We emphasize quantitative analytic skills and an entrepreneurial spirit. Through course work and guided research, the program prepares students to make original contributions in Management Science and Engineering and related fields. Students will master the concepts of organizational design, with an emphasis on applying them to modern challenges (technology, growth, globalization, and the modern workforce). Issues include instrument design, technology development, resource management, multiparty negotiation, and dealing with complexity and uncertainty. Emphasis is on integrated use of modeling tools from diverse methodologies and requirements for policy making application. Emphasis is on integrated use of modeling tools from diverse methodologies and requirements for policy and corporate strategy development. In this course we will survey these results and cover the key algorithmic tools they leverage to achieve these breakthroughs. Related convex analysis, including the separating hyperplane theorem, Farkas lemma, dual cones, optimality conditions, and conic inequalities. Applications to combinatorial optimization, sensor network localization, support vector machine, and graph realization. This course will provide an introduction to the design and analysis of algorithms for these modern data models. MS&E students are candidates for careers in consulting, product and project management, financial analysis, and work in policy arenas. Many have become leaders in technology-based businesses which have an increasing need for analytically oriented people who understand both business and technology. Students will also gain mastery of skills necessary for success in today's workplace (working in teams, communicating verbally, presenting project work). Primarily for master's students; also open to undergraduates and doctoral students. Explores the relation between technology, war, and national security policy from early history to modern day, focusing on current U. national security challenges and the role that technology plays in shaping our understanding and response to these challenges. response and adaptation to new technologies of military significance. Prerequisites: ECON 50, MS&E 211, MS&E 252, or equivalents, or permission of instructor. Prerequisites: ECON 50, MS&E 211, MS&E 252, or equivalents, or permission of instructor. "Hacking for Defense": Solving National Security issues with the Lean Launchpad. In a crisis, national security initiatives move at the speed of a startup yet in peacetime they default to decades-long acquisition and procurement cycles. Ethical theory, feasibility, and desirability of a social order in which coercion by individuals and government is minimized and people pursue ends on a voluntary basis. Theory of polyhedral convex sets, linear inequalities, alternative theorems, and duality. Applications, theories, and algorithms for finite-dimensional linear and nonlinear optimization problems with continuous variables. Topics include interior-point methods, relaxation methods for nonlinear discrete optimization, sequential quadratic programming methods, optimal control and decomposition methods. Possible topics include but are not limited to, spectral graph theory, sparsification, oblivious routing, local partitioning, Laplacian system solving, and maximum flow.
The department’s mission is, through education and research, to advance the design, management, operation, and interaction of technological, economic, and social systems. Decision Analysis III: Frontiers of Decision Analysis. The concept of decision composite; probabilistic insurance and other challenges to the normative approach; the relationship of decision analysis to classical inference and data analysis procedures; the likelihood and exchangeability principles; inference, decision, and experimentation using conjugate distributions; developing a risk attitude based on general properties; alternative decision aiding practices such as analytic hierarchy and fuzzy approaches. The major is designed to allow a student to explore all three areas of the department in greater depth. Coterminal master’s degree candidates are expected to complete all master’s degree requirements as described in this bulletin. Is Silicon Valley-style entrepreneurship possible in other places? Open to graduate students interested in technology driven start-ups. How entrepreneurial strategy focuses on creating structural change or responding to change induced externally. Themes include controversial and disruptive insights, competitive analysis, network effects, organizational design, and capital deployment. This program allows Stanford undergraduates an opportunity to work simultaneously toward a B. in Management Science and Engineering or another quantitative major, and an M. University requirements for the coterminal master’s degree are described in the “Coterminal Master’s Program” section. Practical introduction to financial risk analytics. The focus is on data-driven modeling, computation, and statistical estimation of credit and market risks. How does an entrepreneur act differently when creating a company in a less-developed institutional environment? Provides the experience of an early-stage entrepreneur seeking initial investment, including: team building, opportunity assessment, customer development, go-to-market strategy, and IP. Grabber-holder dynamics as an analytical framework for developing entrepreneurial strategy to increase success in creating and shaping the diffusion of new technology or product innovation dynamics. Case studies, expert guests, and experiential learning projects will be used. The major prepares students for a variety of career paths, including investment banking, management consulting, facilities and process management, or for graduate school in industrial engineering, operations research, business The department expects undergraduate majors in the program to be able to demonstrate the following learning outcomes. degree, a dual master’s degree in cooperation with each of the other departments in the School of Engineering, and joint master's degrees with the School of Law and the Public Policy Program. Ito integral, existence and uniqueness of solutions of stochastic differential equations (SDEs), diffusion approximations, numerical solutions of SDEs, controlled diffusions and the Hamilton-Jacobi-Bellman equation, and statistical inference of SDEs. Enrollment is limited, and project teams will be selected during the first week of class. Prerequisites: CS 261 or equivalent; understanding of basic game theory. These learning outcomes are used in evaluating students and the department's undergraduate program. For University coterminal degree program rules and University application forms, see the Registrar's coterminal degrees web site.
University requirements for the master’s degree are described in the "Graduate Degrees" section of this bulletin. Case studies based on real data will be emphasized throughout the course. Students, individually or in groups, choose, define, formulate, and resolve a real risk management problem, preferably from a local firm or institution. Scope of the project is adapted to the number of students involved. Learn through forming teams, a mentor-guided startup project focused on developing students' startups in international markets, case studies, research on the international aspects of the entrepreneurial process, and networking with top entrepreneurs and venture capitalists who work across borders. Teaching team includes serial entrepreneurs and venture capitalists. Topics: First mover versus follower advantage in an emerging market; latecomer advantage and strategy in a mature market; strategy to break through stagnation; and strategy to turn danger into opportunity.