Stanford University
Showing 201-250 of 362 Results
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Todd Martinez
David Mulvane Ehrsam and Edward Curtis Franklin Professor of Chemistry and Professor of Photon Science
Current Research and Scholarly InterestsAb initio molecular dynamics, photochemistry, molecular design, mechanochemistry, graphical processing unit acceleration of electronic structure and molecular dynamics, automated reaction discovery, ultrafast (femtosecond and attosecond) chemical phenomena
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Michaëlle Ntala Mayalu
Assistant Professor of Mechanical Engineering and, by courtesy, of Bioengineering
BioDr. Michaëlle N. Mayalu is an Assistant Professor of Mechanical Engineering. She received her Ph.D., M.S., and B.S., degrees in Mechanical Engineering at the Massachusetts Institute of Technology. She was a postdoctoral scholar at the California Institute of Technology in the Computing and Mathematical Sciences Department. She was a 2017 California Alliance Postdoctoral Fellowship Program recipient and a 2019 Burroughs Wellcome Fund Postdoctoral Enrichment Program award recipient. She is also a 2023 Hypothesis Fund Grantee.
Dr. Michaëlle N. Mayalu's area of expertise is in mathematical modeling and control theory of synthetic biological and biomedical systems. She is interested in the development of control theoretic tools for understanding, controlling, and predicting biological function at the molecular, cellular, and organismal levels to optimize therapeutic intervention.
She is the director of the Mayalu Lab whose research objective is to investigate how to optimize biomedical therapeutic designs using theoretical and computational approaches coupled with experiments. Initial project concepts include: i) theoretical and experimental design of bacterial "microrobots" for preemptive and targeted therapeutic intervention, ii) system-level multi-scale modeling of gut associated skin disorders for virtual evaluation and optimization of therapy, iii) theoretical and experimental design of "microrobotic" swarms of engineered bacteria with sophisticated centralized and decentralized control schemes to explore possible mechanisms of pattern formation. The experimental projects in the Mayalu Lab utilize established techniques borrowed from the field of synthetic biology to develop synthetic genetic circuits in E. coli to make bacterial "microrobots". Ultimately the Mayalu Lab aims to develop accurate and efficient modeling frameworks that incorporate computation, dynamical systems, and control theory that will become more widespread and impactful in the design of electro-mechanical and biological therapeutic machines. -
Paul McIntyre
Rick and Melinda Reed Professor, Professor of Photon Science and Senior Fellow at the Precourt Institute for Energy
BioMcIntyre's group performs research on nanostructured inorganic materials for applications in electronics, energy technologies and sensors. He is best known for his work on metal oxide/semiconductor interfaces, ultrathin dielectrics, defects in complex metal oxide thin films, and nanostructured Si-Ge single crystals. His research team synthesizes materials, characterizes their structures and compositions with a variety of advanced microscopies and spectroscopies, studies the passivation of their interfaces, and measures functional properties of devices.
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Azalia Mirhoseini
Assistant Professor of Computer Science
BioAzalia Mirhoseini is an Assistant Professor in the Computer Science Department at Stanford University. Professor Mirhoseini's research interest is in developing capable, reliable, and efficient AI systems for solving high-impact, real-world problems. Her work includes generalized learning-based methods for decision-making problems in systems and chip design, self-improving AI models through interactions with the world, and scalable deep learning optimization. Prior to Stanford, she spent several years in industry AI labs, including Anthropic and Google Brain. At Anthropic, she worked on advancing the capabilities and reliability of large language models. At Google Brain, she co-founded the ML for Systems team, with a focus on automating and optimizing computer systems and chip design. She received her BSc degree in Electrical Engineering from Sharif University of Technology and her PhD in Electrical and Computer Engineering from Rice University. Her work has been recognized through the MIT Technology Review’s 35 Under 35 Award, the Best ECE Thesis Award at Rice University, publications in flagship venues such as Nature, and coverage by various media outlets, including MIT Technology Review, IEEE Spectrum, The Verge, The Times, ZDNet, VentureBeat, and WIRED.
