Differential equations are used as a mathematical language to facilitate discussions on dynamic phenomena. Enrollment limited to 60 students. Topics: linear program duality and LP solvers; integer programming; combinatorial optimization problems on networks including minimum spanning trees, shortest paths, and network flows; matching and assignment problems; dynamic programming; linear approximations to convex programs; NP-completeness. Controlled queueing systems. Course themes include: Identifying markets and opportunities, defining the offering and customer experience, creating demand, generating revenue, and measuring success. The means to form ethical judgments; questioning the desirability of physical coercion and deception as a means to reach any end. Prerequisites: MS&E 241, MS&E 211, or equivalents. The Department of Management Science and Engineering leads at the interface of engineering, business, and public policy. JOB TITLE COMPANY LOCATION POSTED Software Integration Engineer Oracle San Francisco, CA March 2nd, 2020 Cloud Software Engineer Oracle San Francisco, CA Feb 25th, 2020 Product Marketing Manager Hearsay Systems San Francisco, CA Feb 18th, 2020 Director of Accounting and Revenue Management Hearsay Systems Budapest Feb 13th, 2020 Senior Data Analyst Hearsay Systems Budapest Course may be repeated for credit. Diffusion approximations, Brownian motion and an introduction to stochastic differential equations. See the “Mathematical and Computational Science” section of this bulletin. MS&E students know math, engineering, as well as behavioral science. Applied introduction to good empirical research and causal inference for social scientists and others analyzing social data. Open to advanced undergraduate and graduate students with continuing participation expectation. Prerequisite: CME 100 or MATH 51 or equivalent. Jeffrey Schox, who is the top recommended patent attorney for Y Combinator, built the patent portfolio for Twilio (IPO), Cruise ($1B acquisition), and 300 startups that have collectively raised over $3B in venture capital. Students take courses in probability, statistics, optimization, finance, economics, and computational mathematics as well as a variety of other courses. Primarily for master's students; also open to undergraduates and doctoral students. Projects involving the practical application of optimization under uncertainty to financial planning. MS&E 250B. 475 Via Ortega, Stanford, CA 94305. Introduction to Decision Analysis. 3-4 Units. Master students are encouraged to explore courses from across the department, and with multiple MS&E faculty members. 4 Units. Prerequisites: MS&E 211, 245A, 245B, or equivalents, some exposure to statistics and programming. Prerequisite: 182A or permission of instructor. 3-4 Units. Doctoral research seminar covering current topics in health policy, health systems modeling, and health innovation. 3-4 Units. Incentives and Algorithms. Students work in teams to develop skills and approaches necessary to becoming effective entrepreneurial leaders and managers. The chair must be an Academic Council member and may not be affiliated with either the Department of Management Science and Engineering nor any department in which the student's adviser has a regular appointment; emeriti professors are eligible to serve as an orals chair. MS&E 234. MS&E conducts an annual review of all doctoral students' progress on degree progress milestones and research. MS&E 245B. Those results are complemented with models and algorithms developed for modern applications in market design, online advertising, and ride sharing. 3-4 Units. Attendance is mandatory and performance will be assessed on the basis of the quality of the students¿ presentations and class participation. Prerequisites: working knowledge of a programming language such as C, C++, Java, Python, or FORTRAN; calculus-base probability; and basic statistical methods. 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. 2 Units. This course blends lecture, case discussions, readings about pertinent research, and hands-on projects to learn about what leaders and senior teams can do to bring about broad-based change in complex organizations. Economics of risk management. Students work in small teams under the supervision of the course instructor and partners at the Lucille Packard Children's Hospital, the Stanford Hospital, and other regional healthcare providers. Venture Creation for the Real Economy. Exposure to a wide range of applications. Information about loan programs and need-based aid for U.S. citizens and permanent residents can be obtained from the Financial Aid Office. in Management Science and Engineering. Structuring relationships with key customers, partners and suppliers. Principles are applied to decisions in business, technology, law, and medicine. 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. During the last two weeks of the quarter groups of first year students will make presentations on how they would approach a problem drawing on two or more of the perspectives to which they have been exposed earlier in the class. Interpretation and use of accounting information for decision making. To maintain good standing in the degree program, first-year students must: develop relationships with faculty members who can potentially serve as dissertation adviser or reading committee member. Structuring and assessment of decision problems under uncertainty. Stochastic Modeling. Course may be repeated for credit. Student must clarify deliverables, units, and grading basis with faculty member before applicable deadlines. Financial Theory and Modeling (select one): Optimization and Analytics (select whichever of optimization or analytics wasn't taken for core): Quantitative Methods and Financial Applications (select three): Operations and Analytics Concentration (four courses required). MS&E 349. Over the past decade there has been an explosion in activity in designing new provably efficient fast graph algorithms. 