Stanford University
Showing 101-200 of 537 Results
-
Junting Duan
Ph.D. Student in Management Science and Engineering, admitted Autumn 2020
BioJunting Duan is a PhD candidate in the Department of Management Science and Engineering (MS&E) at Stanford University. Prior to joining Stanford, she received her B.S. in Mathematics and Applied Mathematics from Peking University in 2020.
Junting's research interests lie broadly in data-driven decision-making, focusing on statistical inference and machine learning, with applications to causal inference and finance. Her research develops new methodologies with rigorous statistical foundations that enable reliable decision-making with complex and imperfect data, and lies at the intersection of (1) statistical learning for high-dimensional data; (2) causal inference; and (3) machine learning for finance and risk management. Her work has been recognized through publications and revisions at top journals including Management Science and the Journal of Econometrics, as well as invitations to present at major conferences such as the American Economic Association Annual Meeting, the NBER-NSF Time-Series Conference, the NBER Forecasting & Empirical Methods Conference, and the INFORMS Annual Meeting.
Visit her personal website for more details: https://juntingduan.com. -
Charles (Chuck) Eesley
Professor of Management Science and Engineering
Current Research and Scholarly InterestsI study how institutions shape technology-based entrepreneurship. My research identifies the institutional environments that encourage the founding of high-growth, engineering-driven firms, and shows that effective institutional change influences who starts firms and whether they succeed — not just how many firms are started. My recent work extends this agenda to AI: how AI systems function as new institutional actors shaping entrepreneurial opportunity, and how AI can be used as a research tool
-
Kathleen Eisenhardt
Stanford W. Ascherman, M.D. Professor in the School of Engineering, Emerita
Current Research and Scholarly InterestsTheoretical approaches: Cognition, complexity, learning, and organizational theories
Methods: Multi-case Theory Building as well as machine learning, simulation, and econometrics
Recent research: Business model design, strategy as "simple rules" heuristics, strategic interaction in novel markets and ecosystems, strategy in marketplaces, communities v. firm organizational forms -
Kay Giesecke
Professor of Management Science and Engineering
Current Research and Scholarly InterestsKay is a financial technologist whose research agenda is driven by significant applied problems in areas such as investment management, risk analytics, lending, and regulation, where data streams are increasingly large-scale and dynamical, and where computational demands are critical. He develops and analyzes statistical machine learning methods to make explainable data-driven decisions in these and other areas and efficient numerical algorithms to address the associated computational issues.
-
Peter Glynn
Thomas W. Ford Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsStochastic modeling; statistics; simulation; finance
-
Ashish Goel
Stanford W. Ascherman, MD Professor in the School of Engineering and Professor, by courtesy, of Computer Science
BioAshish Goel is a Professor of Management Science and Engineering, the Fortinet Founders Chair of Management Science and Engineering, and Professor (by courtesy) of Computer Science at Stanford University. He received his PhD in Computer Science from Stanford in 1999, and was an Assistant Professor of Computer Science at the University of Southern California from 1999 to 2002. His research interests lie in the design, analysis, and applications of algorithms.
-
Martin Jose Gonzalez
Ph.D. Student in Management Science and Engineering, admitted Autumn 2025
BioA PhD student in Management Science & Engineering, Martin researches the impact of AI on organizations through the Center for Work, Technology and Organization.
With master's degrees from Columbia and the London School of Economics, Martin frequently lectures at top-tier institutions including Stanford, Wharton, and INSEAD. His professional background includes roles at BCG and Google, where he focused on organizational design, cultural transformation, and leadership development. -
Angel Gunaman
Office Aide, GSE Dean's Office
Undergraduate, Management Science and Engineering
Undergraduate, Mechanical EngineeringBioI'm a Mechanical Engineering major at Stanford, concentrating in Product Realization and minoring in Management Science & Engineering. I'm passionate about building meaningful technology and have experience in engineering research, product development, and public sector infrastructure.
-
Yinbin Han
Ph.D. Student in Management Science and Engineering, admitted Autumn 2025
BioYinbin Han is a Ph.D. student in the Department of Management Science and Engineering at the Stanford University. Before joining Stanford, Yinbin was a Ph.D. student in the Department of Finance and Risk Engineering at the New York University from 2024 - 2025 and in the Epstein Department of Industrial and Systems Engineering at the University of Southern California from 2021 - 2024. Yinbin is fortunate to be co-advised by Prof. Renyuan Xu (Stanford) and Prof. Meisam Razaviyayn (USC). Yinbin obtained his B.S. in Mathematics from the Chinese University of Hong Kong, Shenzhen, where he was advised by Prof. Zizhuo Wang. Yinbin's research interests include diffusion models, reinforcement learning, stochastic control and nonconvex optimization.
-
Warren Hausman
Professor of Management Science and Engineering, Emeritus
BioProfessor Hausman performs research in operations planning and control, with specific interests in supply chain management. Most of his contributions are based upon quantitative modeling techniques and emphasize relevance and real world applicability.
He has recently studied how RFID technology can revolutionize the management of supply chains. He has investigated the value of RFID applications in retail environments, in logistics, and in manufacturing and assembly operations. He has also studied how Supply Flexibility in retail supply chains affects a company's financial performance and market capitalization.
