School of Engineering
Showing 4,401-4,500 of 6,464 Results
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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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Amanda Pratt
Ph.D. Student in Management Science and Engineering, admitted Autumn 2022
BioAmanda Pratt is a Ph.D. candidate in Management Science at Stanford University, where she is part of the Center for Work, Technology, and Organization. Her research interests include how organizations must change to adopt technology – particularly data and ML-based technologies - and how technology changes them. Prior to returning to school, Amanda was a Principal at Keystone Strategy, a technology-focused consulting firm. Amanda holds a bachelor's degree in engineering from Olin College, a master's degree in engineering from UC Berkeley, and an MBA from Harvard University.
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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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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. -
Alejandro Pulido
Undergraduate, Mechanical Engineering
BioSophomore in the class of 2028 studying Mechanical Engineering!
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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. -
Lei (Stanley) Qi
Associate Professor of Bioengineering
BioDr. Lei (Stanley) Qi (publishes as Lei S. Qi) is an Associate Professor in the Department of Bioengineering at Stanford University, an Institute Scholar at Sarafan ChEM-H, and a Chan Zuckerberg Biohub Investigator. Trained in physics and mathematics (Tsinghua University) and bioengineering (UC Berkeley), he was a Systems Biology Fellow at UCSF before joining the Stanford faculty in 2014.
Qi is a pioneer in CRISPR technology and genome engineering. His lab created the first nuclease-deactivated Cas9 (dCas9) for targeted gene regulation, establishing CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa). Since then, his group has expanded CRISPR from an editing tool into a platform for programmable control of dynamic and spatial cell state, integrating scalable perturbation, live-cell and super-resolution imaging, and computation-guided design. This work has produced technologies for multiplexed transcriptome regulation, programmable 3D genome organization, spatial RNA logistics control, and real-time visualization of chromatin and transcriptional events in living cells.
A distinctive focus of the Qi lab is closed-loop biology, combining perturbation with high-content measurements to infer mechanisms and iteratively refine control strategies. The lab develops platforms spanning multiplexed transcriptional and epigenetic control, spatial genome–transcriptome organization, and quantitative live-cell imaging of chromatin and transcriptional dynamics. A compact nuclease-dead CRISPR epigenetic editor from this technology lineage has advanced to first-in-human clinical testing for facioscapulohumeral muscular dystrophy (FSHD; NCT06907875), underscoring the translational potential of principle-driven control systems.
Beyond single-cell control, Qi’s lab is building a framework for synthetic cell–cell communication, with 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 experimental bioengineering with computation and machine learning, the lab aims to identify generalizable rules linking molecular programs to systems-level physiology and disease trajectories and to translate those rules into next-generation therapeutic cells. -
Gary Qian
Ph.D. Student in Management Science and Engineering, admitted Autumn 2021
BioI am currently a 2nd year PhD student in Management Science and Engineering at Stanford working with Professor Margaret Brandeau. My research focuses on the development of applied mathematical, economic models, and machine learning models to support health policy decisions. My recent work has been focused on HIV prevention and treatment programs, programs to control US opioid epidemic, and policies for minimizing spread of infectious diseases (including COVID-19).
I am passionate about using optimization theory and machine learning to implement scalable solutions in solving complex, real-world problems including but not limited to applications in healthcare. -
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,
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Stephen Quake
Lee Otterson Professor in the School of Engineering and Professor of Bioengineering, of Applied Physics and, by courtesy, of Physics
Current Research and Scholarly InterestsSingle molecule biophysics, precision force measurement, micro and nano fabrication with soft materials, integrated microfluidics and large scale biological automation.
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Priyanka Raina
Associate Professor of Electrical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsFor Priyanka's research please visit her group research page at https://stanfordaccelerate.github.io
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Ram Rajagopal
Associate Professor of Civil and Environmental Engineering, of Electrical Engineering and Senior Fellow at the Precourt Institute for Energy
BioRam Rajagopal is an Associate Professor of Civil and Environmental Engineering at Stanford University, where he directs the Stanford Sustainable Systems Lab (S3L), focused on large-scale monitoring, data analytics and stochastic control for infrastructure networks, in particular, power networks. His current research interests in power systems are in the integration of renewables, smart distribution systems, and demand-side data analytics.
He holds a Ph.D. in Electrical Engineering and Computer Sciences and an M.A. in Statistics, both from the University of California Berkeley, Masters in Electrical and Computer Engineering from University of Texas, Austin and Bachelors in Electrical Engineering from the Federal University of Rio de Janeiro. He is a recipient of the NSF CAREER Award, Powell Foundation Fellowship, Berkeley Regents Fellowship and the Makhoul Conjecture Challenge award. He holds more than 30 patents and several best paper awards from his work and has advised or founded various companies in the fields of sensor networks, power systems, and data analytics. -
Ashwin Ramaswami
Affiliate, Program-Liang, P.
BioAshwin is currently CTO and Co-founder at Corridor, a startup using AI to help security teams fix vulnerabilities at scale. With a CS degree at Stanford and law degree at Georgetown, Ashwin worked in the federal government at CISA on cybersecurity and election security. https://ashwin.run/
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Vedanth Ramji
Undergraduate, Computer Science
BioLinkedIn: www.linkedin.com/in/vedanth-ramji
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Yash Rampuria
Masters Student in Aeronautics and Astronautics, admitted Autumn 2025
BioI am an MS student, pursuing robotics at Stanford University. I am particularly interested in AI applications to autonomous mobility. My work at the Indian Institute of Technology Bombay has spanned the intersection of computer vision, SLAM and controls for self-driving, drones and healthcare. I have served as the CTO of Autonomous systems at IIT Bombay Racing Driverless, leading a team of 100+ students in building self-driving race cars for Formula Student, United Kingdom.
Leading multiple teams throughout my education has allowed me to hone my teamwork and management skills, while staying deeply involved in engineering and technology. -
Akshita Rao
Ph.D. Student in Bioengineering, admitted Autumn 2022
Other Tech - Graduate, Summer SessionCurrent Research and Scholarly InterestsMultimodal electrophysiology, sleep neuroscience
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Ashwin Rao
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
BioMy current research and teaching is in Machine Learning (specifically RL) with applications to Financial Markets and Retail businesses. My academic origins are in Algorithms Theory and Abstract Algebra. More details on my background are here: https://www.linkedin.com/in/ashwin2rao/
My Stanford Home Page: https://stanford.edu/~ashlearn
CME 241 ("RL for Finance"), which I teach each Winter quarter: http://cme241.stanford.edu
