School of Engineering

Showing 51-100 of 136 Results

  • Thomas Kenny

    Thomas Kenny

    Senior Associate Dean for Education and Student Affairs and Richard W. Weiland Professor in the School of Engineering

    BioKenny's group is researching fundamental issues and applications of micromechanical structures. These devices are usually fabricated from silicon wafers using integrated circuit fabrication tools. Using these techniques, the group builds sensitive accelerometers, infrared detectors, and force-sensing cantilevers. This research has many applications, including integrated packaging, inertial navigation, fundamental force measurements, experiments on bio-molecules, device cooling, bio-analytical instruments, and small robots. Because this research field is multidisciplinary in nature, work in this group is characterized by strong collaborations with other departments, as well as with local industry.

  • Oussama Khatib

    Oussama Khatib

    Weichai Professor and Professor, by courtesy, of Electrical Engineering

    BioRobotics research on novel control architectures, algorithms, sensing, and human-friendly designs for advanced capabilities in complex environments. With a focus on enabling robots to interact cooperatively and safely with humans and the physical world, these studies bring understanding of human movements for therapy, athletic training, and performance enhancement. Our work on understanding human cognitive task representation and physical skills is enabling transfer for increased robot autonomy. With these core capabilities, we are exploring applications in healthcare and wellness, industry and service, farms and smart cities, and dangerous and unreachable settings -- deep in oceans, mines, and space.

  • Butrus Khuri-Yakub

    Butrus Khuri-Yakub

    Professor (Research) of Electrical Engineering, Emeritus

    BioButrus (Pierre) T. Khuri-Yakub is a Professor of Electrical Engineering at Stanford University. He received the BS degree from the American University of Beirut, the MS degree from Dartmouth College, and the Ph.D. degree from Stanford University, all in electrical engineering. His current research interests include medical ultrasound imaging and therapy, ultrasound neuro-stimulation, chemical/biological sensors, gas flow and energy flow sensing, micromachined ultrasonic transducers, and ultrasonic fluid ejectors. He has authored over 600 publications and has been principal inventor or co-inventor of 107 US and international issued patents. He was awarded the Medal of the City of Bordeaux in 1983 for his contributions to Nondestructive Evaluation, the Distinguished Advisor Award of the School of Engineering at Stanford University in 1987, the Distinguished Lecturer Award of the IEEE UFFC society in 1999, a Stanford University Outstanding Inventor Award in 2004, Distinguished Alumnus Award of the School of Engineering of the American University of Beirut in 2005, Stanford Biodesign Certificate of Appreciation for commitment to educate, mentor and inspire Biodesgin Fellows, 2011, and 2011 recipient of IEEE Rayleigh award.

  • Peter K. Kitanidis

    Peter K. Kitanidis

    Professor of Civil and Environmental Engineering

    BioKitanidis develops methods for the solution of interpolation and inverse problems utilizing observations and mathematical models of flow and transport. He studies dilution and mixing of soluble substances in heterogeneous geologic formations, issues of scale in mass transport in heterogeneous porous media, and techniques to speed up the decay of pollutants in situ. He also develops methods for hydrologic forecasting and the optimization of sampling and control strategies.

  • Ellen Kuhl

    Ellen Kuhl

    Walter B Reinhold Professor in the School of Engineering, Robert Bosch Chair of Mechanical Engineering, Professor of Mechanical Engineering and, by courtesy, of Bioengineering

    Current Research and Scholarly Interestscomputaitonal simulation of brain development, cortical folding, computational simulation of cardiac disease, heart failure, left ventricular remodeling, electrophysiology, excitation-contraction coupling, computer-guided surgical planning, patient-specific simulation

  • Ching-Yao Lai

    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.

  • Thomas Lee

    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.

  • Sanjiva Lele

    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.

  • Adrian Lew

    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.

  • Christian Linder

    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).

