Same as: CS 366. Stochastic processes and models in operations research. Management Science (MS) can be defined as: “A problem-solving process used by an interdisciplinary team to develop mathematical models that represent simple-to-complex functional relationships and provide management with a basis for decision-making and a means of uncovering new problems for quantitative analysis”. Output analysis (autoregressive, regenerative, spectral, and stationary times series methods). Typically, this occurs at a faculty meeting at the end of Spring Quarter, and an appropriate email notification is sent over the summer to the student and their adviser. 3 Units. The University oral examination may be scheduled after the dissertation reading committee has given tentative approval to the dissertation. Through the core, students in the program are exposed to the breadth of faculty interests and prepared to study different areas of application of the department's methodologies. Big Financial Data and Algorithmic Trading. 4 Units. Learn through forming teams, a mentor-guided startup project focused on developing students' startups in international markets, case studies, research on the unequal access to wealth creation and innovation via entrepreneurship, while also networking with top entrepreneurs and venture capitalists who work across borders. 3 Units. Advanced students will make presentations designed for first-year doctoral students regardless of area. Focus on quantitative models dealing with sustainability and related to operations management. The Policy and Strategy (P&S) Area addresses policy and strategy questions in a variety of organizational and societal settings. or Ph.D. degree in MS&E. Approximation Algorithms. The committee then makes a recommendation to the CSS area and the MS&E department regarding qualification of the student for the Ph.D. program in CSS. 2-3 Units. Read further to learn about the curriculum of a typical B.S. An important component of the class is a research project aimed at understanding a focused issue in reinforcement learning. Students must take a minimum of 45 course units as follows: Courses for Core and Concentration must cover each of the three sub-areas below. To maintain good standing in the degree program second-year students must: submit a candidacy form signed by at least one MS&E faculty member with whom they have or will complete research rotations, tutorials, or papers, and listing the course requirements agreed upon by both the student and the program adviser; complete at least two one-quarter research rotations or tutorials, or one two-quarter research rotation, tutorial, or research paper, continuing to develop relationships with faculty members who might serve as dissertation adviser or reading committee member; complete 30 units, including most, if not all, of the required courses listed on the candidacy form; To maintain good standing in the degree program, third-year students must: submit a progress form listing the dissertation topic and signed by the dissertation adviser (if the dissertation adviser is not an MS&E faculty member, the form must also be signed by an MS&E faculty member who agrees to be on the student's reading committee, as well as the student's point of contact within the department); complete 30 units, including any remaining depth courses. Prerequisite: consent of instructor. in Mathematical and Computational Science. They deal with human traits and, hence, are to be employed creatively given the requirements of the position. Investment valuation models can optimize short term or long term returns, by optimizing or ignoring environmental and social impacts. The educational objectives of the undergraduate degree program are: See also the department's undergraduate Learning Outcomes for additional learning objectives. MS&E 250B. Examples from inventory, overbooking, options, investment, queues, reliability, quality, capacity, transportation. What is your highest level of education completed? Specific topics covered include: the role of theory in field research, variance versus process models, collecting and analyzing different kinds of data (observation, interview, survey), levels of analysis, construct development and validity, blending qualitative and quantitative data (in a paper, a study, or a career), and writing up field research for publication. Doctoral research seminar, limited to Ph.D. students. 1 Unit. Management science often has drawn its concepts and methods from the older disciplines of economics, business administration, psychology, sociology, and mathematics. 3 Units. Students will apply course concepts and learning to identify opportunities for the U.S. to maintain its technological edge and compete more effectively in this era of great power rivalry. Both the adviser and the advisee are expected to maintain professionalism and integrity. Students are encouraged to talk with both the faculty program adviser and the student services office as they consider courses. To receive a permission code to enroll, please submit this form: https://forms.gle/bFtMtwJMyaCJRhkf8 with statement and offer letter. May be repeated for credit. Same as: CEE 372, ENERGY 309, © 2020-21 Stanford University. Aimed at PhD students, but open by permission to Master's students and to students in other Stanford programs with relevant coursework or experience in analytics and statistics. Learning from evidence. Decision trees, utility, two-stage and multi-stage decision problems, approaches to stochastic programming, model formulation; large-scale systems, Benders and Dantzig-Wolfe decomposition, Monte Carlo sampling and variance reduction techniques, risk management, portfolio optimization, asset-liability management, mortgage finance. Sustainable Energy Interdisciplinary Graduate Seminar. Foundation in Policy and Strategy (three): The student must select a program of four or more electives including disciplinary depth courses that reflects his or her interests and this approved by the Policy and Strategy faculty. Enrollment Limited. What kinds of inequalities are created by limited access to capital or education and what role does entrepreneurship play in upward mobility in societies globally? Students take the area qualifying exam at the beginning of their second year of study. MS&E 249. MS&E 112. Mathematical Programming and Combinatorial Optimization. 