Zhe Liu is an Assistant Professor in the Analytics & Operations group at Imperial College Business School, where he also serves as PhD Director. He holds a PhD in Operations Management from Columbia Business School and a BS in Industrial Engineering from Tsinghua University. His research focuses on revenue management and supply chain optimization, with specialized interests in sharing economy platforms and multi-sourcing strategies. Liu's work examines operational challenges in modern business environments through mathematical modeling, including queueing systems, pricing optimization, and risk management in volatile supply chains. His publications demonstrate consistent themes in platform operations, stochastic optimization, and behavioral interactions within multi-agent systems. Recognized with numerous honors, Liu received the 1st Place Service Science Best Cluster Paper Award (2024), 2nd Place CSAMSE Best Paper Award (2024), and was a finalist in the George Nicholson Student Paper Competition. He actively mentors PhD students and serves as judge for international paper competitions and conference program committees.
Hua Cai is the Thomas and Jane Schmidt Rising Star Associate Professor at Purdue University's Edwardson School of Industrial Engineering with a joint appointment in Environmental & Ecological Engineering. She holds a PhD in Environmental Engineering & Natural Resources from the University of Michigan, an MS in Environmental Engineering from Penn State, and a BS from Tsinghua University. Her research integrates operations research and production systems to address sustainability challenges, with focus areas including: Environmental implications of emerging technologies Urban sustainability modeling and infrastructure resilience Industrial ecology and complex adaptive systems Sustainable transportation and mobility systems Recent publications demonstrate strong focus on sustainable transportation systems, with extensive analysis of shared mobility patterns (bike/e-scooter systems), autonomous vehicle impacts, and microgrid resilience. Her work consistently applies advanced computational methods including reinforcement learning, agent-based modeling, and spatiotemporal analysis to urban sustainability challenges. Dr. Cai has received recognition including the Thomas and Jane Schmidt Rising Star Professorship for her contributions to sustainable systems engineering. She leads research on renewable energy integration in transportation infrastructure and advises projects on climate-resilient urban systems.
Omar Rifki is an Associate Professor (Maître de Conférences) specializing in combinatorial optimization and artificial intelligence applications. His research bridges theoretical computer science with practical logistics challenges, focusing on routing problems, process mining, and machine learning integration for complex decision systems. His core research interests include phase transitions in NP-hard problems, vehicle routing optimization under time constraints, and healthcare process modeling. Rifki's work demonstrates a consistent pattern of integrating reinforcement learning with traditional optimization techniques to solve large-scale real-world problems in transportation and logistics, with particular emphasis on spatio-temporal data effects and collaborative systems. Analysis of his 15 publications (2019-2025) reveals three dominant research thrusts: (1) Fundamental studies of combinatorial problem hardness using phase transition frameworks, (2) Practical applications of deep reinforcement learning in vehicle routing and taxi assignment, and (3) Healthcare process optimization through advanced process mining techniques. His work consistently addresses scalability challenges in real-world implementations while maintaining theoretical rigor. No scientific awards were documented in the provided materials. His collaborative work with researchers like Christine Solnon and Thierry Garaix indicates active participation in European operations research communities, though specific grant details remain unreported. Rifki's research shows increasing integration of graph theory and machine learning in transportation applications, particularly evident in his Lyon City case studies on autonomous ride-sharing systems.