  • Ali Mani

    Ali Mani

    Associate Professor of Mechanical Engineering

    BioAli Mani is an associate professor of Mechanical Engineering at Stanford University. He is a faculty affiliate of the Institute for Computational and Mathematical Engineering at Stanford. He received his PhD in Mechanical Engineering from Stanford in 2009. Prior to joining the faculty in 2011, he was an engineering research associate at Stanford and a senior postdoctoral associate at Massachusetts Institute of Technology in the Department of Chemical Engineering. His research group builds and utilizes large-scale high-fidelity numerical simulations, as well as methods of applied mathematics, to develop quantitative understanding of transport processes that involve strong coupling with fluid flow and commonly involve turbulence or chaos. His teaching includes the undergraduate engineering math classes and graduate courses on fluid mechanics and numerical analysis.

  • Alison Marsden

    Alison Marsden

    Douglass M. and Nola Leishman Professor of Cardiovascular Diseases, Professor of Pediatrics (Cardiology) and of Bioengineering and, by courtesy, of Mechanical Engineering

    Current Research and Scholarly InterestsThe Cardiovascular Biomechanics Computation Lab at Stanford develops novel computational methods for the study of cardiovascular disease progression, surgical methods, and medical devices. We have a particular interest in pediatric cardiology, and use virtual surgery to design novel surgical concepts for children born with heart defects.

  • Todd Martinez

    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

  • Michaëlle Ntala Mayalu

    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

    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.

  • Ariam Mogos

    Ariam Mogos


    BioAriam Mogos leads emerging technology initiatives at Stanford's Hasso Plattner Institute of Design (, 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.

  • Parviz Moin

    Parviz Moin

    Franklin P. and Caroline M. Johnson Professor in the School of Engineering
    On Partial Leave from 10/01/2023 To 06/30/2024

    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.

  • Louie Montoya

    Louie Montoya


    BioA self-proclaimed deeper learning education nerd, Louie Montoya joined the 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

    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.

  • Sanjiv Narayan

    Sanjiv Narayan

    Professor of Medicine (Cardiovascular Medicine)
    On Partial Leave from 09/05/2023 To 06/30/2024

    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.

  • Brett Newman

    Brett Newman


    2013 - 2018 : Stanford : Lecturer : Visual Thinking, ME115C: Design and Business Factors
    2018 - Present : Stanford : Lead Lecturer : Design 161 Capstone

    2004 - 2007 : Azud : VP Product
    2007 - Present : Daylight Design : Partner

  • Brad Osgood

    Brad Osgood

    Professor of Electrical Engineering and, by courtesy, in Education
    On Leave from 10/01/2023 To 06/30/2024

    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.

  • Julia Palacios

    Julia Palacios

    Associate Professor of Statistics, of Biomedical Data Science and, by courtesy, of Biology

    BioDr. Palacios seek to provide statistically rigorous answers to concrete, data driven questions in evolutionary genetics and public health . My research involves probabilistic modeling of evolutionary forces and the development of computationally tractable methods that are applicable to big data problems. Past and current research relies heavily on the theory of stochastic processes, Bayesian nonparametrics and recent developments in machine learning and statistical theory for big data.

  • Arogyaswami Paulraj

    Arogyaswami Paulraj

    Professor (Research) of Electrical Engineering, Emeritus

    BioProfessor Emeritus Arogyaswami Paulraj, Stanford University, is a pioneer of MIMO wireless communications, a technology break through that enables improved wireless performance. MIMO is now incorporated into all new wireless systems.

    Paulraj is the author of over 400 research papers, two textbooks, and a co-inventor in 80 US patents.

    Paulraj has won over a dozen awards, notably the National Inventors Hall of Fame (USPTO), Marconi Prize and Fellowship, 2014 and the IEEE Alexander Graham Bell Medal, 2011. He is a fellow of eight scientific / engineering national academies including the US, China, India, and Sweden. He is a fellow of IEEE and AAAS.

    In 1999, Paulraj founded Iospan Wireless Inc. - which developed and established MIMO-OFDMA wireless as the core 4G technology. Iospan was acquired by Intel Corporation in 2003. In 2004, he co-founded Beceem Communications Inc. The company became the market leader in 4G-WiMAX semiconductor and was acquired by Broadcom Corp. in 2010. In 2014 he founded Rasa Networks to develop Machine Learning tools for WiFi Networks. The company was acquired HPE in 2016.

