جست‌وجوی استاد و پژوهشگر

Melissa Clarkمشاهده پروفایل

استاد

• Business Sustainability
• Marketing
• Hospitality and Tourism Management
• +۴ مورد دیگر

Melissa Clark is a Professor at Coastal Carolina University's E. Craig Wall Sr. College of Business Administration, specializing in the Department of Marketing and Hospitality, Resort and Tourism Management. Her career spans roles as Professor, Associate Professor, and Assistant Professor at Coastal Carolina University and the University of North Alabama, alongside her Graduate Teaching Assistantship at the University of Mississippi. Education: Ph.D. in Business Administration (Marketing) from the University of Mississippi MBA from the University of North Alabama Bachelor of Business Administration in Finance from the University of North Alabama Dr. Clark's research focuses on Business Sustainability, Marketing, and Hospitality/Tourism Management , with a strong emphasis on integrating Environmental Sustainability and Relationship Marketing into sector-specific practices. Her work bridges Consumer Behavior and Social Media Marketing , analyzing trends in sustainable tourism, green energy adoption, and digital engagement. The 15 most recent articles highlight her exploration of topics such as Green Energy Purchase Intentions , Social Media's Role in Tourism Promotion , and Pharmaceutical Market Segmentation , reflecting a multidisciplinary approach to sustainable business practices. Teaching Interests: Business Sustainability, Principles of Marketing, and Sustainability and Social Responsibility.

Lina von Sydowمشاهده پروفایل

استاد

• Computational Science
• Computational Finance
• Ice Sheet Modeling
• +۲ مورد دیگر

Lina von Sydow is a Professor in Computational Science at Uppsala University's Department of Information Technology. She serves as Section Dean for the Mathematical-Computer Science Section since July 2023. Her academic journey includes becoming an Associate Professor in 2000, Senior Lecturer since 1997, and leading the Department of Information Technology from 2018 to 2023. PhD in Domain Decomposition Methods (1995, Uppsala University) Postdoctoral Fellow at Oxford University (1996-1997) Her research spans computational science with dual focuses on Computational Finance and Ice Sheet Modeling . In finance, she develops numerical methods for option pricing using PDEs, radial basis functions, and stochastic volatility models. In climate science, she contributes to ice sheet dynamics through full Stokes models and adaptive time-stepping approaches, particularly in simulating grounding line migration. Recent publications (2025) address gender disparities in IT education, including comparative analysis of admission trends and intervention studies to boost female enrollment. Earlier works (2020-2015) focus on high-order finite difference methods for financial derivatives, BENCHOP benchmarking projects, and preconditioning techniques for PDEs. Scientific awards include Excellent Teacher (2013) She actively collaborates on educational reforms, co-authoring studies like Gender-aware course reform in Scientific Computing (2013). Her leadership roles include Head of Department (2018-2023) and Section Dean (2023-present), influencing academic governance and interdisciplinary research. Labs and teams: Works with Uppsala University's Computational Science group, Elmer/ICE project collaborators (e.g., Per Lötstedt, Gong Cheng), and international partners in numerical finance and climate modeling.

• Discrete Choice Econometrics
• Transportation Economics
• Urban Economics
• +۲ مورد دیگر

Mogens Fosgerau is a Professor at the Department of Economics, University of Copenhagen, with a research focus on discrete choice theory, rational inattention, transportation and urban economics, congestion modeling, and entropy-based frameworks. He has held an ERC Advanced Grant (2017-2023) and completed a Grand Solutions project for the Innovation Fund Denmark (2016-20). Education: Mathematical Economics (Aarhus University, 1990), PhD in Mathematics (University College London, 1992). Current affiliations: Department of Economics (University of Copenhagen), Faculty of Social Sciences. Former roles: Guest Professor at DTU (2022-2023), member of the Commission for Green Transition of Passenger Cars (2019-2021). His research explores the intersection of information theory and discrete choice models, addressing complex substitution patterns and endogeneity issues through generalized entropy frameworks. He applies these models to transportation planning, urban economics, and climate policy analysis. Recent publications focus on perturbed utility models, inverse product differentiation logit, and rational inattention in spatial choice contexts. His work bridges theoretical econometrics with practical transport and environmental policy challenges. Awards: Recipient of the 2021 Transportation Science Meritorious Service Award. Former Editor-in-Chief of Economics of Transportation (2012-2020). Advising and Grants: Leads research projects funded by the European Research Council and Innovation Fund Denmark. Has participated in policy committees including the Danish Environmental Economic Council (2019-2025) and the Committee on Public Transport Mobility (2023-24).

