Management Science and Engineering
Showing 401-500 of 523 Results
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Alicia Myles Sheares
Assistant Professor of Management Science and Engineering and, by courtesy, of Sociology
BioProfessor Alicia Myles Sheares is an Assistant Professor in the Management Science and Engineering department at Stanford University. Her research sits at the intersection of race and organizations with a specific focus on how underrepresented professionals of color fare in the United States. Currently, she’s working on two major projects. The first explores the experiences of Black tech entrepreneurs in Silicon Valley and Atlanta, while the second explores individual and company-level factors that are associated with success among Black and Latine startups in the U.S. Her research has been published in Social Forces, the Sociology of Race and Ethnicity, Big Data and Society, and the International Migration Review. Professor Sheares was a University of California President’s Postdoctoral Fellow at UCLA. She received her Ph.D. in sociology from UC Berkeley, her M.Sc. in Migration Studies from the University of Oxford, and her B.A. from Spelman College.
Email: asheares@stanford.edu -
Aaron Sidford
Associate Professor of Management Science and Engineering and of Computer Science
Current Research and Scholarly InterestsMy research interests lie broadly in the optimization, the theory of computation, and the design and analysis of algorithms. I am particularly interested in work at the intersection of continuous optimization, graph theory, numerical linear algebra, and data structures.
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Leeth Singhage
Ida Fellow, Institute for Diversity in the Arts
Undergraduate, Management Science and Engineering
Student Wardrobe Supervisor, Theater and Performance Studies
Undergraduate, Theater and Performance StudiesBioLeeth Singhage is an actor, writer, and producer from Sri Lanka, pursuing dual degrees in Management Science & Engineering (B.S.) and Theater & Performance Studies (B.A.) at Stanford. His creative work often investigates pressing current events and explores themes of identity, resilience, and cross-cultural storytelling. His writing credits include QUARANteen (2021), a verbatim-theater production on the teen experience of the COVID19 lockdowns, GROWTHesque (2022-23), a meta exploration of Sri Lanka's political and economic crisis hosted at the Edinburgh Fringe and NYC's United Solo festivals and filmed by Kehelmala Studios, Lab-Grown Meat (2023) a solo play on the incipient alt-meat industry produced at Stanford, and Yakada Yaka (2026), a full-length play on suicide currently in development in Sri Lanka and in the U.S.
Beyond appearances in his original work produced under SarongHoodie, Leeth has played lead roles across theater and screen internationally for over 10-years. Select acting credits include: "Shaan Murthy" in British TV series The Good Karma Hospital - Season 4 (2022) by Tiger Aspects Productions, "Friedrich" in the Broadway touring production of The Sound of Music (2018) by Andrew Lloyd Webber's The Really Useful Group, "Kalana" in multiple award-winning Grease Yaka Returns (2019-20) by AnandaDrama, "Ariel" in The Workshop Players' Shakespeare in the Park production of The Tempest (2017) by AnandaDrama, and "Peter Pan" in Peter Pan the Musical (2016) by COLD Theatre 7.
Leeth has worked in development for Academy® Award-winning filmmakers Jimmy Chin and Chai Vasarhelyi at Little Monster Films, for the multiple Emmy® Award-winning team at Baboon Animation, and for Sri Lankan production company, Kehelmala. Through his cross-cultural storytelling company, SarongHoodie, he aims to increase international representation of underprivileged communities in film and television. -
Robert Sutton
Professor of Management Science & Engineering, Emeritus
BioRobert I. Sutton is an organizational psychologist and best-selling author. He studies leadership, innovation, organizational change, and workplace dynamics. Sutton has published over 200 articles, chapters, and case studies. His focus recently is scaling and leading at scale—how to grow organizations, spread good things (and remove bad things) in teams and organizations, and enhance performance, innovation, and well-being in big organizations.
Sutton received his PhD in Organizational Psychology from The University of Michigan and has served on the Stanford faculty since 1983. He served as Professor of Management Science & Engineering until 2023 and is now Professor Emeritus at Stanford. Sutton is co-founder and former co-director of the Center for Work, Technology and Organization, co-founder of the Stanford Technology Ventures Program, and co-founder of the “Stanford d.school.” Sutton was a resident Fellow at the Center for Advanced Study in the Behavioral Sciences during multiple years. He has served on the editorial boards of numerous scholarly publications and as an editor for Administrative Science Quarterly and Research in Organizational Behavior.