Tridas Mukhopadhyay is the Deloitte Consulting Professor of e-Business at Carnegie Mellon University's Tepper School of Business, where he has served on the faculty since 1986. His academic journey at CMU progressed from Instructor of Information Systems (1986-1987) to Assistant Professor (1987-1993), Associate Professor (1993-1997), Professor (1998-present), and Deloitte Consulting Professor of e-Business (2000-present). He also served as Director of the MS in Electronic Commerce program from 1999-2004. Ph.D. in Computer and Information Systems, University of Michigan–Ann Arbor, 1987 M.B.A. in Computer and Information Systems, Indian Institute of Management Calcutta, 1981 B. Tech. in Electrical Engineering, Indian Institute of Technology Kharagpur, 1978 Professor Mukhopadhyay's research spans multiple critical areas in information systems and technology management. His work on strategic IT use examines how organizations derive business value from information technology investments. He has conducted extensive research on business-to-business commerce, particularly focusing on e-procurement systems, web-based marketplaces, and electronic intermediation models. His cybersecurity research investigates the economic aspects of cyber security, including liability mechanisms and patch release strategies. In software engineering, he has studied productivity, quality metrics, and offshore software development contracts. His most recent publications reveal several key trends in his research trajectory. There's a growing focus on digital platform economics, examining advertising models, virtual currency systems in gaming, and sharing economy dynamics. His work increasingly incorporates behavioral aspects, studying how users respond to personalized content and how backers exert control in crowdfunded projects. Methodologically, his research employs sophisticated analytical approaches including hierarchical Bayesian models, structural equation modeling, and natural experiment designs. CART Research Frontier Award, Carnegie Mellon, 2005 Distinguished Ph.D. Alum, Michigan Business School, 2004 Best Paper, International Conference on Information Systems, 2001 Best Paper, MIS Quarterly, 1995 Xerox Research Chair, Tepper School of Business, 1988-1989 Information Systems Society Distinguished Fellow, 2012 Professor Mukhopadhyay has served on numerous editorial boards including Information Systems Research (1994-2003), Management Science (1999-2003), and MIS Quarterly (1997-1999), demonstrating his significant contributions to the field. His consulting work with major organizations including Alcoa, Chrysler, Ford, General Motors, IBM, and governmental agencies like the United States Post Office and Pennsylvania Turnpike has provided practical insights that inform his academic research. He has been actively involved in university governance through committee service including the Business Technology Faculty Search Committee and the CMU Faculty Senate. His research has been supported through various industry partnerships and academic grants, though specific grant details aren't provided in the source material. His teaching focuses on Business Computing and Strategic IT courses, reflecting his expertise in both foundational information systems concepts and strategic applications of technology in business contexts.
Jeremy J. Michalek is a Professor of Mechanical Engineering and Engineering and Public Policy at Carnegie Mellon University. He serves as Director of the Design Decisions Laboratory and co-Director of the Vehicle Electrification Group, with affiliations in multiple sustainability-focused institutes including the Center for Climate and Energy Decision-Making. Education: Ph.D. in Mechanical Engineering (University of Michigan, 2005) Research spans vehicle electrification , life cycle analysis , consumer behavior , and green design . His recent publications focus on battery economics, charging infrastructure impacts, and equity considerations in transportation technologies. Key awards include the NSF CAREER Award , ASME Best Paper Award , and George Tallman Ladd Research Award . Michalek's work has been featured in major media outlets including The New York Times , The Atlantic , and BBC , with policy briefings presented on Capitol Hill. Current research explores EV supply chains, climate resilience, and transportation equity.
Devin G. Pope is the Steven G. Rothmeier Professor of Behavioral Science and Economics at the University of Chicago's Booth School of Business. His research examines psychological biases in economic decision-making using observational data across diverse markets including healthcare, voting, transportation, and consumer behavior. Pope has published extensively in top economics journals (American Economic Review, Quarterly Journal of Economics), general science publications (Science, Nature), and interdisciplinary outlets (Management Science, Psychological Science). His research interests bridge behavioral economics and psychology, focusing on vaccination incentives , racial bias measurement , consumer decision heuristics , and observational data analysis . Recent work leverages smartphone data to study religious attendance patterns, voting wait times, and geographic mobility. Pope's research methodology emphasizes real-world field experiments and large-scale observational datasets to identify psychological biases affecting economic outcomes. Notable scientific contributions include: Co-editing the American Economic Review Amazon Scholar appointment (2019-2021) Robert King Steel Faculty Fellowship Steven G. Rothmeier Professorship Pope advises PhD students and teaches graduate courses including Behavioral Economics and Workshop in Behavioral Science. His research has received significant external funding for pandemic response studies and behavioral interventions. Pope maintains active research collaborations across economics, psychology, and public health disciplines through the Booth School's research centers and workshops.
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.
Yue Zhao is an Associate Professor in the Department of Electrical and Computer Engineering at Stony Brook University, with an affiliated appointment in Applied Mathematics and Statistics. Prior to this, she held postdoctoral positions at Stanford University and Princeton University. She earned her Ph.D. from UCLA in 2011 and B.E. from Tsinghua University in 2006. Her research focuses on smart grid systems, renewable energy integration, machine learning applications in power systems, and game-theoretic approaches to electricity markets. Key areas include transportation electrification, demand response mechanisms, and cyber-physical security of grid infrastructure. She teaches courses on digital signal processing, convex optimization, and communication systems. Her work spans over 50 publications in top journals and conferences like IEEE Transactions on Power Systems and ACM e-Energy. Notable contributions include dynamic state estimation frameworks for inverter-based resources, incentive-compatible market mechanisms for renewable aggregation, and cyber attack detection methodologies. Dr. Zhao advises a research group focused on interdisciplinary challenges in energy systems. Current openings exist for Ph.D. students with strong analytical backgrounds. Sponsors include NSF, DOE, and industry collaborators.
