Stanford University
Showing 151-200 of 458 Results
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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. -
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.
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Hillard Huntington
Researcher, Contingent
Executive Director, 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.
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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. -
Ramesh Johari
Professor of Management Science and Engineering, Senior Fellow at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and, by courtesy, of Electrical Engineering
BioJohari is broadly interested in the design, economic analysis, and operation of online platforms, as well as statistical and machine learning techniques used by these platforms (such as search, recommendation, matching, and pricing algorithms).
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Prof Theresa Johnson
Affiliate, Management Science and Engineering
BioDr. Johnson is a seasoned product leader with deep technical roots and a rare track record of impact across startups, academia, and top-tier tech companies. She currently serves as Head of Product for the Roblox Operating System, where she shapes the product vision for the employee lifecycle for employees at one of the world’s most immersive virtual platforms.
Before that, she led Payments Data Products at Airbnb, tackling complex infrastructure challenges at scale with a focus on user trust, access, and seamless global transactions.
Her career is built on a strong technical foundation—she earned a PhD in Aeronautics and Astronautics from Stanford, becoming the second Black woman in history to do so. That mix of deep systems thinking, experimentation, and executional rigor shows up in everything from launching infrastructure and AI-enabled products, to leading cross-functional teams, to mentoring students and early-career PMs. As Lecturing Professor at Stanford for Introduction to Product Management in the School of Engineering, she's passionate about building inclusive, high-performing teams and designing products that don’t just hit metrics, but matter.
Prof. Theresa Johnson has a BS in Science, Technology and Society and an MS and PhD in Aeronautics and Astronautics from Stanford University. She’s been published in the fields of robotics, machine learning and plasma physics. Theresa lives in Bernal Heights, San Francisco with her husband, two daughters and her rescued catahoula hound, Amelie. -
Amin Karbasi
Adjunct Professor, Management Science and Engineering
BioAn academic entrepreneur, Amin Karbasi is a Senior Director at Cisco Foundation AI, an adjunct professor at Stanford, and serves on the scientific board of the Simons Institute for the Theory of Computing. Previously, he served as Chief Scientist at Robust Intelligence (acquired by Cisco in 2024). Before that, he was a professor at Yale University and a research staff scientist at Google. He has received the National Science Foundation (NSF) CAREER Award, Office of Naval Research (ONR) Young Investigator Award, Air Force Office of Scientific Research (AFOSR) Young Investigator Award, DARPA Young Faculty Award, National Academy of Engineering Grainger Award, Amazon Research Award, Nokia Bell-Labs Award, Google Faculty Research Award, Microsoft Azure Research Award, Yale innovation award, Simons Research Fellowship, and ETH Research Fellowship. His work has also been recognized with paper awards from Graphs in Biomedical Image Analysis (GRAIL), Medical Image Computing and Computer Assisted Interventions Conference (MICCAI), International Conference on Artificial Intelligence and Statistics (AISTATS), IEEE ComSoc Data Storage, International Conference on Acoustics, Speech, and Signal Processing (ICASSP), ACM SIGMETRICS, and IEEE International Symposium on Information Theory (ISIT). His Ph.D. thesis received the Patrick Denantes Memorial Prize from the School of Computer and Communication Sciences at EPFL, Switzerland.
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Arvind Karunakaran
Assistant Professor of Management Science & Engineering and, by courtesy, of Sociology
Current Research and Scholarly InterestsAreas of Research:
Sociology of Work and Occupations/Professions
Organization Theory
Technological/Organizational change
Topics:
Authority in the Workplace
Accountability (Professional, Organizational, Algorithmic)
Phenomena:
Social/Algorithmic Evaluation (of Job applicants, Employees, Startups)
Human-AI augmentation and Reskilling
Social Media Scrutiny
Conflicts in Symmetrical vs. Asymmetrical Relations -
Riitta Katila
W.M. Keck Professor and Professor of Management Science and Engineering
Current Research and Scholarly InterestsThe question that drives Prof. Katila's research is how technology-based firms with significant resources can stay innovative. Her work lies at the intersection of the fields of technology, innovation, and strategy and focuses on strategies that enable organizations to discover, develop and commercialize technologies. She combines theory with longitudinal large-sample data (e.g., robotics, biomedical, platform and multi-industry datasets), background fieldwork, and state-of-the-art quantitative methods. The ultimate objective is to understand what makes technology-based firms successful.
To answer this question, Prof. Katila conducts two interrelated streams of research. She studies (1) strategies that help firms leverage their existing resources (leverage stream), and (2) strategies through which firms can acquire new resources (acquisition stream) to create innovation. Her early contributions were firm centric while recent contributions focus on innovation in the context of competitive interaction and ecosystems.
Professor Katila's work has appeared in the Academy of Management Journal, Administrative Science Quarterly, Organization Science, Strategic Entrepreneurship Journal, Strategy Science, Strategic Management Journal, Research Policy and other outlets. In her work, supported by the National Science Foundation, Katila examines how firms create new products successfully. Focusing on the robotics and medical device industries, she investigates how different search approaches, such as the exploitation of existing knowledge and the exploration for new knowledge, influence the kinds of new products that technology-intensive firms introduce.
