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Research Areas

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Research in MS&E spans a broad intellectual spectrum, and our work often involves cross-disciplinary integrations across areas of the department and Stanford as a whole.

MS&E faculty work within and across these research areas:

Computational Social Science
Decision and Risk Analysis
Operations Research
Organizations, Technology and Entrepreneurship
Policy and Strategy
Quantitative Finance


Computational Social Science

The design and operation of networks requires technical concepts such as information theory, algorithms, and optimization, but also depends on economic, social, and even political factors.

One example is the concept of net neutrality, in which infrastructure providers seeking to recoup their investments by charging differently based on bandwidth consumption come into conflict with users who oppose making economic distinctions related to information content. The department has deep expertise in all facets of these and other problems of technology implementation and usage in the real world.


Decision and Risk Analysis

MS&E Professor Ron Howard pioneered the field of decision analysis starting in 1964. And MS&E continues to lead in the field today.

Although many people make personal decisions instinctively and haphazardly, a more serious approach essential for management is to analyze the problem as a three-legged structure of preferences, alternatives, and available information in the context of a frame.


Operations Research

Research focuses on developing and applying analytical, computational, and economic tools to address a wide variety of problems in business, government, and society.

The area is characterized by its mathematical depth, broad applicability, and interdisciplinary nature and has a particular emphasis in developing and applying models and algorithms to gain new insights and make better decisions across multiple domains.

Operations research is distinguished by its combination of foundational methodological research with applications and translation to practice.  The methodological foundations of operations research include: linear and nonlinear optimization; applied probability and stochastic modeling; simulation; statistical methodology; algorithms; dynamic programming and reinforcement learning; and game theory, market design, and microeconomic theory.  Research in this area often combines ideas across these methodological foundations to develop new techniques that are matched to emerging needs driven by applications; for example, many modern advances in machine learning are driven by advances at the interface of optimization, algorithms, and stochastic analysis, and a rich frontier in market design involves the interface of computational and economic theories.

In turn, these methodological foundations have significant impact on practice.  Faculty in operations research have consistently contributed to both methodological innovation, and instantiation of those methodological innovations in applied domains.  Interaction with applications further inspires novel frontiers for methodological research.  Significant areas of application include: school choice; design of kidney exchanges; design of pricing and matching algorithms for online platforms; operations management for health care; computational methods for social choice and collective decision-making; analysis and control of epidemics; and energy efficient management of buildings.


Organizations, Technology and Entrepreneurship

Research spans the study of technical work, technology's effects on individuals and teams, the formation and growth of entrepreneurial firms, and strategy and innovation in technology-based firms.

Some projects examine the role of technology in the work of engineers, including the interplay between workplace technologies and engineering knowledge, on-the-job learning, problem-solving, and coordination. Other research investigates the dynamics of globally distributed work teams, the implications of contracting and outsourcing, human-robot interaction in the workplace, and evidence-based management.

At the firm-level, research examines how entrepreneurial firms gain financing, build alliance networks, and grow. Other investigations center on established firms, including creating successful R&D collaborations across businesses, effectively competing against other firms, and entering new markets. Researchers also study strategies that enable established organizations to discover, develop, and commercialize technologies.


Policy and Strategy

Research and teaching in this area focus on the design and analysis of public policies and corporate strategies, especially those with technology-based issues.  Sub-areas include Energy and Environment, Health Systems Modeling and Policy, and National Security Policy

It features a grounding in microeconomics and modeling approaches. Courses with a policy focus include such topics such as national security, energy and environment, and health care. Courses with a strategy focus cover topics such as entrepreneurship, innovation, and product development.


Quantitative Finance

Research and teaching in the department cover a range of topics including investments, economic growth, natural resources and energy, entrepreneurship, and microeconomics.

Through systematic analysis and application of sophisticated mathematical tools, engineers make vital contributions to understanding commodities, credit, currencies, derivatives, equities, pricing, profits, resources, and other core economic and financial concepts.