School of Engineering
Showing 1-50 of 52 Results
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Ching-Yao Lai
Assistant Professor of Geophysics
BioMy group attacks fundamental questions in ice-dynamics, geophysics, and fluid dynamics by integrating mathematical and machine-learned models with observational data. We use our findings to address challenges facing the world, such as advancing our scientific knowledge of ice dynamics under climate change. The length scale of the systems we are interested in varies broadly from a few microns to thousands of kilometers, because the governing physical principles are often universal across a range of length and time scales. We use mathematical models, simulations, and machine learning to study the complex interactions between fluids and elasticity and their interfacial dynamics, such as multiphase flows, flows in deformable structures, and cracks. We extend our findings to tackle emerging topics in climate science and geophysics, such as understand the missing physics that governs the flow of ice sheets in a warming climate. We welcome collaborations across disciplinary lines, from geophysics, engineering, physics, applied math to computer science, since we believe combining expertise and methodologies across fields is crucial for new discoveries.
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Sanjay Lall
Professor of Electrical Engineering
On Leave from 04/01/2024 To 06/30/2024BioSanjay Lall is Professor of Electrical Engineering in the Information Systems Laboratory and Professor of Aeronautics and Astronautics at Stanford University. He received a B.A. degree in Mathematics with first-class honors in 1990 and a Ph.D. degree in Engineering in 1995, both from the University of Cambridge, England. His research group focuses on algorithms for control, optimization, and machine learning. Before joining Stanford he was a Research Fellow at the California Institute of Technology in the Department of Control and Dynamical Systems, and prior to that he was a NATO Research Fellow at Massachusetts Institute of Technology, in the Laboratory for Information and Decision Systems. He was also a visiting scholar at Lund Institute of Technology in the Department of Automatic Control. He has significant industrial experience applying advanced algorithms to problems including satellite systems, advanced audio systems, Formula 1 racing, the America's cup, cloud services monitoring, and integrated circuit diagnostic systems, in addition to several startup companies. Professor Lall has served as Associate Editor for the journal Automatica, on the steering and program committees of several international conferences, and as a reviewer for the National Science Foundation, DARPA, and the Air Force Office of Scientific Research. He is the author of over 130 peer-refereed publications.
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Monica Lam
Kleiner Perkins, Mayfield, Sequoia Capital Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
BioDr. Monica Lam is a Professor in the Computer Science Department at Stanford University, and the Faculty Director of the Stanford Open Virtual Assistant Laboratory. Dr. Monica Lam obtained her BS degree in computer science from University of British Columbia, and her PhD degree in computer science from Carnegie Mellon University in 1987. She joined Stanford in 1988.
Professor Lam's current research is on conversational virtual assistants with an emphasis on privacy protection. Her research uses deep learning to map task-oriented natural language dialogues into formal semantics, represented by a new executable programming language called ThingTalk. Her Almond virtual assistant, trained on open knowledge graphs and IoT API standards, can be easily customized to perform new tasks. She is leading an Open Virtual Assistant Initiative to create the largest, open, crowdsourced language semantics model to promote open access in all languages. Her decentralized Almond virtual assistant that supports fine-grain sharing with privacy has received Popular Science's Best of What's New Award in Security in 2019.
Prof. Lam is also an expert in compilers for high-performance machines. Her pioneering work of affine partitioning provides a unifying theory to the field of loop transformations for parallelism and locality. Her software pipelining algorithm is used in commercial systems for instruction level parallelism. Her research team created the first, widely adopted research compiler, SUIF. She is a co-author of the classic compiler textbook, popularly known as the “dragon book”. She was on the founding team of Tensilica, now a part of Cadence.
Dr. Lam is a Member of the National Academy of Engineering and an Association of Computing Machinery (ACM) Fellow. -
James Landay
Denning Co-Director (Acting) of Stanford HAI, Anand Rajaraman and Venky Harinarayan Professor and Senior Fellow at the Stanford Institute for HAI
Current Research and Scholarly InterestsLanday's current research interests include Technology to Support Behavior Change (especially for health and sustainability), Demonstrational User Interfaces, Mobile & Ubiquitous Computing, Cross-Cultural Interface Design, Human-Centered AI, and User Interface Design Tools. He has developed tools, techniques, and a top professional book on Web Interface Design.
