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. With approval from the students' adviser, one quarter of the requirement may be fulfilled by working as a Course Assistant (CA). ... Facebook LinkedIn. Attitudes toward ethical dilemmas through an explicit personal code. Prerequisite: 221 or equivalent. To ensure an early start, all students must work at least 25% of their time in their first year as a research assistant with a faculty member. Management Science and Engineering . Directed Reading and Research. MS&E also participates with the departments of Computer Science, Mathematics, and Statistics in a program leading to a B.S. The Program in Science, Technology, and Society is a dynamic interdisciplinary major that provides students with a liberal arts education for the twenty-first century. 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. Faculty in the focal area of the week comment on the student presentations. Information service engineering and management. Disaster recovery networks. Virus and worm propagation dynamics and containment. Introduces core marketing concepts to bring a new product or service to market and build for its success. Students are expected to be able: MS&E offers programs leading to the degrees of Master of Science and Doctor of Philosophy. Multiname modeling: index and tranche swaps and options, collateralized debt obligations. Same as: Accelerate. It is the responsibility of the student's adviser to find an appropriate orals chair. prepares engineers for a lifelong career addressing the critical technical and managerial needs of private and public organizations. In addition to the required prerequisite and minor courses, it is recommended that students also take the following courses. Ali Mottaghi. Students will master the concepts of organizational design, with an emphasis on applying them to modern challenges (technology, growth, globalization, and the modern workforce). This committee plans the student’s program jointly with the student. Foundation in Organizational Behavior (five courses): Plus three of the following, which must include at least one 37x course and one 38x course: Statistics and Research Methods (examples; three courses required). M.S. The lists may differ depending on whether the student is pursuing an M.S. The three main focuses are data privacy, personalization and targeting algorithms, and online experimentation. A limited number of fellowships and assistantships are awarded each year. nnA key objective of the class will be to get students to think about how social choice theory can be applied to real-life problems through the design of algorithms. Topics include common voting rules and impossibility results; ordinal vs cardinal voting; market approaches to large scale decision making; voting in complex elections, including multi-winner elections and participatory budgeting; protocols for large scale negotiation and deliberation; fairness in societal decision making;nalgorithmic approaches to governance of modern distributed systems such as blockchains and community-mediated social networks; opinion dynamics and polarization. The department’s engineering research strength is integrated with its educational program at the undergraduate, master’s, and doctoral levels: graduates of the program are trained as engineers and future leaders in technology, policy, and industry. Autonomic self-defending networks. Management Science and Engineering. Prerequisites: 220, 252, or equivalents, or consent of instructor. MS&E 376. Students are expected to earn a letter grade of A- or better in all courses counted for the requirements. Conditional independence and requisite information. Reinforcement Learning: Frontiers. Lectures, presentations, and discussion. Prerequisite: 263 and a mandatory meeting during the preceding Winter quarter to choose projects. 3 Units. Prerequisites: MS&E 250A and consent of instructor. Like technology for medicine, finance is being rebuilt as machine learned code, algorithmic investment rules and regulatory monitoring. Applications: matching marketplaces (NRMP, Upwork, college admissions), dynamic pricing in ride-sharing, advertising mechanisms, reputation systems, platform design, kidney exchange and organ allocations, food banks. For graduate students only, with a preference for engineering and science majors. Same as: MS&E 140. Contact. 1 Unit. Contemporary Themes in Work and Organization Studies. 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. 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. For further information, see http://scpd.stanford.edu/programs/graduate-certificates. Other graduates make careers tackling the problems faced by local, national, and international governments by developing new healthcare systems, new energy systems and a more sustainable environment. Transforming finance through engineering requires finding, applying and evolving codes of professional conduct to make sure that engineers use their skills within legal and ethical norms. These learning outcomes are used in evaluating students and the department's undergraduate program. Prerequisites: CME 100 or MATH 51; 120, 220 or STATS 116; experience with R at the level of CME/STATS 195 or equivalent. Understanding concepts of cost-effectiveness analysis. After that time, enrollment may be in MS&E or Law, and students may choose courses from either program regardless of where enrolled. and the M.S. Required for all students are three problem sets, three in-class exams, and a take-home final exam. Combinatorial and mathematical programming (integer and non-linear) techniques for optimization. For additional information and sample programs see the Handbook for Undergraduate Engineering Programs (UGHB). Primarily for doctoral students. Probability is the foundation behind many important disciplines including statistics, machine learning, risk analysis, stochastic modeling and optimization. The Management Science and Engineering graduate certificate program gives you a strong foundation for a strategic decision-making mindset and the opportunity to design your own plan of study at the crossroads of policy, management, and technology. MS&E 325. 