School of Engineering
Showing 481-490 of 683 Results
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J David Powell
Professor of Aeronautics and Astronautics and of Mechanical Engineering, Emeritus
BioEDUCATION:
1960 - B.S. Mechanical Engineering, M.I.T.
1966 - M.S. Aeronautics & Astronautics, Stanford
1970 - Ph.D. Aeronautics & Astronautics, Stanford
EXPERIENCE:
1960-1961 - Engine Design and Testing Engineer at Outboard Marine Corp.
1961-1967 – Engineer at Lockheed in the field of Aerospace Guidance and Control
1967-1968 – Engineer at Analytical Mechanics Associates
1968-1970 – Engineer, Systems Control, Inc. Parameter ID of aircraft models from flight data, automatic generation of approach paths for Air Traffic Control. Attended Stanford University specializing in control systems.
1971 – 1998 – Member of the Stanford Faculty in the Aeronautics and Astronautics Department. His research has included spacecraft pointing, space tether dynamics and control, internal combustion engine control, the design of aerospace digital flight control systems, GPS-based attitude determination augmented with inertial sensors, and the use of GPS for air and land vehicle surveillance and navigation. He taught courses in aerospace control including radio and inertial navigation, optimization and digital implementations and is a coauthor of two of the leading control textbooks. He is also an author or coauthor on over 100 papers.
1998 – present – Emeritus faculty carrying out research in Aeronautics and Astronautics at Stanford Univ. Recent focus of research is the use of GPS-based attitude determination augmented with inertial sensors, applications of the FAA’s WAAS for enhanced pilot displays, flight inspection of aircraft landing systems, and the use of WAAS and new displays to enable closer spacing of parallel runways.
SOCIETY MEMBERSHIPS
AIAA (Fellow), ASME (Fellow), SAE, IEEE, ION
CONSULTANT TO: (over past several years)
Seagull Technology
Sequoia Instruments
Engine Control and Monitoring
Transparent Networks
Pratt and Whitney (Technical Advisory Committee)
Sensor Platforms
OTHER RECENT ACTIVITIES
Co-Founder, CEO, and Director of GyroSat Corp. 1999 – 2000
Director of Sequoia Instruments, 2001 – 2005
Aircraft owner and licensed instrument pilot
National Research Council Panel member for the review of NASA airspace activities, 2003
Board of Directors, Mechanics Bank, Richmond, CA., 2003 – 2015
Board of Directors, ExactBid, Inc. 2014-present. -
Balaji Prabhakar
VMware Founders Professor of Computer Science, Professor of Electrical Engineering and, by courtesy, of Operations, Information and Technology at the Graduate School of Business
BioPrabhakar's research focuses on the design, analysis, and implementation of data networks: both wireline and wireless. He has been interested in designing network algorithms, problems in ad hoc wireless networks, and designing incentive mechanisms. He has a long-standing interest in stochastic network theory, information theory, algorithms, and probability theory.
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Manu Prakash
Associate Professor of Bioengineering, Senior Fellow at the Woods Institute for the Environment and Associate Professor, by courtesy, of Oceans
BioWe use interdisciplinary approaches including theory and experiments to understand how computation is embodied in biological matter. Examples include cognition in single cell protists and morphological computing in animals with no neurons and origins of complex behavior in multi-cellular systems. Broadly, we invent new tools for studying non-model organisms with significant focus on life in the ocean - addressing fundamental questions such as how do cells sense pressure or gravity? Finally, we are dedicated towards inventing and distributing “frugal science” tools to democratize access to science (previous inventions used worldwide: Foldscope, Abuzz), diagnostics of deadly diseases like malaria and convening global citizen science communities to tackle planetary scale environmental challenges such as mosquito surveillance or plankton surveillance by citizen sailors mapping the ocean in the age of Anthropocene.