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Kincho Law
Professor of Civil and Environmental Engineering
BioProf. Law’s professional and research interests focus on the application of computational and information science in engineering. His work has dealt with various aspects of computational mechanics and structural dynamics, AI and machine learning, large scale database management, Internet and cloud computing, numerical methods and high performance computing. His research application areas include computer aided engineering, legal and engineering informatics, engineering enterprise integration, web services and supply chain management, monitoring and control of engineering systems, smart infrastructures, and smart manufacturing.
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James Leckie
C.L. Peck, Class of 1906 Professor in the School of Engineering, Emeritus
BioLeckie investigates chemical pollutant behavior in natural aquatic systems and engineered processes, specifically the environmental aspects of surface and colloid chemistry and the geochemistry of trace elements. New research efforts are focused on the development of techniques and models for assessment of exposure of humans to toxic chemicals. Specific attention has been paid to the evaluation of exposure of young children to toxic chemicals. Other interests include technology transfer and the development of environmental science programs in developing nations.
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Cynthia Bailey (Lee)
Senior Lecturer of Computer Science
Current Research and Scholarly InterestsI have a PhD in Computer Science from the University of California, San Diego, in the area of High-Performance Computing (HPC), specifically market-based scheduling algorithms. My graduate research was done as part of San Diego Supercomputer Center (SDSC)'s Performance Modeling and Characterization Lab (PMaC), where I investigated economic models of scheduling on high performance computing systems. My adviser was Allan Snavely of SDSC.
My dissertation abstract is as follows: Effective management of Grid and HPC resources is essential to maximizing return on the substantial infrastructure investment these resources entail. An important prerequisite to effective resource management is productive interaction between the user and scheduler. My work analyzes several aspects of the user-scheduler relationship and develops solutions to three of the most vexing barriers between the two. First, users' monetary valuation of compute time and schedule turnaround time is examined in terms of a utility function. Second, responsiveness of the scheduler to users' varied valuations is optimized via a genetic algorithm heuristic, creating a controlled market for computation. Finally, the chronic problem of inaccurate user runtime requests, and its implications for scheduler performance, is examined, along with mitigation techniques.
My current research projects are in the area of Computer Science Education, with an emphasis on assessment and the use of Peer Instruction pedagogy in lecture. With colleagues Mark Guzdial, Leo Porter, and Beth Simon, I run the New CS Faculty Teaching Workshop, an annual "bootcamp" on how to teach effectively that draws attendees from dozens of the top CS programs in the country. The short-term goal is to give newly-hired faculty entering their first year of teaching the skills they need to succeed for themselves and their students. The long-term goal is to transform undergraduate education in CS by seeding our best rising stars with best practices so they can create communities of practice as their institutions and mentor their students in active learning strategies, creating a culture where these are the new norm. -
Jin Hyung Lee
Associate Professor of Neurology (Neurology Research Faculty), of Neurosurgery and of Bioengineering and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsIn vivo visualization and control of neural circuits
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Nicolas Lee
Lecturer
BioNicolas Lee is currently a Research Engineer in Aeronautics and Astronautics at Stanford University, working primarily on asteroid resource characterization and CubeSat technologies. Previously, Nicolas was a Ph.D. student at Stanford studying meteoroid impact effects on spacecraft, and a W. M. Keck Institute for Space Studies postdoctoral scholar in aerospace at Caltech, researching technologies for robotically assembled space telecopes, membrane structures for space solar power applications, and small satellite high voltage electronics.
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Thomas Lee
Professor of Electrical Engineering
BioProfessor Lee's principal areas of professional interest include analog circuitry of all types, ranging from low-level DC instrumentation to high-speed RF communications systems. His present research focus is on CMOS RF integrated circuit design, and on extending operation into the terahertz realm.
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Larry John Leifer
Professor of Mechanical Engineering, Emeritus
Current Research and Scholarly InterestsOur "designXlab" at the Stanford Center for Design Research (CDR) has long (30+ years) been focused on Engineering Design Team dynamics at global collaboration scale working with corporate partners in my graduate course ME310ABC. In our most recent studies we have added Neuroscience visualization of brain activity using fMRI and fNIRS. In doing so we have launched "NeuroDesign" as a professional discipline.