3 Units. Same as: INTLPOL 340. Entrepreneurial Thought Leaders' Seminar. Vast amounts of high volume, high frequency observations of financial quotes, orders and transactions are now available, and poses a unique set of challenges. 3 Units. Why prisons and jails have become COVID hotspots. PhD Student at Stanford University Department of Management Science and Engineering. MS&E 180. Facebook. Product Managers define a product's functional requirements and lead cross functional teams responsible for development, launch, and ongoing improvement. Prerequisite: consent of instructor. Single name products: corporate bonds, equity, equity options, credit and equity default swaps, forwards and swaptions. Recommended: 212. Prerequisites: basic knowledge of Excel spreadsheets, probability. Combinatorial and mathematical programming (integer and non-linear) techniques for optimization. Enrollment Limited. 3-4 Units. Same as: ENGR 62, MS&E 111. The course develops an appreciation that innovation in military systems throughout history has followed a repeatable pattern: technology innovation > new weapons > experimentation with new weapons/operational concepts > pushback from incumbents > first use of new operational concepts. Guest speakers from industry will present real-world challenges related to class concepts. As a best practice, advising expectations should be periodically discussed and reviewed to ensure mutual understanding. Technical material includes non-cooperative and cooperative games, behavioral game theory, equilibrium analysis, repeated games, social choice, mechanism and auction design, and matching markets. To maintain good standing in the degree program, fourth-year students must: select a reading committee (a dissertation adviser and two readers) with at least one member from the student's major department, and submit the reading committee form signed by each member on the reading committee; make satisfactory progress on their dissertation as determined by their dissertation adviser; if the student has not transferred any previous graduate units to Stanford, complete 30 dissertation units. Research and teaching activities are complemented by an outreach program that encourages the transfer of ideas to the environment of Silicon Valley and beyond. Leading Organizational Change. One concern with the rise of such algorithmic decision making is that it may replicate or exacerbate human bias. Topics in Management Science and Engineering. MS&E 296. MS&E 334. The presentations will be devoted to: illuminating how people in the area being explored that day think about and approach problems, and illustrating what can and cannot be done when addressing problems by deploying the knowledge, perspectives, and skills acquired by those who specialize in the area in question. Relation to MS&E 232: while 232 provides an extensive introduction to game theory, this course focuses on designing the "rules of the game" to achieve good economic outcomes and will cover only a few basic topics from MS&E 232, including more on application and algorithmic design. MS&E 250A. The Honors Cooperative Program (HCP) provides opportunities for fully employed working professionals to earn an M.S. . Same as: MS&E 146. Prerequisite: admission to PEAK Fellows Program. In addition every student pursues a specialty in one of seven areas: Students are expected to have completed both. 3-4 Units. Students should schedule three hours for the oral examination, which usually consists of a 45-minute public presentation, followed by closed-session questioning of the examinee by the committee, and committee deliberation. Current meso-level field research on organizational behavior, especially work and coordination. Preference given to students who have taken other Design Group or d.school classes. Variance reduction techniques (antithetic variables, common random numbers, control variables, discrete-time, conversion, importance sampling). During the last two weeks of the quarter, groups of first year students make presentations on how they would approach a problem drawing on two or more of the perspectives to which they have been exposed earlier in the class. MS&E 347. Credit Risk: Modeling and Management. The Stanford Center for Professional Development (SCPD) provides opportunities for employees of some local and remote companies to take courses at Stanford. Energy/environmental policy issues such as automobile fuel economy regulation, global climate change, research and development policy, and environmental benefit assessment. Every student is assigned a faculty program adviser based on their stated area within the department. 3-4 Units. Students should discuss their course schedule with their dissertation advisers. This course provides an in-depth undergraduate-level introduction to fundamental ideas and tools of probability. 