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Friedrich Prinz
Leonardo Professor, Professor of Mechanical Engineering, of Materials Science and Engineering and Senior Fellow at the Precourt Institute for Energy
BioFritz Prinz is the Leonardo Professor in the School of Engineering at Stanford University, Professor of Materials Science and Engineering, Professor of Mechanical Engineering, and Senior Fellow at the Precourt Institute for Energy. He also serves as the Director of the Nanoscale Prototyping Laboratory and Faculty Co-director of the NPL-Affiliate Program. A solid-state physicist by training, Prinz leads a group of doctoral students, postdoctoral scholars, and visiting scholars who are addressing fundamental issues on energy conversion and storage at the nanoscale. In his Laboratory, a wide range of nano-fabrication technologies are employed to build prototype fuel cells and capacitors with induced topological electronic states. We are testing these concepts and novel material structures through atomic layer deposition, scanning tunneling microscopy, impedance spectroscopy and other technologies. In addition, the Prinz group group uses atomic scale modeling to gain insights into the nature of charge separation and recombination processes. Before coming to Stanford in 1994, he was on the faculty at Carnegie Mellon University. Prinz earned a PhD in Physics at the University of Vienna.
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Patrick Lee Purdon
Professor of Anesthesiology, Perioperative and Pain Medicine (Department Research) and, by courtesy, of Bioengineering
BioMy research integrates neuroimaging, biomedical signal processing, and the systems neuroscience of general anesthesia and sedation.
My group conducts human studies of anesthesia-induced unconsciousness, using a variety of techniques including multimodal neuroimaging, high-density EEG, and invasive neurophysiological recordings used to diagnose medically refractory epilepsy. We also develop novel methods in neuroimaging and biomedical signal processing to support these studies, as well as methods for monitoring level of consciousness under general anesthesia using EEG. -
Stanley Qi
Associate Professor of Bioengineering and, by courtesy, of Biomedical Data Science
BioStanley Qi (publishing as Lei S. Qi) is a pioneer in the field of genome engineering and the architect of the foundational technologies that transitioned CRISPR from a "cutting" tool into a universal platform for Programmable Biology. As the inventor of CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa), Qi established the first methods for the precise, reversible, and targeted regulation of the human genome without altering the DNA sequence.
The Qi Lab integrates scalable genomic perturbation with live-cell and super-resolution imaging and computation-guided design to redefine the boundaries of cellular control. Under Dr. Qi’s leadership, the group has fundamentally expanded the genome engineering toolbox, evolving CRISPR from a single editing tool into a multidimensional platform for the precise control of dynamic and spatial cell states. This work includes establishing foundational technologies and architectures for precise epigenetic editing, multiplexed regulation of the transcriptome, programmable 3D genome organization, and spatial control of RNA logistics. By pioneering real-time visualization of chromatin dynamics and RNA in living cells, the lab provides an unprecedented window into the fundamental "control principles of life."
This principle-driven technology lineage has moved into the clinic, with the lab's compact epigenetic editor currently in first-in-human clinical testing for FSHD muscular dystrophy (NCT06907875). This milestone represents a core mission of the lab: translating foundational engineering into next-generation therapeutics that act predictably as dynamic, complex systems.
Beyond single-cell control, the Qi Lab is building a framework for synthetic cell–cell communication, with a particular emphasis on the bidirectional interplay between immune cells and neurons. The lab’s goal is to move beyond describing molecular parts to discovering fundamental control principles in living systems: how regulatory landscapes create stable states and memory, how spatial genome–RNA organization shapes dynamic responses, and how engineered cell–cell interactions can generate emergent multicellular behaviors.
By integrating computational design with experimental biology, Dr. Qi aims to identify the generalizable rules linking molecular programs to systems-level physiology. He is a Chan Zuckerberg Biohub Investigator and an Institute Scholar at the Sarafan ChEM-H, and is dedicated to shaping the technical and ethical frameworks that will define the future of human genome engineering. -
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.
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Xiaojie Qiu
Assistant Professor of Genetics and, by courtesy, of Computer Science
Current Research and Scholarly InterestsAt the Qiu Lab, our mission is to unravel and predict the intricacies of gene regulatory networks and cell-cell interactions pivotal in mammalian cell fate transitions over time and space, with a special emphasis on heart evolution, development, and disease. We are a dynamic and interdisciplinary team, harnessing the latest advancements in machine learning as well as single-cell and spatial genomics by integrating the predictive power of systems biology with the scalability of machine learning,
