The application deadline for our doctoral program is 11:59 p.m. PST on December 1, 2015.
You may view your application status and decision on your application activity page. Log back into your online application, and click on "Review Your Activity".
Applicants are notified of decisions in February.
Current Stanford graduate students wishing to apply to the Doctor of Philosophy program in Management Science and Engineering should apply online using the Instructions for New Students, except that it is not necessary for current Stanford graduate students to resend hard copies of transcripts or resend official test scores, as we already have those from the first application. Please do add your current Stanford degree onto your application, and upload your current Stanford transcript (even if there are not yet any grades reported).
Our application requires applicants to list 1-3 research interest areas. Faculty review the applications based on this information. Please see below for information on our research areas to assist you in your selection(s).
Decision and Risk Analysis:
Students who specialize in Decision and Risk Analysis are prepared for careers that include academic and engineering positions, management consulting, policy and strategic analysis, and risk management. They apply engineering systems analysis and probability to tackle complex economic and technical design or management problems, both in the private and public sectors. In the Decision Analysis group, recent theses have included: experiment sample sizes on influence diagrams, Markov process regression, and quantile function methods for decision analysis. The Engineering Risk Research Group (ERRG) is focused on complex engineered systems (recently, for example, the optimal architecture of satellites and the deflection of asteroids’ trajectories), cyber security, and the risks involved in games against adversaries (e.g., counter-terrorism, counter-insurgency, or staying ahead of narco-traffickers). Specialized course work includes the mathematical foundations for modeling dynamic uncertain environments to value and manage uncertain opportunities and risks, applications to public policy and strategy, and an opportunity to work on client projects under faculty guidance. Risk analysis specifically requires optimization, stochastic processes, economics and game theory.
Energy and Environmental Policy
Students who specialize in Energy and Environmental Policy are prepared for careers that include academic positions, management consulting, NGOs, governmental positions, policy and economic analysis, and energy and environmental modeling. Particular recent attention focuses on integrated assessment of global climate change mitigation/impacts/adaption; energy demand analysis including economic and/or behavioral factors associated with energy efficiency; market structure for electricity systems or for environmental mitigation; behavioral economics related to energy; comparative use of energy models through the Energy Modeling Forum. Students learn about economic analysis, mathematical modeling, optimization, decision analysis, policy analysis, econometrics, and a variety of other courses, depending on the student's particular background and interests. Students typically become affiliated with the Energy Modeling Forum and/or the Precourt Energy Efficiency Center.
Entrepreneurship
The Entrepreneurship area focuses on two areas of study: on the formation and growth of new companies, and on the role of public policy in shaping the rate, nature and success of entrepreneurial activities. Students in the area take courses in Organization Theory, Economics, Sociology, Entrepreneurship and Strategy as well as methods courses in regression analysis, difference-in-differences, case study research and other state of the art approaches. Recent dissertations include studies of how entrepreneurs shape new markets, the role of institutional change such as bankruptcy reforms in the formation of new firms in Asia and Latin America, implications of different forms of financing for innovation and venture success, and how venture CEOs manage their boards. PhD students in the area typically are affiliated with the Stanford Technology Ventures Program (STVP).
Finance
The Finance area focuses on the study of financial risks, institutions, markets, and technology. Students in the area take courses in probability, statistics, optimization, finance, economics, computational mathematics, computer science, as well as a variety of other courses. Recent dissertation topics include studies of machine learning methods for risk management; systemic financial risk; algorithmic trading; optimal order execution; large-scale portfolio optimization; mortgage markets; and statistical testing of financial models. PhD students in the area typically are affiliated with the Center for Financial and Risk Analytics (CFRA).
Health Policy
The Health Policy area focuses on the application of analytical, computational, and economic tools to inform decision making in health. Areas of interest include clinical decision making, public health decision making, and healthcare operations management. Students in the Health Policy area take courses in optimization, probability and statistics, economics, operations management, cost-effectiveness analysis, and health policy modeling, as well as a variety of other courses. Recent PhD dissertations in Health Policy include studies of managing uncertainty in medical decision making; resource allocation for infectious disease control; optimizing patient treatment decisions in the presence of rapid technological advances; and economic analysis of HIV prevention and treatment portfolios. PhD students in the Health Policy area are often affiliated with the Center for Health Policy /Program on Clinical Outcomes Research (CHP/PCOR) in the Medical School.
Information Systems
Information Systems focuses on problems at the interface of social and computational science. Students in this area take a diverse set of courses in statistics, computer science, economics, and sociology. Recent PhD dissertations include a design and analysis of a peer-to-peer credit network and reputation system, analysis of dynamic online markets, and fast algorithms for large scale personalized recommendations. Information Systems students are typically affiliated with the Social Algorithms Lab (SOAL).
National Security Policy
see the Engineering Risk Research Group under Decision and Risk Analysis
Optimization
Optimization focuses on research for new algorithms to solve a wide variety of optimizations problems. Typically algorithms are designed to solve a specific class of problems anyone of which covers an eclectic set of real problems. Real problems are often used in the development of new algorithms to test their efficacy. Research also covers developing new algorithms to solve specific real problems for which general-purpose algorithms have not proved sufficiently successful. All the faculty working on optimization are affiliated with ICME. Apart from MS&E courses students studying optimization typically take courses from the Statistics department and the Computer Science department.
Organizations
The Organizations area focuses on the study of work, mainly in technical settings and considers the organizational issues implicated at the intersection of work and technology. Students in the area take courses in Sociology, Social Psychology, Organizational Theory, and Organizational Behavior as well as field research methods courses including ethnography, surveys, and social network analysis. Recent PhD dissertations include studies of global collaboration, flash teams, social movements, occupational identities, and collective innovation. PhD students are typically affiliated with the Center for Work, Technology, and Organizations.
Probability and Stochastic Systems
In many complex systems, randomness plays an integral part in the outcome of an event. The likelihood of a system to produce an event is based on the initial state and a range of parameters. Results are predicted and described by a number of mathematical methods in this academic field, including: axioms of probability, probability trees, random variables, distributions, conditioning, expectation, change of variables, and limit theorems, discrete and continuous time parameter Markov chains, queuing theory, inventory theory and simulation.
Production and Operations Management
The Production and Operations Management area analyzes problems such as capacity planning, production scheduling, and inventory control in both standard and novel environments, generally using existing quantitative and economic modeling techniques. Students concentrating in this area take courses in operations management, operations research (both deterministic and stochastic models), economics, game theory, and doctoral seminars in operations management offered either by the MS&E Department or the Operations, Information & Technology area in Stanford’s Graduate School of Business. Recent dissertation topics include studies of sustainability concerns in global outsourcing; warranty inventory management; and the use of RFID tools in supply chain management. Faculty also have research interests in mechanism and market design, including modeling kidney exchange programs and student-school matching. In addition, faculty from the Operations, Information & Technology area in Stanford’s Graduate School of Business have often supervised all or a portion of student dissertations in the POM area.
Strategy
The Strategy area focuses on innovation, competition, and collaboration within and across firms, particularly technology-based ones, in order to achieve competitive advantage. Students typically take coursework in Strategy, Organization Theory, Economics, and Entrepreneurship, and become proficient in multiple methods including quantitative approaches such as regression and difference-in-differences as well other methods such as case study research and simulation. Recent PhD dissertations have included studies of ecosystem strategy in the solar industry, competitive interaction in the software industry, platform strategies, and CEO succession in family businesses. Students are typically affiliated with the Stanford Technology Ventures Program (STVP).