Soraya Fatehi is an Assistant Professor in the Department of Operations Management at the Jindal School of Management (JSOM), University of Texas at Dallas. Her research focuses on operations management challenges in on-demand and crowdsourced systems, retail operations, and the OM-Finance interface. She holds a PhD in Operations Management from the University of Washington, an MS in Systems Engineering from the University of Arizona, and a BS in Industrial Engineering from the University of Tehran. Education: PhD, Operations Management, University of Washington, 2020 MS, Systems Engineering, University of Arizona, 2015 BS, Industrial Engineering, University of Tehran, Iran, 2013 Her research interests span the operational dynamics of on-demand platforms, crowdsourcing in logistics, sustainable transportation solutions, and the intersection of operations management with financial strategies. She has contributed to advancing methodologies for optimizing inspection policies in manufacturing and developing revenue-sharing frameworks in crowdfunding contexts. In her recent publications, Dr. Fatehi explores the integration of autonomous vehicles in food delivery, green initiatives in ride-hailing, and strategies to combat greenwashing in competitive markets. Her work also addresses the optimization of last-mile delivery through crowdsourcing and the operational management of on-demand systems. Earlier contributions include algorithmic approaches for production process inspections and revenue-sharing models in crowdfunding. Scientific Awards: Outstanding Teaching Award, Foster School of Business, University of Washington, 2019 Outstanding Research Award, Foster School of Business, University of Washington, 2018 Advising and Grants: No specific advising or grant information is provided in the text.
Michel Gendreau is a Full Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal . His research focuses on the application of Operations Research to Transportation , Telecommunications , and Energy Systems , with an emphasis on Stochastic Optimization and Real-time Planning . He co-directs the Intelligent Transportation Systems Laboratory and is affiliated with the CIRRELT , IVADO , and Trottier Energy Institute . Education : Ph.D. in Computer Science (1984), Université de Montréal His work includes developing metaheuristics for complex optimization problems and dynamic transportation systems . Recent projects address smart supply chains and real-time logistics . He has supervised over 40 doctoral and master's students, including notable graduates like Sanchez-Martinez, Guillen Reyes, and Parada Pradenas. Dr. Gendreau has been recognized with prestigious fellowships from IFORS (2022) and INFORMS (2010). His academic contributions span 420 publications, with recent studies appearing in Reliability Engineering and System Safety and Networks , focusing on stochastic programming , multiperiod routing , and UAV network design . He collaborates extensively with industry partners and has secured grants from organizations like FRQNT and CIRRELT . His research integrates machine learning with operations research to solve real-world challenges in transportation , energy , and logistics .
Francisco Benita is an Adjunct Lecturer at the Engineering Systems and Design (ESD) Pillar of Singapore University of Technology and Design (SUTD). He holds a PhD in Engineering Sciences from Monterrey Tech (2016) and an MSc in Industrial Economics from Universidad Autónoma de Nuevo León (2012). Prior to SUTD, he was a postdoctoral fellow at SUTD’s Architecture and Sustainable Design Pillar and a Senior Advisor at the ITESM-BMGI Lean Six Sigma Program. His research focuses on urban systems, optimization, data science, and their intersections with economics and public policy. Key areas include transportation networks, spatial livability indices, and pandemic impacts on urban environments. Benita’s interdisciplinary work spans fields like sustainable urban design, carbon emissions modeling, and global trade dynamics. Recent publications highlight trends in transportation innovation (e.g., ride-sharing impacts, aircraft routing frameworks), climate-resilient urban planning (e.g., walkway thermal comfort), and pandemic analysis. His projects often integrate quantitative methods with real-world data, emphasizing actionable insights for policymakers and urban planners. Though no scientific awards are explicitly mentioned, his extensive international collaborations—including research visits to TU Berlin, Vrije Universiteit Brussel, and Supélec—reflect his global academic engagement. Students and grants are not listed in the provided texts. Benita’s work is anchored in labs/teams within SUTD’s ESD Pillar, though specific lab affiliations are not detailed. His research bridges theoretical optimization with practical urban challenges, contributing to both academic discourse and applied solutions in smart cities.