Damian Nale Dailisanمشاهده پروفایل

مدرس

• Computational Social Science
• Machine Learning
• Multi-Agent Systems
• +۳ مورد دیگر

Dr. Damian Nale Dailisan is a Lecturer in the Department of Humanities, Social and Political Sciences at ETH Zürich, affiliated with the Computational Social Science group. He holds a Ph.D. in Physics from the University of the Philippines, specializing in traffic modeling and machine learning applications. His research focuses on multi-agent systems, particularly in transportation and urban systems. He has held postdoctoral roles and contributed to projects like the ACCeSs@AIM lab. His work bridges computational methods with real-world challenges, including traffic control optimization, AI-driven decision-making, and smart city infrastructure. Notable projects include FAIRLANE for priority lane management and studies on democratizing traffic control systems. Dailisan’s publications span journals like Transportation Research Part C and IEEE Access, addressing topics such as reinforcement learning in traffic signals and ethical AI frameworks. He has presented at workshops like 'Back to the Future' at ETH Zurich and collaborates with interdisciplinary teams to enhance urban mobility solutions. His technical expertise includes Python, network analysis, and agent-based modeling, with contributions to open-source tools for earthquake networks and social systems analysis.

• Computer Science
• Machine Learning
• Data Science
• +۴ مورد دیگر

Yong Zhang is affiliated with Tsinghua University's Research Institute of Information Technology in Beijing, China. His research focuses on machine learning, optimization algorithms, edge computing, and their applications in areas like time series analysis, federated learning, and sensor networks. He has collaborated on projects involving neural networks, scheduling problems, and privacy-preserving techniques. Education: Yong Zhang earned a PhD in Computer Science and Engineering from Fudan University in 2007. His academic career includes roles at institutions like the Chinese Academy of Sciences and the University of Hong Kong, reflecting a strong interdisciplinary background. Research Contributions: His work spans theoretical computer science, algorithm design, and applied machine learning. Notable areas include developing efficient scheduling algorithms for energy systems, creating robust federated learning frameworks for industrial demand forecasting, and advancing methods for sentiment analysis using multimodal data. He has also contributed to biomedical engineering through smartphone-based health monitoring systems. Collaborations: He frequently collaborates with researchers at institutions like the University of Electronic Science and Technology of China, Nanyang Technological University, and The Hong Kong Polytechnic University. Key projects involve data caching optimization in edge computing, distributed algorithms for dynamic networks, and combinatorial optimization problems. Labs & Future Work: His team explores cutting-edge topics in AI-driven systems, including trust-aware machine learning, distributed resource allocation, and real-time data processing for IoT applications. Current research emphasizes scalable solutions for complex optimization challenges in both academic and industrial settings.

• Global Health Education
• Clinical Ethics
• Diabetes Management
• +۳ مورد دیگر

Tracy Rabin, MD, MS, is Associate Professor of Medicine (General Medicine) and Clinical Professor of Nursing at Yale School of Medicine. She directs the Office of Global Health and serves as Associate Program Director for Global and Community Health in the Yale Primary Care Internal Medicine Residency Program. She attends on medical wards at Yale-New Haven Hospital's St. Raphael Campus, directs a multidisciplinary diabetes clinic, and co-leads curricula in community engagement and international medical education through the Makerere University-Yale University collaboration in Uganda. Her research focuses on global health education, clinical ethics, diabetes management, and healthcare transitions. She has developed innovative models for teaching politically charged topics and gender-affirming care. Dr. Rabin's publications address global health equity, non-communicable disease management in Uganda, ethical medical education partnerships, and pandemic responses.