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. Weighs tradeoffs in how money is created, privileging some, under-privileging others, using market mechanisms for transforming and trading financial risk, return, maturity and asset types. Faculty program advisers and students meet regularly, and the faculty program adviser may initiate a meeting with any student deemed to be in academic or research distress. Elements of decision analysis; probabilistic risk analysis (fault trees, event trees, systems dynamics); economic analysis of failure consequences (human safety and long-term economic discounting); and case studies such as space systems, nuclear power plants, and medical systems. The basic limit theorems of probability theory and their application to maximum likelihood estimation. For further information, see http://scpd.stanford.edu/programs/graduate-certificates. Focuses on conceptual foundation and algorithmic methodology of Dynamic Programming and Stochastic Control with applications to engineering, operations research, management science and other fields. Prerequisites: algorithms at the level of 212 or CS 161, probability at the level of 221, and basic game theory, or consent of instructor. 3-4 Units. The program builds on the foundational courses for engineering including calculus, engineering fundamentals, and physics or chemistry as well as management science. The course will include both content and methods discussions, including theory-building from multiple cases. 3 Units. It should be noted that each student inherently has to pass the oral examination (see below) and submit their dissertation before their candidacy expires. 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. Restricted to MS&E MS students. Transparency or opacity can be the norm. Quantitative Finance Qualifying Procedure. Application deadlines: September 20, 2019 (for fall enrollment) and January 3, 2020 (for winter enrollment). Other courses in MS&E, Economics, Finance, Scientific Computing, or Statistics at the MS&E 300-level (or comparable in other departments) may be chosen after consulting with the dissertation adviser. 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). Theories: finite dimensional derivatives, convexity, optimality, duality, and sensitivity. Controlled diffusions. The program must include a minimum of 16 letter-graded units, and a minimum grade point average of 3.3 must be achieved in these courses. How to make optimal decisions in the presence of uncertainty, solution techniques for large-scale systems resulting from decision problems under uncertainty, and applications in finance. Same as: Accelerate. MATLAB. 3 Units. Introduction to Optimization Theory. Seminar on Organizational Theory. Current research on innovation strategy. MS&E 350. Develop mathematical tools to analyze the dynamic models, and use such tools to think about and manage the dynamics of change. The application of mathematical models to problems in health policy. The student must be enrolled in the quarter of their oral examination. 1-3 Unit. Bayesian meta-analysis. to apply knowledge of mathematics, social science, and engineering; to design a system and components to meet desired needs; to identify, formulate, and solve engineering problems; to use techniques, skills, and modern engineering tools necessary for engineering practice; to recognize the need for and demonstrate an ability to engage in life-long learning; to obtain the background necessary for admission to top graduate engineering or professional programs; to understand professional and ethical responsibility; to obtain the broad education necessary to understand the impact of engineering solutions in a global and societal context; and. Group projects involving financial market data. The focus is on data-driven modeling, computation, and statistical estimation of credit and market risks. Explores the relation between technology, war, and national security policy from early history to modern day, focusing on current U.S. national security challenges and the role that technology plays in shaping our understanding and response to these challenges. Topics include mortgage risk, asset-backed securities, commercial lending, consumer delinquencies, online lending, derivatives risk. They inform students and advisers about University and department requirements, procedures, opportunities, and maintain the official records of adviser assignments and course approvals. Focus is on the financial theory and empirical evidence that are useful for investment decisions. 1 Unit. 3 Units. Same as: SOC 278. Topics will include: the potential outcomes framework; randomization-based inference and covariate adjustment; matching, and IPW; instrumental variables, regression discontinuity and synthetic ncontrols. Prerequisite: 352. Theory of polyhedral convex sets, linear inequalities, alternative theorems, and duality. 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. Faculty in the focal area of the week comment on the student presentations. Enrollment limited. No prior knowledge of finance required. Big Financial Data and Algorithmic Trading. Amanda Brown. MS&E 372. Mechanism and Market Design. Stanford Engineering Magazine. The student can do both tutorials with the same faculty member; in this case a single written report is sufficient, and the presentation can be of the two tutorials together. AP/IB credit for Chemistry and Physics may be used if not used above. All first year students are required to attend and participate in MS&E 302 Fundamental Concepts in Management Science and Engineering, which meets in the Autumn Quarter. Discrete Probability Concepts And Models. in Management Science and Engineering or another quantitative major, and an M.S. Network protection services and resource placement. We aim to see the forest and the different species of trees growing in the forest known as the Buy-Side, so as to develop a perspective as financial engineers for how the ecosystem