He is an active consultant to industry and is involved in numerous executive education programs both at Stanford and around the world. He was the founding director of a two-day executive program on Integrated Supply Chain Management held semi-annually in Palo Alto, California from 1994 to 2003. His consulting clients represent the following industries: general manufacturing, electronics, computers, consumer products, food & beverage, transportation, healthcare, and high technology. He is also a co-founder of Supply Chain Online, which provides web-based corporate supply chain management training. He serves on the technical advisory boards of several Silicon Valley startups. He has also served as an Expert Witness for litigation involving operations management
In 1994 he was elected President of the Operations Research Society of America (ORSA). He has also served on the Board of the Institute for Operations Research and the Management Sciences (INFORMS) and on several National Science Foundation Advisory Panels and Committees. He is a Fellow of INFORMS, a Distinguished Fellow of the Manufacturing and Service Operations Management Society, and a Fellow of the Production & Operations Management Society. He has also won several teaching awards, including the Eugene Grant Teaching Award in Stanford's School of Engineering in 1998.
He earned a BA in Economics from Yale and a PhD from MIT's Sloan School of Management. -
Siegfried Hecker
Professor (Research) of Management Science and Engineering and Senior Fellow at the Freeman Spogli Institute for International Studies, Emeritus
Current Research and Scholarly Interestsplutonium science; nuclear weapons stockpile stewardship; cooperative threat reduction
-
Pamela Hinds
Rodney H. Adams Professor in the School of Engineering, Fortinet Founders Chair of the Department of Management Science and Engineering and Professor of Management Science and Engineering
On Leave from 01/01/2026 To 06/30/2026BioPamela J. Hinds is Rodney H. Adams Professor in the School of Engineering, Professor of Management Science & Engineering, Co-Director of the Center on Work, Technology, and Organization, and on the Director's Council for the Hasso Plattner Institute of Design. She studies the effect of technology on teams, collaboration, and innovation. Pamela has conducted extensive research on the dynamics of cross-boundary work teams, particularly those spanning national borders. She explores issues of culture, language, identity, conflict, and the role of site visits in promoting knowledge sharing and collaboration. She has published extensively on the relationship between national culture and work practices, particularly exploring how work practices or technologies created in one location are understood and employed at distant sites. Pamela also has a body of research on human-robot interaction in the work environment and the dynamics of human-robot teams. Most recently, Pamela has been looking at the changing nature of work in the face of emerging technologies, including the nature of coordination in open innovation, changes in work and organizing resulting from 3D-printing, and the work of data analysts. Her research has appeared in journals such as Organization Science, Research in Organizational Behavior, Academy of Management Journal, Academy of Management Annals, Academy of Management Discoveries, Human-Computer Interaction, Journal of Applied Psychology, Journal of Experimental Psychology: Applied, and Organizational Behavior and Human Decision Processes. Pamela is a Senior Editor of Organization Science. She is also co-editor with Sara Kiesler of the book Distributed Work (MIT Press). Pamela holds a Ph.D. in Organizational Science and Management from Carnegie Mellon University.
-
Kent Hippler
Ph.D. Student in Management Science and Engineering, admitted Summer 2025
BioKent Hippler is a PhD student in the Decision and Risk Analysis (DARA) Group in Stanford's Department of Management Science and Engineering, advised by Dr. Elisabeth Paté-Cornell. His current research focuses on risk attitudes in AI Decision Support Systems.
Prior to pursuing his PhD, Kent served as a Nuclear Surface Warfare Officer in the U.S. Navy, supporting three western Pacific deployments aboard the USS Anchorage and USS Theodore Roosevelt. He later worked as a Systems Engineer at Maxar Technologies and a Software Engineer at Amazon. Kent holds a B.S. in Nuclear Engineering, summa cum laude, from the University of Florida (2016) and an M.S. in Management Science and Engineering from Stanford (2025), where he worked with the Language Data and Reasoning Lab under the advisement of Dr. Amin Saberi. -
Andrew Hong
Masters Student in Management Science and Engineering, admitted Autumn 2022
BioI study the intersection of machine learning and social sciences to better align tech with society and use computational methods to understand human behavior. My research focuses on building software and statistical methods to quantify fairness of various electoral voting systems. Now, I'm a Machine Learning Analyst in Google's Trust & Safety Team while finishing my Masters in Management Science & Engineering.
MS: Management Science & Engineering, concentration in computational social sciences
BA: Data Science & Social Systems, concentration in socio-political behavior analysis -
Irene Ai Hsu
Finance and Administrative Manager, Management Science and Engineering - Technology Ventures Program
BioA graduate of Princeton and a former Fulbright scholar to Taiwan, Irene Hsu is passionate about the power of entrepreneurship to bring transformative change, particularly in international settings. Her experience in finance and operations spans a variety of industries including law, nonprofit, and higher education.