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Subhasish Mitra
William E. Ayer Professor of Electrical Engineering and Professor of Computer Science
BioSubhasish Mitra holds the William E. Ayer Endowed Chair Professorship in the Departments of Electrical Engineering and Computer Science at Stanford University. He directs the Stanford Robust Systems Group, serves on the leadership team of the Microelectronics Commons AI Hardware Hub, leads the Computation Focus Area of the Stanford SystemX Alliance, and is the Associate Chair (Faculty Affairs) of Stanford Computer Science. His research ranges across Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences. Results from his research group have influenced almost every contemporary electronic system and have inspired significant government and research initiatives in multiple countries. He has held several international academic appointments — the Carnot Chair of Excellence in NanoSystems at CEA-LETI in France, and Invited Professor at ETH and EPFL in Switzerland and University of Tokyo in Japan. Prof. Mitra also has consulted for major technology companies including AMD (XIlinx), Anthropic, Cisco, Google, Intel, Samsung, and Sony. He recently cofounded TenX Semi, a startup on AI autopilot for chip design.
In the field of Robust Computing, he has created many key approaches for circuit failure prediction, CASP on-line diagnostics, QED system validation, soft error resilience, and X-Compact test compression. Their adoption by industry is growing rapidly, in markets ranging from cloud computing to automotive systems, under various names such as Silicon Lifecycle Management, Predictive Health Monitoring, In-System Test, In-field Scan, In-fleet Scan. His X-Compact approach has proven essential to cost-effective manufacturing and high-quality testing of almost all contemporary digital systems. X-Compact and its derivatives enabled billions of dollars of cost savings across the industry.
In the field of NanoSystems, with his students and collaborators, he demonstrated several firsts: the first NanoSystems hardware among all beyond-silicon nanotechnologies for energy-efficient computing (the carbon nanotube computer), the first 3D NanoSystem with computation immersed in data storage, the first published end-to-end computing systems using resistive memories (Resistive RAM-based non-volatile computing systems delivering 10-fold energy efficiency versus embedded flash), and the first monolithic 3D integration combining heterogeneous logic and memory technologies in silicon foundry. These received wide recognition: cover of NATURE, several Highlights to the US Congress, and highlight as "important scientific breakthrough" by news organizations worldwide.
Prof. Mitra's honors include the Harry H. Goode Memorial Award (by IEEE Computer Society for outstanding contributions in the information processing field), Newton Technical Impact Award in EDA (test-of-time honor by ACM SIGDA and IEEE CEDA), the University Researcher Award (by Semiconductor Industry Association and Semiconductor Research Corporation to recognize lifetime research contributions), the EDAA Achievement Award (by European Design and Automation Association, for outstanding lifetime contributions to electronic design, automation and testing), the Intel Achievement Award (Intel’s highest honor), and the Distinguished Alumnus Award from the Indian Institute of Technology, Kharagpur. He and his students have published over 15 award-winning papers across 5 topic areas (technology, circuits, EDA, test, verification) at major venues including the Design Automation Conference, International Electron Devices Meeting, International Solid-State Circuits Conference, International Test Conference, Symposia on VLSI Technology/VLSI Circuits, and Formal Methods in Computer-Aided Design. Stanford undergraduates have honored him several times "for being important to them." He is a Fellow of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), and a Foreign Member of Academia Europaea. -
Ariam Mogos
Lecturer
BioAriam Mogos leads emerging technology initiatives at Stanford's Hasso Plattner Institute of Design (d.school), where she helps students and educators work with emerging technologies like AI and blockchain, and shapes conversations around the tech’s ethical implications on humans and nature. Her design work and research also investigates the ways that technology can foster playful learning experiences that bridge communities and cultures.