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Sanjiva Lele
Edward C. Wells Professor of the School of Engineering and Professor of Mechanical Engineering
BioProfessor Lele's research combines numerical simulations with modeling to study fundamental unsteady flow phemonema, turbulence, flow instabilities, and flow-generated sound. Recent projects include shock-turbulent boundary layer interactions, supersonic jet noise, wind turbine aeroacoustics, wind farm modeling, aircraft contrails, multi-material mixing and multi-phase flows involving cavitation. He is also interested in developing high-fidelity computational methods for engineering applications.
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Michael Lepech
Professor of Civil and Environmental Engineering and Senior Fellow at the Woods Institute for the Environment
BioUnsustainable energy and material consumption, waste production, and emissions are some of today’s most pressing global concerns. To address these concerns, civil engineers are now designing facilities that, for example, passively generate power, reuse waste, and are carbon neutral. These designs are based foremost on longstanding engineering theory. Yet woven within this basic knowledge must be new science and new technologies, which advance the field of civil engineering to the forefront of sustainability-focused design.
My research develops fundamental engineering design concepts, models, and tools that are tightly integrated with quantitative sustainability assessment and service life modeling across length scales, from material scales to system scales, and throughout the early design, project engineering, construction, and operation life cycle phases of constructed facilities. My research follows the Sustainable Integrated Materials, Structures, Systems (SIMSS) framework. SIMSS is a tool to guide the multi-scale design of sustainable built environments, including multi-physics modeling informed by infrastructure sensing data and computational learning and feedback algorithms to support advanced digital-twinning of engineered systems. Thus, my research applies SIMMS through two complementary research thrusts; (1) developing high-fidelity quantitative sustainability assessment methods that enable civil engineers to quickly and probabilistically measure sustainability indicators, and (2) creating multi-scale, fundamental engineering tools that integrate with sustainability assessment and facilitate setting and meeting sustainability targets throughout the life cycle of constructed facilities.
Most recently, my research forms the foundation of the newly created Stanford Center at the Incheon Global Campus (SCIGC) in South Korea, a university-wide research center examining the potential for smart city technologies to enhance the sustainability of urban areas. Located in the smart city of Songdo, Incheon, South Korea, SCIGC is a unique global platform to (i) advance research on the multi-scale design, construction, and operation of sustainable built environments, (ii) demonstrate to cities worldwide the scalable opportunities for new urban technologies (e.g., dense urban sensing networks, dynamic traffic management, autonomous vehicles), and (iii) improve the sustainability and innovative capacity of increasingly smarter cities globally.
With an engineering background in civil and environmental engineering and material science (BSE, MSE, PhD), and business training in strategy and finance (MBA), I continue to explore to the intersection of entrepreneurship education, innovation capital training, and the potential of startups to more rapidly transfer and scale technologies to solve some of the world's most challenging problems. -
Jure Leskovec
Professor of Computer Science
BioJure Leskovec is Professor of Computer Science at Stanford University. He is affiliated with the Stanford AI Lab, Machine Learning Group and the Center for Research on Foundation Models. In the past, he served as a Chief Scientist at Pinterest and was an investigator at Chan Zuckerberg BioHub. Leskovec recently pioneered the field of Graph Neural Networks and co-authored PyG, the most widely-used graph neural network library. Research from his group has been used by many countries to fight COVID-19 pandemic, and has been incorporated into products at Facebook, Pinterest, Uber, YouTube, Amazon, and more.
His research received several awards including Microsoft Research Faculty Fellowship in 2011, Okawa Research award in 2012, Alfred P. Sloan Fellowship in 2012, Lagrange Prize in 2015, and ICDM Research Contributions Award in 2019. His research contributions have spanned social networks, data mining and machine learning, and computational biomedicine with the focus on drug discovery. His work has won 12 best paper awards and 5 10-year test of time awards at a premier venues in these research areas.
