Stanford University
Showing 401-450 of 494 Results
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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. -
King (Vivek) Vanga
Masters Student in Management Science and Engineering, admitted Autumn 2020
BioKing Vanga is a Stanford-trained AI researcher and the founder of CivicSentinel AI, a public-interest initiative focused on developing ethical tools to detect and neutralize harmful uses of artificial intelligence.
His work spans adversarial AI, misinformation detection, and algorithmic accountability. King previously founded AEGIS (Applied Ethics, Governance, and Institutional Systems) and has worked at the intersection of civic institutions and machine learning.
His research is rooted in Stanford’s interdisciplinary approach to ethical technology and has informed open-source frameworks and public-interest platforms.
King’s academic background includes computer science (AI Track) and Management Science & Engineering, with published research in both graph theory and social systems.
Education & Affiliation
King holds a B.S. in Computer Science (Artificial Intelligence track) from Stanford University and is currently pursuing an M.S. in Management Science & Engineering (Technology and Engineering Management) at Stanford. His training in computer science offers foundational technical fluency, while his advanced work in MS&E underscores his commitment to leadership and the managerial side of technology.
Professional & Research Focus
As Founder and Chief Executive Officer of CivicSentinel AI, King leads the development of transparent, ethical platforms for early threat detection, misinformation triage, and algorithmic accountability—tools designed to empower civic institutions, journalists, and technologists before AI-driven risks escalate.
His research contributions include peer-reviewed studies on AI safety, alignment, adversarial risk modelling, computational approaches to misinformation mitigation, and decision-making under uncertainty. In particular, he has produced quantitative models of AI existential risk and frameworks for algorithmic governance.
King’s career blends deep technical expertise with leadership in technology management, positioning him to bridge innovation and responsible deployment.
Community Service & Civic Engagement
Beyond his academic and professional work, King has a sustained record of community-oriented efforts. He co-founded the nonprofit Kare Packages, which distributed over 1,000 COVID-19 protection kits and 1,500 face masks to unhoused populations across California during the pandemic.
He also co-founded the student-led initiative AEGIS at Stanford, which advanced algorithmic ethics, civic tech oversight, and institutional resilience. His public-facing mission emphasizes that smarter AI must be paired with accountability—and that technology should defend, rather than undermine, public trust.
Key Projects & Impact
• CivicSentinel AI: Founder & CEO, leading a platform for AI-based misinformation detection and threat analysis with transparency and civic purpose.
• Engineering risk analysis of AI existential risk: Peer-reviewed study at Stanford MS&E connecting decision-making under uncertainty to AI governance models.
• Kare Packages: Co-founder of a nonprofit delivering COVID-19 protection kits and masks to unhoused communities across California.
• AEGIS (Applied Ethics, Governance, and Institutional Systems): Co-founded while at Stanford; a student initiative advancing ethics in civic technology and institutional oversight.
Awards & Recognition
• Commended for community service during COVID-19 relief efforts.
• Selected for the Stanford MS&E Leadership Fellowship, recognizing leadership and technical-managerial excellence.
• Published peer-reviewed research cited in academic and policy discussions on AI risk, governance and misinformation. -
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.