Sutton has served as an advisor to McKinsey & Company, Bain & Company, and Microsoft, a Fellow at IDEO, a board member of the Institute for the Future, a Senior Scientist at Gallup, and on faculty at the World Economic Forum in Davos. He is currently an advisor to Teamraderie and Asana’s Work Innovation Lab. Sutton is the academic co-director of Stanford executive education programs including Customer Focused Innovation and Innovation and Entrepreneurship. He has given more than 200 keynote speeches in more than 20 countries.
Sutton’s academic honors include the award for the best paper published in the Academy of Management Journal, induction into the Academy of Management Journals Hall of Fame, the Eugene L. Grant Award for Excellence in Teaching, the McGraw-Hill Innovation in Entrepreneurship Pedagogy Award, and the award for the best article published in the Academy of Management Review. The London Business School selected Sutton for the 2014 Sumantra Ghoshal Award “for rigour and relevance in the study of management.” The American Management Association selected Sutton as one of the top 30 leaders who most influenced business in 2014 (ranking him 10th).
Sutton’s eight books and two edited volumes include (with Jeffrey Pfeffer) The Knowing-Doing Gap, selected by Jack Covert and Todd Sattersten as one of the best 100 business books of all time, and Weird Ideas That Work, selected by the Harvard Business Review as one of the best ten business books of the year. Hard Facts, Dangerous Half-Truths, and Total Nonsense was selected by Toronto’s Globe and Mail as the top management book of 2006 and by Strategy+Business as one of the best 10 books in the last decade.
The No Asshole Rule—a New York Times (NYT), Wall Street Journal (WSJ), and Businessweek bestseller—was translated into over 20 languages and sold over 900,000 copies. Good Boss, Bad Boss is a NYT and WSJ bestseller. Scaling-Up Excellence (with Huggy Rao) is a WSJ bestseller that was selected as one of the best business books of the year by Amazon, Financial Times, Inc., and others. The Asshole Survival Guide was selected as book of the month by the Financial Times.
Sutton’s latest book (with Rao), The Friction Project, unpacks insights from their seven-year learning adventure using academic research, case studies, classes and workshops, and ongoing dialog with scholars, executives, and innovators to learn how smart organizations make the right things easier and the wrong things harder.
Sutton’s research and opinions have appeared in the press, including NYT, The Times (of London), Financial Times, Fortune, WSJ, Wired, Vanity Fair, Washington Post, and more. Sutton has been a guest on numerous radio and television shows and podcasts. Learn more at bobsutton.net -
James Sweeney
Professor of Management Science & Engineering, Emeritus
Current Research and Scholarly InterestsDeterminants of energy efficiency opportunities, barriers, and policy options. Emphasis on behavioral issues, including personal, corporate, or organizational. Behavior may be motivated by economic incentives, social, or cultural factors, or more generally, by a combination of these factors. Systems analysis questions of energy use.
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Edison Tse
Associate Professor of Management Science and Engineering, Emeritus
BioProfessor Edison Tse received his BS, MS, and Ph.D. in Electrical Engineering from Massachusetts Institute of Technology. He is the Director of Asia Center of Management Science and Engineering, which has the charter of developing executive training programs for executives in Asian enterprises, conducting research on development of the emerging economy in Asia and establishing research affiliations with Asian enterprises, with a special focus in Greater China: China, Hong Kong, and Taiwan.
In 1973, he received the prestigious Donald Eckman Award from the American Automatic Control Council in recognition of his outstanding contribution in the field of Automatic Control. He had served as an Associate Editor of the IEEE Transactions of Automatic Control, and a co-editor of the Journal of Economic Dynamics and Control, which he co-founded.
Professor Tse has done research in system and control engineering, economic dynamics and control, computer integrated systems to support fishery management policy decisions, management and control of manufacturing enterprise, and industrial competitive analysis and product development. Tse developed a framework for analyzing dynamic competitive strategy that would shape the formation of an ecosystem supporting a value proposition. Within such a framework, he developed dynamic strategies for firms entering an emerging market, latecomers entering a matured market, and firms managing transformation. Using this framework, he developed a new theory on the business transformation of a company and the economic transformation of a developing economy. He applied his theory to explain China’s rapid growth since 1978, changing from a production economy to an innovation economy. His current research is extending the theory to managing product success, managing inflection point disruptions, sustainable growth strategy in a dynamic changing environment, and industries’ strategy responding to geopolitics disruption. Over the years he has made valuable contributions in the field of engineering, economics, and business creation and expansion. He has published over 180 papers on his research activities.
