School of Engineering
Showing 4,101-4,200 of 5,933 Results
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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. -
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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Fauzan Rahman
Undergraduate, Computer Science
Bioall in on red
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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
SU Student - Summer, 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 -
Christopher Re
Professor of Computer Science
Current Research and Scholarly InterestsAlgorithms, systems, and theory for the next generation of data processing and data analytics systems.
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Daniel Reichman
Affiliate, Program-Barrett, C.
BioDaniel Reichman is an Assistant Professor at WPI and a Visiting Scholar at the Department of Computer Science at Stanford University (starting July 2026). He is interested in theoretical questions arising from artificial intelligence as well as using AI for mathematical and scientific discovery. Reichman completed his PhD in computer science and applied mathematics at the Weizmann Institute and held postdoctoral scholar positions at Cornell, Berkeley and Princeton.
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Kate Reidy
Affiliate, Materials Science and Engineering
BioKate Reidy will begin as an Assistant Professor of Materials Science and Engineering at Stanford in September 2026. Her research takes a ‘bottom up' approach to nanoscale design, tailoring material properties by understanding and manipulating their atomic structure. She combines advanced characterization with in situ microscopy to elucidate growth mechanisms, chemical composition, and response to stimuli at the atomic scale.
Her research group aims to push the limits of nanoscale engineering by observing and controlling atomic-scale kinetic and thermodynamic phenomena such as adsorption, diffusion, nucleation, defect and interface formation - mapping such structural dynamics to quantum, energy, and opto-electronic properties. She is broadly interested in the functional utilization of quantum properties of nanomaterials in our classical world.
Prior to joining Stanford, Kate was a Miller Postdoctoral Fellow at UC Berkeley and Lawrence Berkeley National Lab. She completed her PhD in Materials Science & Engineering at MIT as a MIT Energy initiative and William Asbjornsen Albert Memorial Fellow, entitled 'Atomic-Scale Design at the 2D/3D Interface using Electron Microscopy'. She received her B.Sc in Nanoscience, Physics, and Chemistry of Advanced Materials from Trinity College Dublin, Ireland. Her work has been recognized by the MIT School of Engineering, Microscopy Society of America, Materials Research Society Gold Award, 'Best Doctoral Thesis' Award at MIT DMSE, and the Lemelson-Vest Award for Innovation.
