI and PRSCO highlight peer recognition. Advised 10 students and maintains NATSEM's spatial models and GIS systems.

Alisa TazhitdinovaView profile

Associate Professor

• Public Economics
• Tax Policy
• Econometrics
• +3 more

Alisa Tazhitdinova is an Associate Professor of Economics and Faculty Research Fellow at the National Bureau of Economic Research (NBER), affiliated with the University of California, Santa Barbara (UCSB). As Principal Investigator at the UCSB Public Finance Lab, her research focuses on public economics, tax policy design, and behavioral responses to taxation. Associate Professor | Department of Economics, UCSB Faculty Research Fellow | National Bureau of Economic Research (NBER) Principal Investigator | UCSB Public Finance Lab Research Interests: State and federal tax policy determinants Behavioral responses to taxation (capital gains, moonlighting, social insurance) Corporate political spending influence Value-added tax effects on international trade Policy evaluation methodologies Public finance empirical analysis Scientific Contributions: Her work spans 7 years of publications in top journals like Journal of Public Economics and Review of Economics and Statistics , covering tax reforms, behavioral economics, and policy evaluation. She has authored 6 NBER working papers addressing tax policy drivers, moonlighting dynamics, and VAT trade implications. Awards: 2016 IIPF Peggy and Richard Musgrave Prize Collaborations: Frequent collaborations with scholars like Sarah Robinson, Cailin Slattery, and Gonzalo Vazquez-Bare across disciplines including public economics, econometrics, and political economy.

Eugene VinitskyView profile

Assistant Professor

• Reinforcement Learning
• Multi-agent Learning
• Autonomous Vehicles
• +2 more

Eugene Vinitsky is an Assistant Professor at NYU Tandon School of Engineering, holding joint appointments in Civil and Urban Engineering and Computer Science. His research develops multi-agent reinforcement learning systems for autonomous vehicles and traffic control, with applications in robotics and intelligent infrastructure. He directs the Computational Transportation Systems Lab and leads projects like CIRCLES on congestion reduction. Research Focus: Designs algorithms enabling complex behaviors through unsupervised agent interactions, human-AI compatibility, and environment synthesis for autonomous systems. Awards & Leadership: NSF Graduate Fellow (2016), Eisenhower Fellow (2018, 2020), and PI on multiple grants including Amazon Research Awards. Mentored 14+ graduate students and organized international RL conferences.