    During his 30 years in the Indian (Navy) (1961-1991), he founded three national-level laboratories in India and headed one of India’s most successful military R&D projects – APSOH sonar. He received over a dozen awards (many at the national level) in India including the Padma Bhushan, Ati Vishist Seva Medal and the VASVIK Medal.

  • Marco Pavone

    Marco Pavone

    Associate Professor of Aeronautics and Astronautics and, by courtesy, of Electrical Engineering and 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.

  • Markus Pelger

    Markus Pelger

    Assistant 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.

  • Mert Pilanci

    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.

  • Peter Pinsky

    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.

  • Jim Plummer

    Jim Plummer

    John M. Fluke Professor of Electrical Engineering and Professor, by courtesy, of Materials Science and Engineering

    Current Research and Scholarly InterestsGenerally studies the governing physics and fabrication technology of silicon integrated circuits, including the scaling limits of silicon technology, and the application of silicon technology outside traditional integrated circuits, including power switching devices such as IGBTs. Process simulation tools like SUPREM for simulating fabrication. Recent work has focused on wide bandgap semiconductor materials, particularly SiC and GaN, for power control devices.

  • Ada Poon

    Ada Poon

    Associate Professor of Electrical Engineering

    Current Research and Scholarly InterestsOur research focuses on providing theoretical foundations and engineering platforms for realizing electronics that seamlessly integrate with the body. Such systems will allow precise recording or modulation of physiological activity, for advancing basic scientific discovery and for restoring or augmenting biological functions for clinical applications.

  • Eric Pop

    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.

  • Christopher Re

    Christopher Re

    Associate Professor of Computer Science
    On Leave from 04/01/2024 To 06/30/2024

    Current Research and Scholarly InterestsAlgorithms, systems, and theory for the next generation of data processing and data analytics systems.

  • Juan Rivas-Davila

    Juan Rivas-Davila

    Associate Professor of Electrical Engineering and Senior Fellow at the Precourt Institute for Energy

    Current Research and Scholarly InterestsModern applications demand power capabilities beyond what is presently achievable. High performance systems need high power density and bandwidth that are difficult to achieve.
    Power density can be improved with better semiconductors and passive componets, and by reducing the energy storage requirements of the system. By dramatically increasing switching frequency it is possible to reduce size of power converters. I'm interested in high performance/frequency circuits switching >10 MHz.

  • Noah Rosenberg

    Noah Rosenberg

    Stanford Professor of Population Genetics and Society

    Current Research and Scholarly InterestsHuman evolutionary genetics, mathematical models in evolution and genetics, mathematical phylogenetics, statistical and computational genetics, theoretical population genetics

  • Grant M. Rotskoff

    Grant M. Rotskoff

    Assistant Professor of Chemistry

    BioGrant Rotskoff studies the nonequilibrium dynamics of living matter with a particular focus on self-organization from the molecular to the cellular scale. His work involves developing theoretical and computational tools that can probe and predict the properties of physical systems driven away from equilibrium. Recently, he has focused on characterizing and designing physically accurate machine learning techniques for biophysical modeling. Prior to his current position, Grant was a James S. McDonnell Fellow working at the Courant Institute of Mathematical Sciences at New York University. He completed his Ph.D. at the University of California, Berkeley in the Biophysics graduate group supported by an NSF Graduate Research Fellowship. His thesis, which was advised by Phillip Geissler and Gavin Crooks, developed theoretical tools for understanding nonequilibrium control of the small, fluctuating systems, such as those encountered in molecular biophysics. He also worked on coarsegrained models of the hydrophobic effect and self-assembly. Grant received an S.B. in Mathematics from the University of Chicago, where he became interested in biophysics as an undergraduate while working on free energy methods for large-scale molecular dynamics simulations.

