School of Engineering
Showing 181-200 of 522 Results
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Donald Iglehart
Professor of Engineering-Economic Systems & Operations Research, Emeritus
BioDonald L. Iglehart is a John von Neumann Theory Prize recipient who has made fundamental contributions to performance analysis, optimization, and simulation of stochastic systems. Iglehart received his Bachelor’s degree in Engineering Physics from Cornell in 1956, his Master’s degree in Mathematical Statistics from Stanford University in 1959, and his PhD in the same subject from Stanford in 1961. His dissertation was supervised by Herbert E. Scarf and Samuel Karlin, and the topic was on dynamic programming and stationary analysis of inventory problems. He taught at Cornell University from 1961 to 1967 and came to Stanford in 1967, where he has been emeritus since 1999. In1976, he spent a very productive year as an Overseas Fellow at Churchill College at Cambridge University. In his capacity as a PhD advisor, he has had many notable students, including Peter Glynn, Peter Haas, Phil Heidelberger, Doug Kennedy, and Ward Whitt.
Iglehart was jointly awarded the John von Neumann Theory Prize in 2002 with Cyrus Derman, the same year he was named an inaugural Fellow of the Institute for Operations Research and the Management Sciences. He was recognized for having pioneered and developed diffusion limits and approximations for heavily congested stochastic systems. His ideas provided tractable limiting processes and readily computable approximations for complex queueing and other stochastic systems for which closed-form solutions have proved intractable. Iglehart’s original research and contributions have heavily influenced queueing theory in the years since their publication, and his papers have been cited in hundreds of publications. Some of his other work has focused on inventory and distribution problems.
Iglehart was also honored by the INFORMS Simulation Society in 2012 with its highest honor, the Lifetime Professional Achievement Award (LPAA). His foundational work in that field recognized and exploited the underlying stochastic structure of simulation as a means of producing enhanced simulation methodologies. For example, he introduced and led the development of the regenerative method for stochastic simulation output analysis, inspiring a flood of significant contributions to simulation methodology. In the late 1980s, Iglehart and Glynn incorporated such techniques as importance sampling into stochastic simulations. The LPAA also noted his ability to clearly organize and articulate deep theory in his presentations and writing, and recognized his education of Ph.D. students who have had, individually and cumulatively, a profound impact on simulation education and research. The citation for his award states that "It is no exaggeration to say that Don Iglehart’s contributions made simulation a respectable research discipline in some circles of the operations research community."
In addition to being an INFORMS Fellow, Iglehart was elected in 1999 to the National Academy of Engineering, having been selected for his contributions to queueing theory, simulation methodology, inventory control, and diffusion approximations. He was also honored in 1971 through his induction as a Fellow of the Institute of Mathematical Statistics.
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Historical Academic Appointments:
1961-67 School of Operations Research and Industrial Engineering, Cornell University
1967-96 Department of Operations Research, Stanford University
1996-99 Department of Engineering-Economic Systems and Operations Research, Stanford University -
Ruizhe Jia
Assistant Professor of Management Science and Engineering
BioI am an Assistant Professor in the Department of Management Science & Engineering at Stanford University. I earned my Ph.D. in Operations Research at Columbia University, advised by Prof. Agostino Capponi, and completed my B.S. and M.A. in Mathematics at UCLA.
My research sits at the intersection of financial technology, market microstructure, and mechanism design. I study how financial markets function and how they can be redesigned for greater efficiency and fairness, with a particular focus on decentralized finance (DeFi) and blockchain-based trading. My work spans three areas:
Market microstructure — analyzing trading behavior and designing better financial markets.
FinTech and DeFi — examining how cryptographic tools and decentralized protocols reshape financial transactions.
Incentives in financial technology — addressing misalignments that emerge in crypto-finance and proposing mechanisms that improve adoption and efficiency.
I believe finance is a social science that benefits from active engagement with real markets. I work closely with both industry and regulators to ensure my research not only advances theory but also informs practice and policy in digital assets and financial technology. -
Ramesh Johari
Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering
BioJohari is broadly interested in the design, economic analysis, and operation of online platforms, as well as statistical and machine learning techniques used by these platforms (such as search, recommendation, matching, and pricing algorithms).
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Prof Theresa Johnson
Affiliate, Management Science and Engineering
BioDr. Johnson is a seasoned product leader with deep technical roots and a rare track record of impact across startups, academia, and top-tier tech companies. She currently serves as Head of Product for the Roblox Operating System, where she shapes the product vision for the employee lifecycle for employees at one of the world’s most immersive virtual platforms.
Before that, she led Payments Data Products at Airbnb, tackling complex infrastructure challenges at scale with a focus on user trust, access, and seamless global transactions.
Her career is built on a strong technical foundation—she earned a PhD in Aeronautics and Astronautics from Stanford, becoming the second Black woman in history to do so. That mix of deep systems thinking, experimentation, and executional rigor shows up in everything from launching infrastructure and AI-enabled products, to leading cross-functional teams, to mentoring students and early-career PMs. As Lecturing Professor at Stanford for Introduction to Product Management in the School of Engineering, she's passionate about building inclusive, high-performing teams and designing products that don’t just hit metrics, but matter.
Prof. Theresa Johnson has a BS in Science, Technology and Society and an MS and PhD in Aeronautics and Astronautics from Stanford University. She’s been published in the fields of robotics, machine learning and plasma physics. Theresa lives in Bernal Heights, San Francisco with her husband, two daughters and her rescued catahoula hound, Amelie.