Mogens Fosgerauمشاهده پروفایل

استاد

• Transport Economics
• Discrete Choice Modeling
• Travel Behavior
• +۷ مورد دیگر

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

Michael Hylandمشاهده پروفایل

دانشیار

• Transportation Systems
• Autonomous Vehicles
• Operations Research
• +۴ مورد دیگر

Michael Hyland is an Associate Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering, University of California, Irvine. His research focuses on the modeling, analysis, and optimization of smart urban transportation systems, with particular emphasis on shared autonomous vehicles, microtransit integration with fixed-route transit, and sustainable mobility solutions. He employs methodologies from operations research (optimization, Markov decision processes), statistical modeling (discrete choice, regression), and economic analysis to address challenges in urban mobility. Education: Ph.D., Civil and Environmental Engineering (Transportation), Northwestern University, 2018 M.Eng., Civil and Environmental Engineering (Transportation), Cornell University, 2013 B.S. Civil and Environmental Engineering, Cornell University, Magna Cum Laude, 2013 His recent research explores emerging mobility paradigms through topics such as dynamic fleet management, vehicle miles traveled (VMT) impacts, equity in job accessibility, electricity demand implications of e-bikes, and human-machine collaborative planning frameworks. The work often combines large-scale simulation with interpretable modeling techniques. Hyland leads the Hyland Lab , which develops computational tools for evaluating integrated transportation systems. The lab's work spans theoretical modeling (e.g., state-space representations, decomposition heuristics) and applied policy analysis (e.g., assessing Senate Bill 1 infrastructure projects, AV-era parking reforms, and micromobility deployment strategies).

Richard Baileyمشاهده پروفایل

استاد

• Environmental Systems
• Human-Environment Interactions
• Mathematical Modeling
• +۷ مورد دیگر

Professor Richard Bailey is Professor of Environmental Systems at the University of Oxford's School of Geography and the Environment. He serves as a Tutorial Fellow and Dean of St Catherine's College, a Senior Research Fellow at the Institute for New Economic Thinking, and a member of the Oxford Biodiversity Institute. Bailey co-directs the Oxford Luminescence Dating Laboratory and leads the CoHESys-lab research group focused on complex human-environmental systems. Richard's research centers on the dynamics of natural environmental systems and coupled human-environment interactions across various timescales. His work employs mathematical modeling, numerical simulations, and empirical data analysis to understand complex systems, with a strong focus on sustainability applications, particularly in ocean systems. The CoHESys-lab develops models that integrate machine learning methods to explore implementable policies for environmental challenges. His recent publications demonstrate a strong trend toward interdisciplinary research combining environmental science, computational modeling, and sustainability. Bailey's work spans from theoretical explorations of complex systems to applied projects addressing pressing issues like plastic pollution, fisheries management, and climate change impacts on marine ecosystems. His research increasingly incorporates agent-based modeling and machine learning approaches to tackle coupled human-environment challenges. Co-Director of Oxford Martin School Programme on Sustainable Oceans Co-Director of Oxford Luminescence Dating Laboratory Leader of CoHESys-lab research group Professor Bailey currently supervises graduate students Maike Nowatzki (focusing on dunefield morphology using deep learning) and Thomas Youngman (working on macroeconomic modeling for UK climate transition). His recent advisees include Emily Neil (rewilding impacts at Knepp Estate) and Diana Bailey (LM OSL analysis techniques). His research is supported through collaborations with organizations including Ocean Conservancy, Stanford University, George Mason University, and the University of California at Santa Barbara, with computational support from Amazon Web Services. Bailey leads the CoHESys-lab (Complex Human Environmental Systems Simulation Laboratory), which develops sophisticated models for understanding coupled human-environment systems. His OSIRIS framework (Ocean Systems Interactions, Risks, Instabilities and Synergies) represents a significant contribution to analyzing multiple stressors on marine systems. The lab maintains strong collaborations with environmental organizations and academic institutions worldwide to address sustainability challenges through innovative computational approaches.