From 2004- 2015, he co-directed various Stanford-China programs on regional industry and enterprise transformation that were attended by high level city officials from various cities in China and high level executives from Chinese enterprises. From 2007-2013, he co-directed a Stanford Financial Engineering Certificate Program in Hong Kong that upgrades the quality of managers and traders in the financial institutions in Hong Kong
He was a co-founder and a Board member of Advanced Decision System (ADS), a technology company with emphasis on AI and advanced decision tools. The company was found in 1979 and later acquired by Booz Allen and Hamilton in 1991. In 1988, Verity was spun off from ADS with AI search engine technology developed in ADS to provide enterprise search software. He was a Board member of Verity representing ADS before Verity went IPO in 1995. From 2007-2010, he was a Board member of KBC Fund Management Co., Ltd. -
Madeleine Udell
Assistant Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsProfessor Udell builds the mathematical and computational foundations needed for
scalable, accessible, and responsible data-driven decisionmaking in high-stakes domains, with impact on challenges in healthcare, finance, marketing, operations, and engineering.
She develops new efficient algorithms to accelerate and automate optimization and data science, and new frameworks that empower users to invoke these algorithms and interpret the resulting decisions. -
Melissa Valentine
Associate Professor of Management Science and Engineering and Senior Fellow at the Stanford Institute for Human-Centered AI
Current Research and Scholarly InterestsAs societies develop and adopt new technologies, they fundamentally change how work is organized. The intertwined relationship between technology and organizing has played out time and again, and scholars predict that new internet and data analytic technologies will spur disruptive transformations to work and organizing.
These changes are already well-documented in the construction of new market arrangements by companies such as Upwork and TaskRabbit, which defined new categories of “gig workers.” Yet less is known about how internet and data analytic technologies are transforming the design of large, complex organizations, which confront and solve much different coordination problems than gig platform companies.
Questions related to the structuring of work in bureaucratic organizations have been explored for over a century in the industrial engineering and organizational design fields. Some of these concepts are now so commonplace as to be taken for granted. Yet there was a time when researchers, workers, managers, and policymakers defined and constructed concepts including jobs, careers, teams, managers, or functions.
My research program argues that some of these fundamental concepts need to be revisited in light of advances in internet and data analytic technologies, which are changing how work is divided and integrated in organizations and broader societies. I study how our prior notions of jobs, teams, departments, and bureaucracy itself are evolving in the age of crowdsourcing, algorithms, and increasing technical specialization. In particular, my research is untangling how data analytic technologies and hyper-specialization shape the division and integration of labor in complex, collaborative production efforts characteristic of organizations. -
Benjamin Van Roy
Professor of Electrical Engineering, of Management Science and Engineering and, by courtesy, of Computer Science
BioBenjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His current research focuses on reinforcement learning. Beyond academia, he leads a DeepMind Research team in Mountain View, and has also led research programs at Unica (acquired by IBM), Enuvis (acquired by SiRF), and Morgan Stanley.
He is a Fellow of INFORMS and IEEE and has served on the editorial boards of Machine Learning, Mathematics of Operations Research, for which he co-edited the Learning Theory Area, Operations Research, for which he edited the Financial Engineering Area, and the INFORMS Journal on Optimization. He received the SB in Computer Science and Engineering and the SM and PhD in Electrical Engineering and Computer Science, all from MIT, where his doctoral research was advised by John N. Tstitsiklis. He has been a recipient of the MIT George C. Newton Undergraduate Laboratory Project Award, the MIT Morris J. Levin Memorial Master's Thesis Award, the MIT George M. Sprowls Doctoral Dissertation Award, the National Science Foundation CAREER Award, the Stanford Tau Beta Pi Award for Excellence in Undergraduate Teaching, the Management Science and Engineering Department's Graduate Teaching Award, and the Lanchester Prize. He was the plenary speaker at the 2019 Allerton Conference on Communications, Control, and Computing. He has held visiting positions as the Wolfgang and Helga Gaul Visiting Professor at the University of Karlsruhe, the Chin Sophonpanich Foundation Professor and the InTouch Professor at Chulalongkorn University, a Visiting Professor at the National University of Singapore, and a Visiting Professor at the Chinese University of Hong Kong, Shenzhen. -
Luca Vendraminelli
Postdoctoral Scholar, Management Science and Engineering
BioLuca Vendraminelli is a Postdoctoral Researcher at the Digital Economy Lab and the Stanford Institute for Human-Centered AI (HAI) at Stanford University. He is also a research affiliate at the Center for Work, Technology & Organization (WTO) in the Department of Management Science and Engineering at Stanford University, and at the Data Science and AI Operations Lab in the Digital Data Design Institute at Harvard.