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Parviz Moin
Franklin P. and Caroline M. Johnson Professor in the School of Engineering
BioMoin is the founding director of the Center for Turbulence Research. Established in 1987 as a research consortium between NASA and Stanford, Center for Turbulence Research is devoted to fundamental studies of turbulent flows. Center of Turbulence Research is widely recognized as the international focal point for turbulence research, attracting diverse groups of researchers from engineering, mathematics and physics. He was the founding director of the Institute for Computational and Mathematical Engineering at Stanford.
Professor Moin pioneered the use of direct and Large Eddy Simulation techniques for the study of turbulence physics, control and modelling concepts and has written widely on the structure of turbulent shear flows. His current interests include: Computational physics, Physics and control of turbulent boundary layers, hypersonic flows, propulsion, flow control, large eddy simulation for aerospace applications and aircraft icing. -
Pedram Mokrian
Lecturer
Instructor, Stanford Engineering Center for Global and Online EducationBioPedram Mokrian is Adjunct Professor at Stanford University and a lecturer at the Haas School of business at UC Berkeley where he teaches and advises entrepreneurs and global 1000 companies alike on entrepreneurship, business model disruption, and technology innovation strategy. He was previously a Principal at Mayfield, one of Silicon Valley’s most storied venture capital firms, where he was part of the investment team with over $3.5B assets under management. Mokrian is a founding Partner of the Ratio Academy, New Line Ventures. He also serves as a mentor or advisor to a number of start-ups, innovation incubators, including Global Innovation Catalyst, the Texas Medical Center Innovation Center, Innovation Labs, MISO, and Moog, and serves on the advisory board of Phillips66.
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Louie Montoya
Lecturer
BioA self-proclaimed deeper learning education nerd, Louie Montoya joined the d.school in 2018 to work with educators on learning and implementing design in the classroom. Today he leads the Deeper Learning Puzzle Bus, a K12 lab mobile experiment designed to look at how “escape rooms” can change the way educators think about measurement and assessment, as well as bring more delight into the classroom.
A first generation Mexican American raised across the western hemisphere, Louie developed an interest in other cultures that anchors his work on behalf of equitable practices in the design process. As an experience designer at the Business Innovation Factory in Rhode Island, Louie co-designed and ran the Teachers for Equity Fellowship that worked with educators across the United States to address issues of racial inequity in their schools and classrooms. As a member of the Deeper Learning network Louie focuses on building capacity around skills such as collaboration, communication and critical thinking with students. -
Walter Murray
Professor (Research) of Management Science and Engineering, Emeritus
BioProfessor Murray's research interests include numerical optimization, numerical linear algebra, sparse matrix methods, optimization software and applications of optimization. He has authored two books (Practical Optimization and Optimization and Numerical Linear Algebra) and over eighty papers. In addition to his University work he has extensive consulting experience with industry, government, and commerce.
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Sanjiv Narayan
Professor of Medicine (Cardiovascular Medicine)
Current Research and Scholarly InterestsDr. Narayan directs the Computational Arrhythmia Research Laboratory, whose goal is to define the mechanisms underlying complex human heart rhythm disorders, to develop bioengineering-focused solutions to improve therapy that will be tested in clinical trials. The laboratory has been funded continuously since 2001 by the National Institutes of Health, AHA and ACC, and interlinks a disease-focused group of clinicians, computational physicists, bioengineers and trialists.
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Brett Newman
Lecturer
BioAcademic
2013 - 2018 : Stanford : Lecturer : Visual Thinking, ME115C: Design and Business Factors
2018 - Present : Stanford : Lead Lecturer : Design 161 Capstone
Professional
2004 - 2007 : Azud : VP Product
2007 - Present : Daylight Design : Partner -
Simona Onori
Associate Professor of Energy Science Engineering and Senior Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsModeling, control and optimization of dynamic systems;
Model-based control in advanced propulsion systems;
Energy management control and optimization in HEVs and PHEVs;
Energy storage systems- Li-ion and PbA batteries, Supercapacitors;
Battery aging modeling, state of health estimation and life prediction for control;
Damage degradation modeling in interconnected systems -
Brad Osgood
Professor of Electrical Engineering and, by courtesy, in Education
BioOsgood is a mathematician by training and applies techniques from analysis and geometry to various engineering problems. He is interested in problems in imaging, pattern recognition, and signal processing.
