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Bing Wen Brunton

Ph.D. in Molecular Biology & Neuroscience, Princeton University, 2012

B.S. in Biology, California Institute of Technology (Caltech), 2006

Photograph by Carl Bergstrom

Postdoctoral Researchers


Katie Stanchak, Ph.D.

Postdoctoral Researcher

Ph.D., University of Washington, Biology
B.S., Massachusetts Institute of Technology, Mechanical Engineering 

Katie is a postdoc co-advised with David Perkel. She is an evolutionary biologist primarily interested in how anatomical novelty influences the evolution of animal locomotion. Her doctoral project in the lab of Sharlene Santana at UW focused on a unique skeletal element in the bat hindlimb wing membrane. Currently, she is trying to understand the exceptional lumbosacral spinal cord of birds, which may act as a mechanosensory structure that helps birds balance. She is also working with a team to study the evolution of distributed sensor placement on insect wings and the implications of sensor placement on sensing ability for different wing morphologies.



Harsha Gurnani, Ph.D.

Schmidt Science Fellow

UW Data Science Postdoctoral Fellow

Ph.D., University College London, Neuroscience
B.S., Indian Institute of Science, Biology and Mathematics

Harsha joined the lab in 2023 as a postdoctoral fellow. She is broadly interested in the role of sensory feedback and internal models in motor learning, including when it may potentially lead to sub-optimal learning. Currently, she is modeling these processes in artificial neural networks, but is always excited about testing these ideas in neural recordings (data-wrangling being her favorite). She is also interested in using control theoretic approaches and computational models to design and interpret perturbations of neural circuits, such as when using optogenetics for “causal” inferences. In her free time, she enjoys all forms of contemporary art, poetry, petting dogs and (car-free) hiking.



Elliott Abe, Ph.D.

Swartz Theory Fellow

UW Data Science Postdoctoral Fellow

Ph.D., University of Oregon, Biology
B.S., University of Washington, Physics

Elliott is a computational and theoretical neuroscientist whose research focuses on the brain’s ability to process diverse types of information, as well as extract and utilize representations to guide behavior. His work aims to establish general principles that can be applied across different contexts, drawing on insights and techniques from a range of disciplines including neuroscience, machine learning, and physics. By integrating knowledge and tools from these fields, he seeks to develop biologically grounded theories, models, and data analysis methods that can deepen our understanding of neural representations underlying natural behaviors.


Graduate Students


Michelle Hickner

Ph.D. student in Mechanical Engineering

M.S., University of Washington, Applied Mathematics
B.A., Oberlin College, Physics

Michelle is co-advised with Steve Brunton. Her current research is on sparse sensor placement for control and categorization in biological and engineered systems. She is interested in bio-inspired mathematical methods.



Zoe Steine-Hanson

Ph.D. student in Computer Science & Engineering

NSF Grad Fellow

H.B.S., Oregon State University, Computer Science
Zoe is co-advised with Rajesh Rao. She came to Seattle to work in the fascinating intersection between Neuroscience and Machine Learning. Her research interests broadly cover Machine Learning, Cognitive Science and Neuroscience. In her undergrad, she was involved with research on how gender biases manifest in software interfaces and how to fix these biases.



Raveena Chhibber

Ph.D. student in Neuroscience

NSF Grad Fellow

B.S. Emory University, Neuroscience


Raveena is a graduate student co-advised by John Tuthill interested in motor control and Machine Learning. Before grad school, she used information-theoretic methods to understand the timescale of motor sequencing in songbirds.


Jianqiao (Lawrence) Hu

Ph.D. student in Neuroscience

B.A. Boston University, Statistics & Biology

Lawrence is a graduate student enrolled in the Neuroscience program, co-advised by Edgar Walker. His research focus revolves around unraveling the intricate processes through which sensory information is represented in the brain, utilizing machine learning techniques. Before relocating to Seattle, Lawrence dedicated his efforts to improving the scalability of high-throughput sequencing data preprocessing, aiming to deepen our understanding of somatic recombination mechanisms.



Sarah Pugliese

Ph.D. student in Neuroscience

B.S. Brown University,  Applied Mathematics-Biology


Sarah is a neuroscience graduate student co-advised with John Tuthill. She is studying the structure and function of proprioceptive and motor circuits in the Drosophila ventral nerve cord. Her approach combines working with network models derived from the synapse-level connectome and performing optogenetics experiments in flies.



Kameron Decker Harris, Ph.D. (next position: Assistant Professor of Computer Science, Western Washington University)

Aditya G. Nair, Ph.D. (next position: Assistant Professor of Mechanical Engineering, University of Nevada Reno)

Steven Peterson, Ph.D. (next position: Facebook)

Urban Fasel, Ph.D. (next position: Lecturer of Aeronautics at Imperial College London)

Ali Weber, Ph.D. (next position: Assistant Professor of Neuroscience, Bryn Mawr College)


Nancy X. R. Wang, Ph.D. in CSE, 2018  (next position: IBM Research; now at Amazon)

Nate Linden (next position: Ph.D. student at UCSD Mechanical Eng.)

Seth Hirsh, Ph.D. in Physics, 2020 (next position: Lyft)

Sara Ichinaga (next position: Ph.D. student at UW Applied Math)

Satpreet Singh, Ph.D. in Electrical and Computer Engineering, 2021 (next position: Meta; now at Baylor)

Aaron D. Garcia, Ph.D. in Neuroscience, 2023 (next position: Allen Institute)

Lili Karashchuk, Ph.D. in Neuroscience, 2023 (next position, Allen Institute)

Prospective Grad Students

Students interested in joining the lab for graduate studies should submit applications for admission through one of the following University of Washington Ph.D. graduate programs:

  1. Biology

  2. Neuroscience

  3. Computer Science & Engineering

  4. Applied Mathematics

Postdoc Researcher Positions

We are actively recruiting talented new postdocs to join the group! If you are excited about doing research in big data, applied mathematics, machine learning, and neuroscience, email Bing (please include a copy of your CV). 

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