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, economics, law, medicine, or public policy. Prerequisite: 145, 245A, or equivalent. The MS&E student services staff are also an important part of the advising team. 1 Unit. 3 Units. Prerequisite: 220 or equivalent, or consent of instructor. Decision Analysis Seminar. Structuring relationships with key customers, partners and suppliers. Relevance and decision diagrams to represent inference and decision. 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. Same as: MS&E 112. Students will also gain mastery of skills necessary for success in today's workplace (working in teams, communicating verbally, presenting project work). 3 Units. Possible topics include (but are not limited to) critical point computation of non-convex functions, linear system solving, eigenvector computation, finite sum optimization, linear system solving, principle component analysis, interior point methods, linear programming, semi-definite programming, and cutting-plane methods. Methods: simplex and interior-point, gradient, Newton, and barrier. The student needs to reserve a room, and meet with the student services manager to complete the oral examination schedule and pick up other paper work. Topics vary year to year based on interest. Structuring relationships with key customers, partners and suppliers. 3 Units. Prerequisite: 120, CS 106A, or equivalents. Contact. Limited enrollment. Introduction to Optimization. 3-4 Units. This course provides an in-depth undergraduate-level introduction to fundamental ideas and tools of probability. Topics: scientific discovery, innovation search, organizational learning, evolutionary approaches, and incremental and radical change. MS&E 332. Stochastic Methods in Engineering. MS&E 245B. This plan should be provided to the students' academic adviser for review no later than May 15 each calendar year. MS&E 120. Linear-quadratic-Gaussian decision models and Kalman filters. Decision analysis uses a structured conversation based on actional thought to obtain clarity of action in a wide variety of domains. Coterminal master’s degree candidates are expected to complete all master’s degree requirements as described in this bulletin. This course provides an introduction to how networks underly our social, technological, and natural worlds, with an emphasis on developing intuitions for broadly applicable concepts in network analysis. Theory of polyhedral convex sets, linear inequalities, alternative theorems, and duality. Limited enrollment. Team applications required in February, see hacking4defense.stanford.edu. master’s students have breadth as well as depth. How to ensure focus, discipline, and passion when making important decisions. Introduction to accounting concepts and the operating characteristics of accounting systems. Enrollment limited. 4 Units. Class lectures will be supplemented by data-driven problem sets and a project. 3 Units. Case studies; guest speakers from government (FDA) and industry. 4 Units. . The department’s mission is, through education and research, to advance the design, management, operation, and interaction of technological, economic, and social systems. 3 Units. 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. Recommended: basic accounting. Enrollment limited. Courses taken in Health and Human Performance (e.g. Prerequisites: calculus and linear algebra. Same as: ENGR 62X, MS&E 111X. To personalize their exploration, students select additional courses from different application areas of the department, with greater emphasis in one of them. Three phases: risk assessment, communication, and management. The following are a number of sample programs: Toggle School of Earth, Energy and Environmental Sciences, Handbook for Undergraduate Engineering Programs (UGHB), Undergraduate Major Unit Requirements and WIMs, Involuntary Leave of Absence and Return Policy, Main Quadrangle • Memorial Court • Oval • White Plaza, Sexual Harassment and Consensual Sexual or Romantic Relationships, Student Non-​Academic Grievance Procedure, Title IX of the Education Amendments of 1972, Visitor Policy • University Statement on Privacy, School of Earth, Energy and Environmental Sciences, Emmett Interdisciplinary Program in Environment and Resources (E-​IPER), Institute for Computational and Mathematical Engineering, Comparative Studies in Race and Ethnicity (CSRE), Division of Literatures, Cultures, and Languages, Russian, East European and Eurasian Studies, Stem Cell Biology and Regenerative Medicine, Mission of the Undergraduate Program in Management Science and Engineering, Graduate Programs in Management Science and Engineering, Bachelor of Science in Management Science and Engineering, Management Science and Engineering (MS&E), Management Science and Engineering (MS&E) Minor, Coterminal Program in Management Science and Engineering, Master of Science in Management Science and Engineering, Computational Social Science (four courses required), Financial Analytics Concentration (five