Leskovec received his bachelor's degree in computer science from University of Ljubljana, Slovenia, PhD in machine learning from Carnegie Mellon University and postdoctoral training at Cornell University. -
Marc Levenston
Associate Professor of Mechanical Engineering and, by courtesy, of Radiology (Radiological Sciences Laboratory)
Current Research and Scholarly InterestsMy lab's research involves the function, degeneration and repair of musculoskeletal soft tissues, with a focus on meniscal fibrocartilage and articular cartilage. We are particularly interested in the complex interactions between biophysical and biochemical cues in controlling cell behavior, the roles of these interactions in degenerative conditions such as osteoarthritis, and development of tissue engineered 3D model systems for studying physical influences on primary and progenitor cells.
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Craig Levin
Professor of Radiology (Molecular Imaging Program at Stanford/Nuclear Medicine) and, by courtesy, of Physics, of Electrical Engineering and of Bioengineering
Current Research and Scholarly InterestsMolecular Imaging Instrumentation
Laboratory
Our research interests involve the development of novel instrumentation and software algorithms for in vivo imaging of cellular and molecular signatures of disease in humans and small laboratory animal subjects. -
Philip Levis
Professor of Computer Science and of Electrical Engineering
BioProfessor Levis' research focuses on the design and implementation of efficient software systems for embedded wireless sensor networks; embedded network sensor architecture and design; systems programming and software engineering.
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Raymond Levitt
Kumagai Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsDr. Levitt founded and directs Stanford’s Global Projects Center (GPC), which conducts research, education and outreach to enhance financing, governance and sustainability of global building and infrastructure projects. Dr. Levitt's research focuses on developing enhanced governance of infrastructure projects procured via Public-Private Partnerships (PPP) delivery, and alternative project delivery approaches for complex buildings like full-service hospitals or data centers.
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Marc Levoy
VMware Founders Professor in Computer Science and Professor of Electrical Engineering, Emeritus
BioLevoy's current interests include the science and art of photography, computational photography, light field sensing and display, and applications of computer graphics in microscopy and biology.
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Adrian Lew
Professor of Mechanical Engineering
BioProf. Lew's interests lie in the broad area of computational solid mechanics. He is concerned with the fundamental design and mathematical analysis of material models and numerical algorithms.
Currently the group is focused on the design of algorithms to simulate hydraulic fracturing. To this end we work on algorithms for time-integration embedded or immersed boundary methods. -
Fei-Fei Li
Sequoia Capital Professor, Denning Co-Director (On Leave) of Stanford HAI, Senior Fellow at HAI and Professor, by courtesy, of Operations, Information and Technology at the Graduate School of Business
On Partial Leave from 01/01/2024 To 12/31/2025Current Research and Scholarly InterestsAI, Machine Learning, Computer Vision, Robotics, AI+Healthcare, Human Vision
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Zhiye Li
Research Engineer
BioDr. Li is a research engineer in Civil and Environmental Engineering at Stanford University in the field of data-driven innovation and multiscale modeling on climate-resilient and sustainable civil infrastructures. She is also a researcher at the John A. Blume Earthquake Engineering Center at Stanford University and the Stanford Center at the Incheon Global Campus (SCIGC). Her interdisciplinary research integrates multiphysics model, machine learning, life cycle assessment and material innovation to accelerate the global net-zero transition. Within civil engineering, her research focuses on developing new building materials and building practices for more sustainable built environments. She researched at Hopkins Extreme Materials Institute and completed her Ph.D. in Civil Engineering at Johns Hopkins University.
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Percy Liang
Associate Professor of Computer Science, Senior Fellow at the Stanford Institute for HAI, and Associate Professor, by courtesy, of Statistics
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011) and the director of the Center for Research on Foundation Models (CRFM). He is currently focused on making foundation models (in particular, language models) more accessible through open-source and understandable through rigorous benchmarking. In the past, he has worked on many topics centered on machine learning and natural language processing, including robustness, interpretability, human interaction, learning theory, grounding, semantics, and reasoning. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), a Microsoft Research Faculty Fellowship (2014), and paper awards at ACL, EMNLP, ICML, COLT, ISMIR, CHI, UIST, and RSS.