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Julia Palacios
Associate Professor of Statistics and of Biomedical Data Science
BioDr. Palacios’s research spans Bayesian nonparametrics, probabilistic AI, stochastic processes, and computational statistics. Her group develops stochastic models and efficient inference algorithms for understanding evolutionary dynamics in population genetics, infectious diseases and cancer.
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Arogyaswami Paulraj
Professor (Research) of Electrical Engineering, Emeritus
BioProf. Arogyaswami Paulraj is an Emeritus Professor at Stanford University. Paulraj's legacy is deeply intertwined with the evolution of wireless communication. His groundbreaking work on MIMO (multiple input, multiple output) technology laid the foundation for today's ubiquitous 4G/5G networks and high-speed Wi-Fi.
Paulraj's journey began in the Indian Navy, where he served from 1965 to 1991. During this time, he led the development of the APSOH anti-submarine sonar system and established three key R&D labs for the Indian government. His contributions earned him the prestigious Padma Bhushan award, India's third highest civilian honor.
Following his naval career, Paulraj joined Stanford University as a postdoctoral researcher. His research focus shifted to wireless communication, where he made groundbreaking contributions to MIMO technology. MIMO enables data transmission using multiple antennas, significantly increasing network capacity and data rates.
Paulraj's innovation has been recognized with numerous accolades, including the 2024 Royal Acad. Eng. Prince Philip Medal, the 2023 IET Faraday Medal, the 2014 Marconi Prize, and the 2011 IEEE Alexander Graham Bell Medal. He is also a fellow of nine national academies in engineering, sciences, and the arts, and an inductee of the US Patent Office’s National Inventors Hall of Fame.
Currently, Paulraj continues to contribute to technological advancement. He chairs several committees for the Government of India, focusing on the Indian Semiconductor Mission and Core ICT initiatives. His dedication to research and development continues to shape the future of wireless communication. -
Marco Pavone
Associate Professor of Aeronautics and Astronautics, Senior Fellow at the Precourt Institute for Energy and Associate Professor, by courtesy, of Electrical Engineering & of Computer Science
BioDr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University, where he directs the Autonomous Systems Laboratory and the Center for Automotive Research at Stanford. He is also a Distinguished Research Scientist at NVIDIA where he leads autonomous vehicle research. Before joining Stanford, he was a Research Technologist within the Robotics Section at the NASA Jet Propulsion Laboratory. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He is a recipient of a number of awards, including a Presidential Early Career Award for Scientists and Engineers from President Barack Obama, an Office of Naval Research Young Investigator Award, a National Science Foundation Early Career (CAREER) Award, a NASA Early Career Faculty Award, and an Early-Career Spotlight Award from the Robotics Science and Systems Foundation. He was identified by the American Society for Engineering Education (ASEE) as one of America's 20 most highly promising investigators under the age of 40. His work has been recognized with best paper nominations or awards at a number of venues, including the European Conference on Computer Vision, the IEEE International Conference on Robotics and Automation, the European Control Conference, the IEEE International Conference on Intelligent Transportation Systems, the Field and Service Robotics Conference, the Robotics: Science and Systems Conference, and the INFORMS Annual Meeting.
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Markus Pelger
Associate Professor of Management Science and Engineering
Current Research and Scholarly InterestsHis research focuses on understanding and managing financial risk. He develops mathematical financial models and statistical methods, analyzes financial data and engineers computational techniques. His research is divided into three streams: machine learning solutions to big-data problems in empirical asset pricing, statistical theory for high-dimensional data and stochastic financial modeling.
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Mert Pilanci
Assistant Professor of Electrical Engineering
Current Research and Scholarly InterestsDr. Pilanci's research interests include neural networks, machine learning, mathematical optimization, information theory and signal processing.