Prof. Dr. Julia Rieck is a Full Professor of Business Administration at the University of Hildesheim , leading the Department of Business Administration and Operations Research within the Faculty of Mathematics, Natural Sciences, Economics and Computer Science. As Dean of the Faculty , she oversees academic programs, quality management, and research initiatives. Her roles include academic advising for the Business Information Systems (B.Sc./M.Sc.) programs and active participation in examination boards and quality committees. Education: PhD in Political Science (Dr. rer. pol.) with summa cum laude (2008), Habilitation at Clausthal University of Technology (2014), and studies in Business Mathematics (Diploma, University of Hamburg, 2003) and Mathematics (Georg-August-University Göttingen, 2000). Research: Focuses on Operations Research , Supply Chain Management , Project Planning , and Logistics . Her work integrates mathematical modeling , machine learning , and real-world applications , particularly in disaster response , dynamic transportation , and sustainable e-commerce . Projects: Leads third-party funded initiatives like "IT für die sorgende Gesellschaft" (AI in healthcare/social sectors) and contributes to the HULLS real-lab (AI in aging societies). Collaborates with regional companies (e.g., Youco, ADITUS) and institutions (HAWK, University of Hannover). Teaching: Emphasizes practical application through case studies, industry partnerships, and the IT-Speed Dating event for student-company connections. Her courses cover project resource planning , logistics , and digital transformation . Labs & Teams: Active in the Institute of Business Administration & Business Information Systems , contributing to the KET Kompetenzwerkstatt (entrepreneurship support) and interdisciplinary teams in AI and sustainability research.
Zhengtian Xu is an Assistant Professor in the Department of Civil & Environmental Engineering at George Washington University , affiliated with the School of Engineering & Applied Science . His research focuses on optimizing urban transportation systems through mathematical modeling and data-driven analysis, emphasizing emerging mobility services and vehicle technologies. Education: B.S., Tsinghua University (2014) M.S., University of Florida (2016) Ph.D., University of Michigan (2020) Research interests include urban transportation systems, mathematical modeling, operations research, and sustainable mobility solutions. His work addresses challenges such as electrification of ride-hailing services, driver labor dynamics, and last-mile delivery optimization. Recent publications explore topics like drone delivery networks and platform competition in autonomous vehicle markets. No academic awards or student advisees are listed. His articles highlight trends in electrification strategies, behavioral driver dynamics, and urban logistics optimization. He has not disclosed grants or lab affiliations in the provided information.
Arash Asadpour Rahimabadi is an Associate Professor at the N. P. Loomba Department of Management within the Zicklin School of Business at Baruch College, CUNY . His research bridges Operations Research and Management Science , focusing on algorithmic design, dynamic pricing, and optimization in gig economy platforms. Education: Ph.D. in Operations Research, Stanford University (2010) BSc in Computer Engineering, Sharif University of Technology (2004) His research interests include stochastic optimization , submodular maximization , marketplace stability , and fair allocation . Recent work explores dynamic pricing in extreme value regimes , shared ride sustainability , and regulation of gig economy platforms . His scientific contributions span algorithmic game theory, combinatorial optimization, and resource allocation, with key publications in Management Science and Operations Research . Current projects analyze escrow payment mechanisms , shared mobility efficiency , and hotel reservation systems . Scientific Awards Best Paper Award, ACM-SIAM Symposium on Discrete Algorithms (SODA), 2010 1st Rank in Iran’s National Graduate Entrance Exam in Computer Engineering, 2004 Silver Medals in Iranian National Olympiads in Informatics, 1999–2000 He serves on graduate and PhD committees at CUNY and has reviewed for journals including Management Science and Operations Research . His teaching includes courses like Decision Models and Analytics and Advanced Discrete Optimization .
Yu Nie is a Professor in the Department of Civil and Environmental Engineering at Northwestern University, affiliated with the NU-TREND research group within the McCormick School of Engineering. His work focuses on optimizing transportation networks, integrating human behavior, infrastructure design, and network topology to enhance mobility, reliability, and sustainability. He holds a Ph.D. from the University of California, Davis, an M.S. from the National University of Singapore, and a B.S. (cum laude) from Tsinghua University. His research interests span interdisciplinary approaches combining optimization, network science, traffic flow theory, economics, and statistics. Key areas include congestion pricing strategies, ride-hailing market dynamics, autonomous vehicle integration, and transit system design. He has contributed to studies on dockless bike-sharing systems, ethics-aware transit design, and traffic management in autonomous vehicle zones. Nie’s recent publications (2024–2025) highlight advancements in modular autonomous vehicle systems, co-modal freight solutions, and policy frameworks for sustainable urban mobility. His work often bridges theoretical insights with practical applications, addressing challenges like EV charging chaos and ride-pooling impacts. He received the 2021 Transportation Science Meritorious Service Award for his editorial contributions. His research also explores freight exchange platforms, taxi market resilience during pandemics, and the role of route choice models in transit design. Labs/Teams: Yu Nie is associated with the NU-TREND research group, specializing in innovative transportation solutions through interdisciplinary collaboration.