Sorawoot Srisumaمشاهده پروفایل

دانشیار

• Econometrics
• Empirical Industrial Organizations
• Dynamic Discrete Choice Models
• +۳ مورد دیگر

Sorawoot Srisuma is an Associate Professor in the Department of Economics at the National University of Singapore (NUS). His research focuses on econometrics and empirical industrial organization, with particular emphasis on structural estimation, dynamic discrete choice models, and market structure analysis. He holds a PhD from the London School of Economics. Key research areas include the analysis of subjective well-being data, nonparametric identification in economic models, and the welfare effects of market frictions. His work often combines advanced econometric techniques with applications in industrial organization and development economics. Recent publications explore topics such as search models with heterogeneous agents, spatial autoregressions with varying coefficients, and the impacts of mental health policies. He is affiliated with the Institute of Operations Research and Analytics (IORA), part of NUS’s Smart Nation Research Cluster. His teaching areas include advanced econometrics, and he has contributed to methodological advancements in structural estimation, particularly in dynamic games and Markov decision processes.

• Consumer Behavior
• Pricing Strategy
• Auctions
• +۷ مورد دیگر

Eric A. Greenleaf is a Professor of Marketing at New York University's Leonard N. Stern School of Business, where he has been a faculty member since 1988. He teaches undergraduate and MBA courses in Introduction to Marketing, Market Research, New Product Development, and Pricing Strategies, as well as doctoral seminars on Pricing Theory and Response and Context Effects in Surveys. Education: Ph.D. in Marketing, Columbia University, 1986 M.B.A., Columbia University, 1981 B.S. in Town Planning and Design, University of New Hampshire, 1977 (Summa Cum Laude) Professor Greenleaf's research centers on consumer behavior in pricing, auctions, and marketing research. His work explores how consumers react to prices, the economics of auctions (particularly in art markets), the application of neuroscience in marketing, aesthetic responses to products, and methodological issues in survey research. He has published in leading journals such as Journal of Consumer Research , Marketing Science , Management Science , and Public Opinion Quarterly . The analysis of his recent publications reveals a consistent focus on behavioral aspects of pricing and auctions, with increasing integration of neuroscience and psychological mechanisms. His work spans experimental design, field studies, and theoretical modeling, often bridging marketing with economics and psychology. Key themes include partitioned pricing, bidding behavior, regret and rejoicing in auctions, and context effects in consumer judgment. Scientific Awards and Honors: Winner, Marketing Science Institute Behavioral Pricing Competition Grant (2004) Winner, MSI Pricing Strategy Competition Research Grant (1994) Nominated for Paul E. Green Award, Journal of Marketing Research (1998) Beta Gamma Sigma Honor Society Phi Beta Kappa Honor Society Summa Cum Laude, University of New Hampshire Professor Greenleaf has received significant research funding, including a large NIH grant (2009) with colleagues in Psychology and Marketing to study public service ads using neuroscience methods. He has advised on school enrollment forecasting in Manhattan. He has held visiting positions at Columbia University, Wharton, and the Haas School of Business. He has not advised any named students in the provided texts, but his long tenure suggests mentorship of numerous doctoral candidates. He is actively engaged in research and teaching, with no indication of retirement or part-time status.

Jackson Buntingمشاهده پروفایل

استادیار

• Econometrics
• Applied Microeconomics
• Structural Econometrics
• +۳ مورد دیگر

Jackson Bunting is an Assistant Professor of Economics at the University of Washington. He holds a Ph.D. in Economics from Duke University (2021) and previously served as an Assistant Professor at Texas A&M University. His research focuses on structural econometric approaches to panel data, particularly addressing unobserved heterogeneity and learning models in dynamic settings. Bunting's work emphasizes methodological advancements in dynamic discrete choice models and hypothesis testing for panel data properties like marginal homogeneity. His research interests include applied microeconomics, structural econometrics, and computational methods in economics. Notable contributions involve semiparametric identification frameworks, permutation-based hypothesis testing for dynamic games, and improving computational efficiency in structural estimation. Bunting has collaborated with scholars like Federico Bugni and Takuya Ura on foundational econometric methodologies. Recent publications address topics such as homogeneity testing in dynamic discrete games, estimation techniques for dynamic choice models with unobserved heterogeneity, and algorithmic improvements for econometric analysis. His work bridges theoretical econometrics with applied problems in labor, industrial organization, and policy analysis.

