School of Engineering


Showing 41-49 of 49 Results

  • Edison Tse

    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

    Madeleine Udell

    Assistant Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering

    Current Research and Scholarly InterestsProfessor Udell develops new techniques to accelerate and automate data science,
    with a focus on large-scale optimization and on data preprocessing,
    and with applications in medical informatics, engineering system design, and automated machine learning.

  • Johan Ugander

    Johan Ugander

    Associate Professor of Management Science and Engineering

    BioProfessor Ugander's research develops algorithmic and statistical frameworks for analyzing social networks, social systems, and other large-scale data-rich contexts. He is particularly interested in the challenges of causal inference and experimentation in these complex domains. His work commonly falls at the intersections of graph theory, machine learning, statistics, optimization, and algorithm design.

  • Melissa Valentine

    Melissa Valentine

    Associate Professor of Management Science and Engineering

    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

    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.

  • John Weyant

    John Weyant

    Professor (Research) of Management Science and Engineering and of Energy Science Engineering

    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.

  • Yinyu Ye

    Yinyu Ye

    Kwoh-Ting Li Professor in the School of Engineering, Emeritus

    Current Research and Scholarly InterestsMy current research interests include Continuous and Discrete Optimization, Algorithm Development and Analyses, Algorithmic Game/Market Theory and Mechanism-Design, Markov Decision Process and Reinforcement Learning, Dynamic/Online Optimization and Resource Allocation, and Stochastic and Robust Decision Making. These areas have been the unique and core disciplines of MS&E, and extended to new application areas in AI, Machine Learning, Data Science, and Business Analytics.