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Michael Lin
Associate Professor of Neurobiology, of Bioengineering and, by courtesy, of Chemical and Systems Biology
Current Research and Scholarly InterestsOur lab applies biochemical and engineering principles to the development of protein-based tools for investigating biology in living animals. Topics of investigation include fluorescent protein-based voltage indicators, synthetic light-controllable proteins, bioluminescent reporters, and applications to studying animal models of disease.
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Aaron Lindenberg
Professor of Materials Science and Engineering and of Photon Science
BioLindenberg's research is focused on visualizing the ultrafast dynamics and atomic-scale structure of materials on femtosecond and picosecond time-scales. X-ray and electron scattering and spectroscopic techniques are combined with ultrafast optical techniques to provide a new way of taking snapshots of materials in motion. Current research is focused on the dynamics of phase transitions, ultrafast properties of nanoscale materials, and charge transport, with a focus on materials for information storage technologies, energy-related materials, and nanoscale optoelectronic devices.
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Christian Linder
Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering
BioChristian Linder is a Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering. Through the development of novel and efficient in-house computational methods based on a sound mathematical foundation, the research goal of the Computational Mechanics of Materials (CM2) Lab at Stanford University, led by Dr. Linder, is to understand micromechanically originated multi-scale and multi-physics mechanisms in solid materials undergoing large deformations and fracture. Applications include sustainable energy storage materials, flexible electronics, and granular materials.
Dr. Linder received his Ph.D. in Civil and Environmental Engineering from UC Berkeley, an MA in Mathematics from UC Berkeley, an M.Sc. in Computational Mechanics from the University of Stuttgart, and a Dipl.-Ing. degree in Civil Engineering from TU Graz. Before joining Stanford in 2013 he was a Junior-Professor of Micromechanics of Materials at the Applied Mechanics Institute of Stuttgart University where he also obtained his Habilitation in Mechanics. Notable honors include a Fulbright scholarship, the 2013 Richard-von-Mises Prize, the 2016 ICCM International Computational Method Young Investigator Award, the 2016 NSF CAREER Award, and the 2019 Presidential Early Career Award for Scientists and Engineers (PECASE). -
Scott W Linderman
Assistant Professor of Statistics and, by courtesy, of Computer Science and of Electrical Engineering
BioScott is an Assistant Professor of Statistics and, by courtesy, Electrical Engineering and Computer Science at Stanford University. He is also an Institute Scholar in the Wu Tsai Neurosciences Institute and a member of Stanford Bio-X and the Stanford AI Lab. His lab works at the intersection of machine learning and computational neuroscience, developing statistical methods to analyze large scale neural data. Previously, Scott was a postdoctoral fellow with Liam Paninski and David Blei at Columbia University, and he completed his PhD in Computer Science at Harvard University with Ryan Adams and Leslie Valiant. He obtained his undergraduate degree in Electrical and Computer Engineering from Cornell University and spent three years as a software engineer at Microsoft before graduate school.
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C. Karen Liu
Professor of Computer Science
BioC. Karen Liu is a professor in the Computer Science Department at Stanford University. Prior to joining Stanford, Liu was a faculty member at the School of Interactive Computing at Georgia Tech. She received her Ph.D. degree in Computer Science from the University of Washington. Liu's research interests are in computer graphics and robotics, including physics-based animation, character animation, optimal control, reinforcement learning, and computational biomechanics. She developed computational approaches to modeling realistic and natural human movements, learning complex control policies for humanoids and assistive robots, and advancing fundamental numerical simulation and optimal control algorithms. The algorithms and software developed in her lab have fostered interdisciplinary collaboration with researchers in robotics, computer graphics, mechanical engineering, biomechanics, neuroscience, and biology. Liu received a National Science Foundation CAREER Award, an Alfred P. Sloan Fellowship, and was named Young Innovators Under 35 by Technology Review. In 2012, Liu received the ACM SIGGRAPH Significant New Researcher Award for her contribution in the field of computer graphics.
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Irene Lo
Assistant Professor of Management Science and Engineering
BioIrene is an assistant professor in Management Science & Engineering at Stanford University. Her research is on designing matching markets and assignment processes to improve market outcomes, with a focus on public sector applications and socially responsible operations research. She is also interested in mechanism design for social good and graph theory.