3-4 Units. Students are active contributors to the advising relationship and we urge them to proactively seek academic and professional guidance and take responsibility for informing themselves of policies and degree requirements for their graduate program. Stochastic Modeling. Differential equations are used as a mathematical language to facilitate discussions on dynamic phenomena. MS&E 355. MS&E 284. Service Learning Course (certified by Haas Center). Students should discuss their course schedule with their dissertation advisers. The course starts with classic results characterizing matchings in bipartite and general graphs and explores connections with algebraic graph theory, permanent, Pfaffian and counting and sampling matchings. Courses approved for the minor must form a coherent program, and include a breadth of courses from across the department. MS&E 352. Alternatively, an enrolled student in either the Law School or MS&E may apply for admission to the other program and for joint degree status in both academic units after commencing study in either program. University requirements for the master’s degree are described in the "Graduate Degrees" section of this bulletin. This course engages with ethical challenges in the modern practice of data science. Decision Analysis III: Frontiers of Decision Analysis. Multiname modeling: index and tranche swaps and options, collateralized debt obligations. MS&E 347. Credit Risk: Modeling and Management. The program leading to the B.S. 3-4 Units. Network Structure and Epidemics. MS&E 302. ... learning and assessment techniques provided by WebCT are suitable for the evaluation of student responses in a subject like English. 3 Units. The course builds on concepts presented in MS&E 193/293: Technology and National Security and provides a strong foundation for MS&E 297: Hacking for Defense. Bachelor of Science in Organizational Management. Topics include 1) best practices in research design, model design and selection; 2) types of models available, taxonomy, core concepts, and limitations; 3) interpreting and presenting model results; and 4) advanced topics and recent literature, e.g. The application of mathematical models to problems in health policy. The Ph.D. degree in MS&E is intended for students primarily interested in a career of research and teaching, or high-level technical work in universities, industry, or government. Primarily for doctoral students. Let us know if you have suggestions to improve this article (requires login). Students will develop intuition about the contingent relationship between the nature of the research question and the field research methods used to answer it as a foundation for conducting original field research. Introduces core marketing concepts to bring a new product or service to market and build for its success. Same as: CME 241. A program may allow a student to specialize in areas like logistics or operations. During this presentation, the student must also provide the name of their chosen focus area, and the list of courses that the student has completed and intends to complete in the core as well as in the chosen focus area. For additional information and sample programs see the Handbook for Undergraduate Engineering Programs (UGHB). Doctoral Research Seminar in Health Systems Modeling. 1-3 Unit. In addition to beginning an appropriate course program, students must pass two quarters of tutorial and an oral examination to obtain qualification. MS&E 120. Three phases: risk assessment, communication, and management. Topics include group effectiveness, norms, group composition, diversity, conflict, group dynamics, temporal issues in groups, geographically distributed teams, and intergroup relations. Closely related to the field of organizational studies, strategic management … degree and an M.S. Students taking the course for 4 units of credit must also complete and present a team project that analyzes a decision currently being made by an organization of their choice. Switching, routing and shortest path algorithms. Limited enrollment. Limited enrollment. Applications include matching students to schools, college admissions and the failure the desire to balance equity and merit, assigning vaccines, assigning interns to hospitals, assigning organs to patients, auction designs and pricing, information design, online platforms, allocation of food, transportation, and emissions. The qualification procedure is based on depth in an area of the student’s choice and preparation for dissertation research. Same as: CEE 301, ENERGY 301. MS&E 140. MS&E 371. 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. Introduction of core algorithmic techniques and proof strategies that underlie the best known provable guarantees for minimizing high dimensional convex functions. Examples and problems from various applied areas. Principal methods of economic analysis of the production activities of firms, including production technologies, cost and profit, and perfect and imperfect competition; individual choice, including preferences and demand; and the market-based system, including price formation, efficiency, and welfare. Prerequisite: 145, 245A, or equivalent. Students must apply for a degree program through the standard application process, and must meet the standard application deadlines. For the dual degree, admission to two departments is required, but is coordinated by designated members of both admissions committees who make recommendations to the committees of their respective departments. Leading Organizational Change II. Focus on broad canonical optimization problems and survey results for efficiently solving them, ultimately providing the theoretical foundation for further study in optimization. Computational issues and general theory. The course is fast-paced, but it has no prerequisites. MS&E 240. 4 Units. For further information, see http://scpd.stanford.edu/programs/graduate-certificates. 4 Units. Admission by order of enrollment. Students learn ethical theories and tools from which they create their own personal ethical codes and test them against established ethical principles, class discussion, homework, class presentations, and situations from work and life. Will then draw on techniques from operations research and economics to explore the design of resource allocation platforms in emerging applications including housing, humanitarian logistics, volunteer coordination, food allocation, conservation and sustainability, and informal markets in the developing world. . 