    Research Summary

    My research focuses on theoretical and computational approaches to "mesoscale" biophysics. Many of the cellular phenomena that we consider the hallmarks of living systems occur at the scale of hundreds or thousands of proteins. Processes like the self-assembly of organelle-sized structures, the dynamics of cell division, and the transduction of signals from the environment to the machinery of the cell are not macroscopic phenomena—they are the result of a fluctuating, nonequilibrium dynamics. Experimentally probing mesoscale systems remains extremely difficult, though it is continuing to benefit from advances in cryo-electron microscopy and super-resolution imaging, among many other techniques. Predictive and explanatory models that resolve the essential physics at these intermediate scales have the power to both aid and enrich the understanding we are presently deriving from these experimental developments.

    Major parts of my research include:

    1. Dynamics of mesoscale biophysical assembly and response.— Biophysical processes involve chemical gradients and time-dependent external signals. These inherently nonequilibrium stimuli drive supermolecular organization within the cell. We develop models of active assembly processes and protein-membrane interactions as a foundation for the broad goal of characterizing the properties of nonequilibrium biomaterials.

    2. Machine learning and dimensionality reduction for physical models.— Machine learning techniques are rapidly becoming a central statistical tool in all domains of scientific research. We apply machine learning techniques to sampling problems that arise in computational chemistry and develop approaches for systematically coarse-graining physical models. Recently, we have also been exploring reinforcement learning in the context of nonequilibrium control problems.

    3. Methods for nonequilibrium simulation, optimization, and control.— We lack well-established theoretical frameworks for describing nonequilibrium states, even seemingly simple situations in which there are chemical or thermal gradients. Additionally, there are limited tools for predicting the response of nonequilibrium systems to external perturbations, even when the perturbations are small. Both of these problems pose key technical challenges for a theory of active biomaterials. We work on optimal control, nonequilibrium statistical mechanics, and simulation methodology, with a particular interest in developing techniques for importance sampling configurations from nonequilibrium ensembles.

  • Amin Saberi

    Amin Saberi

    Professor of Management Science and Engineering

    BioAmin Saberi is Professor of Management Science and Engineering at Stanford University. He received his B.Sc. from Sharif University of Technology and his Ph.D. from Georgia Institute of Technology in Computer Science. His research interests include algorithms, design and analysis of social networks, and applications. He is a recipient of the Terman Fellowship, Alfred Sloan Fellowship and several best paper awards.
    Amin was the founding CEO and chairman of NovoEd Inc., a social learning environment designed in his research lab and used by universities such as Stanford as well as non-profit and for-profit institutions for offering courses to hundreds of thousands of learners around the world.

  • Maria Sakovsky

    Maria Sakovsky

    Assistant Professor of Aeronautics and Astronautics

    BioMaria Sakovsky's work focuses on the use of shape adaptation to realize space structures with reconfigurable geometry, stiffness, and even non-mechanical performance (ex. electromagnetic, optical). Particular focus is placed on the mechanics of thin fiber reinforced composite structures, the interplay between composite material properties and structural geometry, as well as embedded functionality and actuation of lightweight structures. The work has led to applications in deployable space structures, reconfigurable antennas, and soft robotics.

    Maria Sakovsky received her BSc in Aerospace Engineering from the University of Toronto. Following this, she completed her MSc and PhD in Space Engineering at Caltech, where she developed a deployable satellite antenna based on origami concepts utilizing elastomer composites. She concurrently worked with NASA’s Jet Propulsion Laboratory on developing cryogenically rated thin-​ply composite antennas for deep space missions. For her ongoing research on physically reconfigurable antennas, she was awarded the ETH Zürich postdoctoral fellowship as well as the Innovation Starting Grant.

  • Alberto Salleo

    Alberto Salleo

    Hong Seh and Vivian W. M. Lim Professor

    Current Research and Scholarly InterestsNovel materials and processing techniques for large-area and flexible electronic/photonic devices. Polymeric materials for electronics, bioelectronics, and biosensors. Electrochemical devices for neuromorphic computing. Defects and structure/property studies of polymeric semiconductors, nano-structured and amorphous materials in thin films. Advanced characterization techniques for soft matter.