Kota Saitoمشاهده پروفایل

استاد

• Decision Theory
• Behavioral Economics
• Experimental Economics
• +۳ مورد دیگر

Kota Saito is a Professor of Economics at the California Institute of Technology. He holds a Ph.D. from Northwestern University (2011) and previously served as an Assistant Professor at Caltech from 2011–16 before becoming a full professor in 2017. Education: B.A. (Keio University, 2005), M.A. (University of Tokyo, 2007), Ph.D. (Northwestern University, 2011) His research focuses on decision theory , developing mathematical models that explain behavioral regularities in experimental economics and psychology. Key areas include stochastic intertemporal preferences , random utility models , and discrete choice analysis . Recent work explores non-separable time preferences in dynamic discrete choice models and axiomatizations for random utility with incomplete datasets. The 15 most recent publications span decision theory , discrete choice , and behavioral economics , with particular attention to stochastic intertemporal choice , mixed logit models , and risk-time preference interactions . These studies often involve collaborations with Federico Echenique, Jay Lu, and Taisuke Imai. Scientific Awards NSF Grant SES-1919263 (PI) NSF Grant SES-1558757 (Co-PI) Pension Research Council/TIAA Institute Partnership Grant (2017-18) At Caltech, Saito is affiliated with the Ronald and Maxine Linde Institute of Economic and Management Sciences and the Center for Theoretical and Experimental Social Sciences (CTESS). He teaches graduate courses in economic theory, including Behavioral Decision Theory and Theory of Value .

• Health Policy
• Pharmacy Reimbursement
• Healthcare Economics
• +۳ مورد دیگر

Dr. Julie M. Urmie is an Associate Professor in the Department of Pharmacy Practice and Science at the University of Iowa College of Pharmacy. She holds a B.S. in Pharmacy from the University of Wisconsin-Madison, followed by an M.S. in Pharmacy Administration and a Ph.D. in Social and Administrative Sciences in Pharmacy from the same institution. Her research focuses on Medicare Part D, pharmacy reimbursement systems, and the impact of prescription drug benefit designs on patient medication adherence and healthcare utilization. Dr. Urmie’s teaching expertise includes healthcare financing systems, health policy, and prescription drug pricing strategies. Her work explores how insurance policies and reimbursement structures influence patient access to medications, with a particular emphasis on vulnerable populations like Medicare beneficiaries and Medicaid coverage gap patients. Her research publications span topics such as pharmacy-led Medicare Part D consultation services, cost-sharing effects on specialty drug use, and the role of pharmacists in collaborative healthcare models. She has been recognized as a High Performing Peer Reviewer by the Journal of Managed Care Pharmacy . Dr. Urmie’s studies often combine qualitative and quantitative methods, including discrete choice experiments, systematic reviews, and stakeholder interviews. Her work highlights systemic challenges in healthcare access and advocates for policy reforms to improve medication affordability and equitable reimbursement practices. Notably, she has examined the financial sustainability of independent pharmacies under Medicare Part D and Medicaid managed care systems, emphasizing the need for equitable reimbursement policies. Her recent projects include evaluating the impact of Medicare drug price negotiation programs and analyzing patient preferences for community pharmacy services.

Noah Gansمشاهده پروفایل

استاد

• Service Operations
• Stochastic Processes
• Queueing Systems
• +۳ مورد دیگر

Noah Gans is the Anheuser-Busch Professor of Management Science at the Wharton School of the University of Pennsylvania, where he serves as Professor in the Operations, Information and Decisions department. His research focuses on service operations with particular emphasis on call center management, stochastic processes, and queueing system control. Department Editor, Stochastic Models and Simulation at Management Science President of Manufacturing and Service Operations Management Society (MSOM) PhD Program Coordinator for the OID Department His academic work spans diverse domains including healthcare technology pricing, container inspection security, workforce optimization, and revenue management. He has pioneered adaptive clinical trial designs and developed novel models for customer demand sensitivity in overbooking scenarios. Key research areas include: Bayesian sequential learning for multi-arm clinical trials Value-based pricing under uncertainty Stochastic control in service systems Security policy analysis for global supply chains Risk-sharing mechanisms in healthcare Scientific honors include NSF CAREER Award (1998), INFORMS George E. Nicholson Prize (1995), and multiple teaching awards from the Wharton MBA program (2004, 2010-2011, 1997-2001). His publications bridge theoretical operations research with practical implementation across healthcare, transportation, and service industries.