courses required), Technology and Engineering Management Concentration (four courses required), Specialized Concentrations (must have approval of the academic adviser), Decision and Risk Analysis Concentration (four courses required), Energy and Environment Concentration (six courses required), Health Systems Modeling and Policy Concentration (four courses required), Joint MS&E and Master of Public Policy Degree, Doctor of Philosophy in Management Science and Engineering, Degree Progress and Student Responsibility, Ph.D. Minor in Management Science and Engineering, Linear Algebra, Multivariable Calculus, and Modern Applications, Introduction to Matrix Methods (formerly CME 103), Structure and Reactivity of Organic Molecules, Ethics, Public Policy, and Technological Change, Expanding Engineering Limits: Culture, Diversity, and Equity, Ethics and Equity in Transportation Systems, Technology and National Security: Past, Present, and Future, International Security in a Changing World, The Public Life of Science and Technology, Introduction to Optimization (Accelerated), Introduction to Electromagnetics and Its Applications, Introduction to Materials Science, Nanotechnology Emphasis, Introduction to Materials Science, Energy Emphasis, Introduction to Materials Science, Biomaterials Emphasis, Introduction to Bioengineering (Engineering Living Matter), Accounting for Managers and Entrepreneurs, Decision Analysis I: Foundations of Decision Analysis, Project Course in Engineering Risk Analysis, Mathematical Programming and Combinatorial Optimization, Fundamentals of Data Science: Prediction, Inference, Causality, Introduction to Computational Social Science, Introduction to Stochastic Control with Applications, Service Operations and the Design of Marketplaces, Future of Work: Issues in Organizational Learning and Design, Accounting for Managers and Entrepreneurs (may be used as one of the required electives above), Organizational Behavior: Evidence in Action, Introduction to Regression Models and Analysis of Variance, Natural Language Processing with Deep Learning, Market Design and Resource Allocation in Non-Profit Settings, Introduction to Human-Computer Interaction Design, Microeconomics I For Non-Economics PhDs students, Machine Learning with Application to Text as Data, Classic and contemporary social psychology research, Massive Computational Experiments, Painlessly, Advanced Investment Science (if not used above), Financial Risk Analytics (if not used above), Reinforcement Learning for Stochastic Control Problems in Finance, Optimization of Uncertainty and Applications in Finance, Big Financial Data and Algorithmic Trading, Introduction to Optimization (Accelerated) (whichever of optimization or analytics wasn't taken for core), Stochastic Modeling (any of the following courses may be substituted only if 221 or an equivalent has been taken), Dynamic Programming and Stochastic Control, Patent Law and Strategy for Innovators and Entrepreneurs, Technology Assessment and Regulation of Medical Devices, The Lean LaunchPad: Getting Your Lean Startup Off the Ground, "Hacking for Defense": Solving National Security issues with the Lean Launchpad, Influence Diagrams and Probabilistics Networks, Advanced Methods in Modeling for Climate and Energy Policy, Energy Systems II: Modeling and Advanced Concepts, Public Economics and Environmental Economics Seminar, Economic, Legal, and Political Analysis of Climate-Change Policy, Advanced Decision Science Methods and Modeling in Health, Analysis of Costs, Risks, and Benefits of Health Care, Decision Analysis II: Professional Decision Analysis, Decision Analysis III: Frontiers of Decision Analysis, Probabilistic Graphical Models: Principles and Techniques, Statistical Methods in Engineering and the Physical Sciences, Linear Algebra with Application to Engineering Computations, Introduction to Numerical Methods for Engineering, Risk Analytics and Management in Finance and Insurance, Current Topics in Strategy, Innovation and Entrepreneurship, Entrepreneurship Doctoral Research Seminar, Statistical Methods for Behavioral and Social Sciences, Sociological Methodology II: Principles of Regression Analysis, Sociological Methodology III: Models for Discrete Outcomes, New Models and Methods in the Social Sciences, Doctoral Research Seminar in Health Systems Modeling, Doctoral Research Seminar in Energy-Environmental Systems Modeling and Analysis, Directed Reading and Research (Methods Apprenticeship), depth in conceptual and analytical foundations, comprehensive coverage of functional areas of application. Advancement to Ph.D. candidacy is determined at the end of the student’s second year of studies, based on the following three components: Students pursuing a Ph.D. in another department who wish to receive a Ph.D. minor in Management Science and Engineering should consult the MS&E student services office. Same as: CME 308, MATH 228. MS&E 302. MS&E 241. Making use of this information, however, requires both statistical tools and an understanding of how the substantive scientific questions should drive the analysis. 3-4 Units. Human action and relations in society in the light of previous thought, and research on the desired form of social interactions. Andrew Zhao, MS '19 Degree: MS in MS&E Concentration: Computational Social Science Title: Surface Warfare Officer Company: United States Navy Sarah Stebbins, MS '19 Degree: MS in MS&E Concentration: Technology Engineering & Management Title: Technology Investing Analyst Company: ICONIQ Strategic Partners Qin En Looi, BS '19 Degree: BS in MS&E Concentration: Finance &