-
Hillard Huntington
Executive Director, Energy Modeling Forum
Researcher, Management Science and Engineering - Energy Modeling Forum
Staff, Management Science and Engineering - Energy Modeling ForumBioHuntington is Executive Director of Stanford University's Energy Modeling Forum, where he conducts studies to improve the usefulness of models for understanding energy and environmental problems. In 2005 the Forum received the prestigious Adelman-Frankel Award from the International Association for Energy Economics for its "unique and innovative contribution to the field of energy economics."
His current research interests are modeling energy security, energy price shocks, energy market impacts of environmental policies, and international natural gas and LNG markets. In 2002 he won the Best Paper Award from the Energy Journal for a paper co-authored with Professor Dermot Gately of New York University.
He is a Senior Fellow and a past-President of the United States Association for Energy Economics and a member of the National Petroleum Council. He was also Vice-President for Publications for the International Association for Energy Economics and a member of the American Statistical Association's Committee on Energy Data. Previously, he served on a joint USA-Russian National Academy of Sciences Panel on energy conservation research and development.
Huntington has testified before the U.S. Senate Committee on Foreign Relations and the California Energy Commission.
Prior to coming to Stanford in 1980, he held positions in the corporate and government sectors with Data Resources Inc., the U.S. Federal Energy Administration, and the Public Utilities Authority in Monrovia, Liberia (as a U.S. Peace Corps Volunteer). -
Donald Iglehart
Professor of Engineering-Economic Systems & Operations Research, Emeritus
BioDonald L. Iglehart is a John von Neumann Theory Prize recipient who has made fundamental contributions to performance analysis, optimization, and simulation of stochastic systems. Iglehart received his Bachelor’s degree in Engineering Physics from Cornell in 1956, his Master’s degree in Mathematical Statistics from Stanford University in 1959, and his PhD in the same subject from Stanford in 1961. His dissertation was supervised by Herbert E. Scarf and Samuel Karlin, and the topic was on dynamic programming and stationary analysis of inventory problems. He taught at Cornell University from 1961 to 1967 and came to Stanford in 1967, where he has been emeritus since 1999. In1976, he spent a very productive year as an Overseas Fellow at Churchill College at Cambridge University. In his capacity as a PhD advisor, he has had many notable students, including Peter Glynn, Peter Haas, Phil Heidelberger, Doug Kennedy, and Ward Whitt.
Iglehart was jointly awarded the John von Neumann Theory Prize in 2002 with Cyrus Derman, the same year he was named an inaugural Fellow of the Institute for Operations Research and the Management Sciences. He was recognized for having pioneered and developed diffusion limits and approximations for heavily congested stochastic systems. His ideas provided tractable limiting processes and readily computable approximations for complex queueing and other stochastic systems for which closed-form solutions have proved intractable. Iglehart’s original research and contributions have heavily influenced queueing theory in the years since their publication, and his papers have been cited in hundreds of publications. Some of his other work has focused on inventory and distribution problems.
Iglehart was also honored by the INFORMS Simulation Society in 2012 with its highest honor, the Lifetime Professional Achievement Award (LPAA). His foundational work in that field recognized and exploited the underlying stochastic structure of simulation as a means of producing enhanced simulation methodologies. For example, he introduced and led the development of the regenerative method for stochastic simulation output analysis, inspiring a flood of significant contributions to simulation methodology. In the late 1980s, Iglehart and Glynn incorporated such techniques as importance sampling into stochastic simulations. The LPAA also noted his ability to clearly organize and articulate deep theory in his presentations and writing, and recognized his education of Ph.D. students who have had, individually and cumulatively, a profound impact on simulation education and research. The citation for his award states that "It is no exaggeration to say that Don Iglehart’s contributions made simulation a respectable research discipline in some circles of the operations research community."
In addition to being an INFORMS Fellow, Iglehart was elected in 1999 to the National Academy of Engineering, having been selected for his contributions to queueing theory, simulation methodology, inventory control, and diffusion approximations. He was also honored in 1971 through his induction as a Fellow of the Institute of Mathematical Statistics.
*****
Historical Academic Appointments:
1961-67 School of Operations Research and Industrial Engineering, Cornell University
1967-96 Department of Operations Research, Stanford University
1996-99 Department of Engineering-Economic Systems and Operations Research, Stanford University -
Ruizhe Jia
Assistant Professor of Management Science and Engineering
BioI am an Assistant Professor in the Department of Management Science & Engineering at Stanford University. I earned my Ph.D. in Operations Research at Columbia University, advised by Prof. Agostino Capponi, and completed my B.S. and M.A. in Mathematics at UCLA.
My research sits at the intersection of financial technology, market microstructure, and mechanism design. I study how financial markets function and how they can be redesigned for greater efficiency and fairness, with a particular focus on decentralized finance (DeFi) and blockchain-based trading. My work spans three areas:
Market microstructure — analyzing trading behavior and designing better financial markets.
FinTech and DeFi — examining how cryptographic tools and decentralized protocols reshape financial transactions.
Incentives in financial technology — addressing misalignments that emerge in crypto-finance and proposing mechanisms that improve adoption and efficiency.
I believe finance is a social science that benefits from active engagement with real markets. I work closely with both industry and regulators to ensure my research not only advances theory but also informs practice and policy in digital assets and financial technology.