Within the context of large organizations, his research examines how AI transforms job tasks, expertise, and, more broadly, organizational design and the division of labor. He also investigates investments into AI and why AI projects fail, focusing on how the interplay between internal organizational factors and vendor strategies may be roadblocks at various stages of the technology innovation lifecycle.
His work has appeared in scientific journals such as the Journal of Product Innovation Management. He was awarded the 2020 Albert Page Award for Outstanding Professional Contribution. -
John Weyant
Professor (Research) of Management Science and Engineering, of Energy Science Engineering and Senior Fellow at the Precourt Institute for Energy
BioJohn P. Weyant is Professor of Management Science and Engineering and Director of the Energy Modeling Forum (EMF) at Stanford University. He is also a Senior Fellow of the Precourt Institute for Energy and an an affiliated faculty member of the Stanford School of Earth, Environment and Energy Sciences, the Woods Institute for the Environment, and the Freeman-Spogli Institute for International Studies at Stanford. His current research focuses on analysis of multi-sector, multi-region coupled human and earth systems dynamics, global change systems analysis, energy technology assessment, and models for strategic planning.
Weyant was a founder and serves as chairman of the Integrated Assessment Modeling Consortium (IAMC), a seventeen-year old collaboration among over 60 member institutions from around the world. He has been an active adviser to the United Nations, the European Commission, U.S.Department of Energy, the U.S. Department of State, and the Environmental Protection Agency. In California, he has been and adviser to the California Air Resources, the California Energy Commission and the California Public Utilities Commission..
Weyant was awarded the US Association for Energy Economics’ 2008 Adelmann-Frankel award for unique and innovative contributions to the field of energy economics and the award for outstanding lifetime contributions to the Profession for 2017 from the International Association for Energy Economics, and a Life Time Achievement award from the Integrated Assessment Modeling Consortium in 2018. Weyant was honored in 2007 as a major contributor to the Nobel Peace prize awarded to the Intergovernmental Panel on Climate Change and in 2008 by Chairman Mary Nichols for contributions to the to the California Air Resources Board's Economic and Technology Advancement Advisory Committee on AB 32.
Fields of Specialization:
Energy/Environmental Policy Analysis, Strategic Planning
Interests:
Overall goal is to accelerate the use of systems models at state, country, and global scales, aiming to provide the best available information and insights to government and private-sector decision makers. Specific areas include energy, climate change, and sustainable development policy, including emerging technologies and market design alternatives. Draws on concepts and techniques from science and engineering fundamentals (e.g., thermodynamics, fluid mechanics, materials science, and electrical power systems), operations research, economics, finance, and decision theory. -
Chenghan Xie
Ph.D. Student in Management Science and Engineering, admitted Autumn 2024
Current Research and Scholarly InterestsOptimization, theory & practice. Energy-aware AI, nerual-network structure & data center management.
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Renyuan Xu
Assistant Professor of Management Science and Engineering
BioRenyuan Xu is an assistant professor of Management Science and Engineering (MS&E) at Stanford University. Prior to joining Stanford, she held positions at New York University (2024-2025) and the University of Southern California (2021–2024), and was a Hooke Research Fellow at the Mathematical Institute, University of Oxford (2019–2021). She received her Ph.D. in Operations Research from the University of California, Berkeley in 2019. Renyuan's current research interests include mathematical finance, stochastic analysis, stochastic controls and games, and machine learning theory. She received an NSF CAREER Award in 2024, the SIAM Activity Group on Financial Mathematics and Engineering Early Career Prize in 2023, and two JP Morgan AI Faculty Research Awards in 2022 and 2025.