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Dr. Michael T. Longaker
Deane P. and Louise Mitchell Professor in the School of Medicine and Professor, by courtesy, of Materials Science and Engineering
Current Research and Scholarly InterestsWe have six main areas of current interest: 1) Cranial Suture Developmental Biology, 2) Distraction Osteogenesis, 3) Fibroblast heterogeneity and fibrosis repair, 4) Scarless Fetal Wound Healing, 5) Skeletal Stem Cells, 6) Novel Gene and Stem Cell Therapeutic Approaches.
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Amory B Lovins
Adjunct Professor
Current Role at StanfordAdjunct Professor of Civil and Environmental Engineering, Sept 2019 – June 2024. Expected to be retitled Lecturer in CEE thereafter, with the same responsibilities, because the definition changed and Lovins lacks a PhD. Visiting Scholar, Precourt Institute for Energy.
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David Luckham
Professor (Research) of Electrical Engineering, Emeritus
BioProfessor (Research) Emeritus of Electrical Engineering.
Research Professor of Electrical Engineering, Stanford University, 1977 to 2003.
Vinton Hayes Senior Research Fellow, Harvard University, 1976.
Senior Research Associate, Stanford Artificial Intelligence Laboratory, 1972-1977.
Associate Professor, UCLA Computer Science Department, 1970-1972.
Professor Luckham's research and consulting activities in software technology include multi-processing and business processing languages, event-driven systems, complex event processing, commercial middleware, program verification, systems architecture modelling and simulation, and artificial intelligence (automated deduction and reasoning systems).
Prof. Luckham has held faculty and invited faculty positions in both mathematics and computer science at eight major universities in Europe and the United States. He has been an invited lecturer, keynote speaker, panelist, and USA delegate at many international conferences and congresses. Until 1999 he was a member of the Computer Systems Laboratory, Stanford University and directed the Program Analysis and Verification Project. He taught courses on Artifical Intelligence and automated deduction, programming languages and program verification, the Anna verification system, systems prototyping and simulation languages, and Complex Event Processing. He was one of the founders of Rational Software, Inc. in 1981.
In the past he has served on review committees during the DoD Ada Language design competition, and was a Distinguished Reviewer on the DoD Ada9X design project. In 1993-94 he was a member of the TRW Independent Assessment Team tasked with reviewing the FAA's Advanced Automation System for the FAA, and in 1994-96 he was a distinguished reviewer for the DoD High Level Language for modelling and simulation. He has published four books and over 100 technical papers; two ACM/IEEE Best Paper Awards, several papers are now in historical anthologies and book collections. His 2002 book is a benchmark introduction to complex event processing, "The Power of Events" . His 2012 book , "Event Processing for Business" documents current applications of Complex Event Processing in many areas of Information Technology. -
David Luenberger
Professor of Management Science and Engineering, Emeritus
BioDavid G. Luenberger received the B.S. degree from the California Institute of Technology and the M.S. and Ph.D. degrees from Stanford University, all in Electrical Engineering. Since 1963 he has been on the faculty of Stanford University. He helped found the Department of Engineering-Economic Systems, now merged to become the Department of Management Science and Engineering, where his is currently a professor.
He served as Technical Assistant to the President's Science Advisor in 1971-72, was Guest Professor at the Technical University of Denmark (1986), Visiting Professor of the Massachusetts Institute of Technology (1976), and served as Department Chairman at Stanford (1980-1991).
His awards include: Member of the National Academy of Engineering (2008), the Bode Lecture Prize of the Control Systems Society (1990), the Oldenburger Medal of the American Society of Mechanical Engineers (1995), and the Expository Writing Award of the Institute of Operations Research and Management Science (1999) He is a Fellow of the Institute of Electrical and Electronic Engineers (since 1975).
Interests:
His overall interest is the application of mathematics to issues in control, planning, and decision making. He has worked in the technical fields of control theory, optimization theory and algorithms, and investment theory for portfolios and project evaluation. He has published six major textbooks: Optimization by Vector Space Methods, Linear and Nonlinear Programming (jointly with Yinyu Ye), Introduction to Dynamic Systems, Microeconomic theory, Investment Science, and Information Science. He has published over eighty journal papers.