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Peter Pinsky
Professor of Mechanical Engineering, Emeritus
BioPinsky works in the theory and practice of computational mechanics with a particular interest in multiphysics problems in biomechanics. His work uses the close coupling of techniques for molecular, statistical and continuum mechanics with biology, chemistry and clinical science. Areas of current interest include the mechanics of human vision (ocular mechanics) and the mechanics of hearing. Topics in the mechanics of vision include the mechanics of transparency, which investigates the mechanisms by which corneal tissue self-organizes at the molecular scale using collagen-proteoglycan-ion interactions to explain the mechanical resilience and almost perfect transparency of the tissue and to provide a theoretical framework for engineered corneal tissue replacement. At the macroscopic scale, advanced imaging data is used to create detailed models of the 3-D organization of collagen fibrils and the results used to predict outcomes of clinical techniques for improving vision as well as how diseased tissue mechanically degrades. Theories for mass transport and reaction are being developed to model metabolic processes and swelling in tissue. Current topics in the hearing research arena include multiscale modeling of hair-cell mechanics in the inner ear including physical mechanisms for the activation of mechanically-gated ion channels. Supporting research addresses the mechanics of lipid bilayer cell membranes and their interaction with the cytoskeleton. Recent past research topics include computational acoustics for exterior, multifrequency and inverse problems; and multiscale modeling of transdermal drug delivery. Professor Pinsky currently serves as Chair of the Mechanics and Computation Group within the Department of Mechanical Engineering at Stanford.
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Eric Pop
Pease-Ye Professor, Professor of Electrical Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Materials Science and Engineering and of Applied Physics
Current Research and Scholarly InterestsThe Pop Lab explores problems at the intersection of nanoelectronics and nanoscale energy conversion. These include fundamental limits of current and heat flow, energy-efficient transistors and memory, and energy harvesting via thermoelectrics. The Pop Lab also works with novel nanomaterials like carbon nanotubes, graphene, BN, MoS2, and their device applications, through an approach that is experimental, computational and highly collaborative.
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Robert Prakash
Chief Technology Officer & Chief Operating Officer, Stanford Engineering Center for Global and Online Education
Current Role at StanfordChief Technology Officer & Chief Operating Officer, Stanford Engineering | Center for Global & Online Education
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Adrienne Propp
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2021
BioI am a fourth year PhD student in ICME (the Institute for Computational and Mathematical Engineering). Prior to Stanford, I was working as a technical analyst at the RAND Corporation where I spent most of my time designing microsimulations and other models to investigate topics in healthcare, education, disaster relief, and international relations.
My research interests lie at the intersection of mathematics, data, and modeling, which has led me to a focus on scientific machine learning (SciML). Specifically, I am working on developing new graph-based surrogate modeling methods for low-data regimes. I am grateful to be advised by Daniel Tartakovsky, During my PhD, I have also collaborated with Jenny Suckale to model volcanic lava fountaining, and Susan Athey and Sanath Kumar Krishnamurthy to design improved algorithms for contextual bandits.
Past research projects have ranged from computational models of the heart to inverse modeling to predict satellite performance. -
Jian Qin
Associate Professor of Chemical Engineering
BioJian Qin is an Associate Professor in the Department of Chemical Engineering at the Stanford University. His research focuses on development of microscopic understanding of structural and physical properties of soft matters by using a combination of analytical theory, scaling argument, numerical computation, and molecular simulation. He worked as a postdoctoral scholar with Juan de Pablo in the Institute for Molecular Engineering at the University of Chicago and with Scott Milner in the Department of Chemical Engineering at the Pennsylvania State University. He received his Ph.D. in the Department of Chemical Engineering and Materials Science at the University of Minnesota under the supervision of David Morse and Frank Bates. His research covers self-assembly of multi-component polymeric systems, molecular origin of entanglement and polymer melt rheology, coacervation of polyelectrolytes, Coulomb interactions in dielectrically heterogeneous electrolytes, and surface charge polarizations in particulate aggregates in the absence or presence of flow.