3 Units. BSc Computer Science degree course is a 3 year course. Simulation in a parallel environment. A faculty member is more likely to accept the responsibility of supervising the research of a student whom he or she knows fairly well than a student whose abilities, initiative, and originality the faculty member knows less well. All required; see SoE Basic Requirements 1 and 2. interaction with other Stanford departments, Silicon Valley industry, and organizations throughout the world. Same as: CS 269O. Topics in Management Science and Engineering. In this class student teams will take actual national security problems and learn how to apply lean startup principles, ("business model canvas," "customer development," and "agile engineering) to discover and validate customer needs and to continually build iterative prototypes to test whether they understood the problem and solution. Ph.D. students are required to take a minimum of 2 advanced-content courses chosen with input from their adviser. Due to the fact that it is near impossible to perform experiments in finance, there is a need for empirical inference and intuition, any model should also be justified in terms of plausibility that goes beyond pure econometric and data mining approaches. As a course project, students will develop a simple decision model to evaluate a current health policy problem. To receive a permission code to enroll, please submit this form: https://forms.gle/bFtMtwJMyaCJRhkf8 with statement and offer letter. "Hacking for Defense": Solving National Security issues with the Lean Launchpad. Found insideWe all want our work to enrich the world. As analytics professionals, we are fortunate - this is our time! We live in a world of pervasive data and ubiquitous, powerful computation. In this class, we will focus on questions of how entrepreneurship may exacerbate or alleviate inequalities in society across race/ethnicity, gender and class. MS&E 326. This article was most recently revised and updated by, https://www.britannica.com/topic/management-science. It is recommended that students participate in research rotations with MS&E and related faculty to facilitate the development of these relationships. The course gives an introduction to Catastrophe Theory, which provides a mathematical model for certain discontinuous phenomena like the crash of the stock market and the extinction of species. Research input is solicited and an individual progress report spelling out the forthcoming milestones and any remedial action needed to maintain status is sent to the student via email. MS&E 230. The following courses are required to fulfill the minor requirements: Students completing a calculus-based probability course such as CS 109 or STATS 116 for their major, may substitute another MS&E course for MS&E 120. Enrollment limited to 60 students. Required a project in dynamic system modeling. Same as: CME 307. MS&E 182A. Market failures occur due to a variety of frictions and need design to be fixed. degree in Management Science and Engineering (MS&E) is outlined in the School of Engineering section of this bulletin; more information is contained in the School of Engineering’s Handbook for Undergraduate Engineering Programs. Energy/environmental policy issues such as automobile fuel economy regulation, global climate change, research and development policy, and environmental benefit assessment. Mathematical Programming and Combinatorial Optimization. In particular, focus will be on first-order methods for both smooth and non-smooth convex function minimization as well as methods for structured convex function minimization, discussing algorithms such as gradient descent, accelerated gradient descent, mirror descent, Newton's method, interior point methods, and more. Prerequisite: basic preparation in probability, statistics, and optimization. See dschool.stanford.edu/classes for more information. 4 Units. Prerequisite: 245A. Autonomic self-defending networks. Focus is on the role of organizations in society, the ways that organizations can "do good," the challenges organizations face in attempting to "do good", limitations to current ways of organizing, alternative ways to organize and lead organizations that are "good," and the role and responsibilities of individuals in organizations. Students become acquainted with a variety of approaches to research design, and are helped to develop their own research projects. 3 Units. MS&E 323. Copyright Complaints By the end of the class, successful students will be equipped with the knowledge and network to create impactful business ideas, many of which have been launched from this class. Faculty program advisers additionally guide doctoral students in designing and conducting research, and development of teaching pedagogy. Perspectives: problem formulation, analytical theory, computational methods, and recent applications in engineering, finance, and economics. Future of Work: Issues in Organizational Learning and Design. Topics will include random utility models, item-response theory, rank aggregation, centrality and ranking on graphs, and random graphs. All other trademarks and copyrights are the property of their respective owners. The finance area focuses on the quantitative and statistical study of financial risks, institutions, markets, and technology. This course explores how technology advances in areas like Cyber, Space, AI, Machine Learning, and Autonomy will create new types of military systems that will be deployed in modern conflicts, and the new operational concepts, organization and strategies that will emerge from these technologies. The Bachelor of Science in Business Administration program offers a wide range of specialized majors, namely Business Economics, Financial Management, Human Resource Management, and Marketing Management. Recommended: 212. In either case, approval may consist of a list applicable to all joint degree students or may be tailored to each individual student’s program. Organizations: Theory and Management. Prerequisites: MS&E 245A or similar, some background in probability and statistics, working knowledge of R, Matlab, or similar computational/statistical package. Hedge Fund Management. We therefore expect students to read regular communication from the Registrar's office and Student Services regarding upcoming academic deadlines and policy updates, and to be responsible for complying with the university and program requirements. Dynamic System: Provides a solid foundation in understanding and modeling the dynamics of change. Project work includes problem identification and definition, data collection and synthesis, modeling, development of feasible solutions, and presentation of results. The course is intended to enable students to design and implement risk analytics tools in practice. Buy-Side Investing. Technical material includes normal and extensive form games, zero-sum games, Nash equilibrium and other solution concepts, repeated games, games with incomplete information, auctions and mechanism design, the core, and Shapley value. Variance reduction techniques (antithetic variables, common random numbers, control variables, discrete-time, conversion, importance sampling). Prerequisites: working knowledge of a programming language such as C, C++, Java, Python, or FORTRAN; calculus-base probability; and basic statistical methods. The course covers the notions of equilibrium, stability, growth and limit cycle of dynamic systems and discussed in terms of examples in product market penetration, business competition, ecology and spread of epidemics. Strategy in Technology-Based Companies.
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