School of 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.