functions, what risks it digests, how it generates capital at what rate and amount for the Sell-Side, and how impacts in the real economy are reflected - or should be reflected - in the culture and risk models adopted by the Buy-Side participants. Relaxations of harder optimization problems and recent convex conic linear programs. © Stanford University, Stanford, California 94305. Foundation courses (may be waived based on prior coursework): Faculty-approved GSB OIT Ph.D. courses (about six are offered every two years). Same as: INTLPOL 256, MS&E 293. The degree program must be completed with a grade point average (GPA) of 3.0 or higher. We cover techniques for summarizing and describing data, methods for statistical inference, and principles for effectively communicating results. Same as: MS&E 212. Explores the ethical reasoning needed to make banking, insurance and financial services safer, fairer and more positively impactful. Completion of the undergraduate program in Management Science and Engineering leads to the conferral of the Bachelor of Science in Management Science and Engineering. 4 Units. 3-4 Units. Methods: simplex and interior-point, gradient, Newton, and barrier. Market Design and Resource Allocation in Non-Profit Settings. MS&E 278. Perspectives: problem formulation, analytical theory, computational methods, and recent applications in engineering, finance, and economics. Admission by application; details at first class. Simulation in a parallel environment. Applications to modeling, analysis and performance engineering of computing systems, communication networks, flexible manufacturing, and service systems. Sensitivity analyses, economic interpretations, and primal-dual methods. 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. Economic Analysis. Contemporary Themes in Work and Organization Studies. Open Faculty Positions. Uses a learning-by-doing approach covering the following topics: changing role of a PM at different stages of the product life cycle; techniques to understand customer needs and validate demand; user experience design and testing; role of detailed product specifications; waterfall and agile methods of software development. Future of Work: Issues in Organizational Learning and Design. We will also describe decision making problems that arise in modern applications, such as distributed systems like blockchains and Wikipedia, as well as applications of topical interest such as the assignment of children to schools, the design of congressional districts, and the direct involvement of communities in participatory budgeting. 3-4 Units. Flickr. MS&E 472. 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. Students may request a new adviser from MS&E Student Services staff as their interests clarify. All courses taken for the major must be taken for a letter grade. Prerequisites: basic mathematical maturity at the level of MATH 51, and probability at the level of MS&E 120 or EE 178. MS&E 249. Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering and of Computer Science. The qualifying exam consists of two written exams: one in Optimization and one in Stochastic Systems. Both the adviser and the advisee are expected to maintain professionalism and integrity. Prerequisites: basic concepts in linear algebra, probability theory, CS 106A or X. This course surveys the legal and ethical principles for assessing the equity of algorithms, describes statistical techniques for designing fair systems, and considers how anti-discrimination law and the design of algorithms may need to evolve to account for machine bias. For PhD students only. Admission by order of enrollment. 3 Units. Restricted to PhD students, or by consent of instructor. All required; see SoE Basic Requirements 1 and 2. Topics in Social Data. The team-based final focuses on developing a go-to-market strategy based on concepts from the course. Stanford Engineering Magazine. Advanced students will make presentations designed for first-year doctoral students regardless of area. MS&E 211. An increasing amount of data is now generated in a variety of disciplines, ranging from finance and economics, to the natural and social sciences. Attitudes toward ethical dilemmas through an explicit personal code. Not intended for MS&E majors. Introduction to Game Theory. 1-3 Unit. Investment Science. ALUMNI CONNECT. This course combines informal lecture and discussion with practical exercises to build specific skills for conducting field research in organizations. Autonomic self-defending networks. Many have become leaders in technology-based businesses which have an increasing need for analytically oriented people who understand both business and technology. candidate in MS&E is permitted to count toward the applicable degree under general departmental guidelines or under departmental rules that apply in the case of a particular student. ... LinkedIn. 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. Admission by application. The deadline for application to the doctoral program is December 3, 2019, and the deadline for application to the master's program is January 14, 2020. Does not explicitly cover social network structure or machine learning as these topics are well-covered elsewhere. In their first two years in the Ph.D. program, all students are expected to work with faculty on research. Three phases: risk assessment, communication, and management. 4 Units. Jiayu Mai | San Francisco, California | Consultant at Stanford Marketing | 70 connections | View Jiayu's homepage, profile, activity, articles

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