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Sarah Harvey, Ph.D.


Department of Applied Physics, Stanford University

Orcid: 0000-0003-2601-7487
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I am a recent graduate of the applied physics department at Stanford University, where I am a theorist in the Ganguli Lab. My current research interests focus on using methods from nonequilibrium statistical physics and large deviation theory to study biological computation, from the micoscopic scale of single receptor computations to macroscopic reinforcement learning. I am interested generally in statistical physics, computational neuroscience, and machine learning.

My latest paper (with Subhaneil Lahiri) studies thermodynamic limits on sensors modeled as continuous time Markov chains, using stochastic thermodynamics and large deviation theory. We can place interesting bounds on sensors of this type by first deriving a thermodynamic uncertainty relation for densities in subsets of Markov chain states.

With Chris Stock and Sam Ocko, I have also recently been working on a project deriving biologically plausible synaptic update rules that provably preserve the task an RNN is trained to do, while also increasing the network robustness. We can think of this synaptic update rule as traversing a manifold in synaptic weight space of networks that perform exactly the same task, to find the network with the best noise robustness quality.

Both of these projects have associated preprints that are listed below.

I have recently defended, and will be starting as a research fellow at the Flatiron Institute in Fall 2022!

Publication Links

Sarah E. Harvey, Subhaneil Lahiri, Surya Ganguli. (2022). Universal energy-accuracy tradeoffs in nonequilibrium cellular sensing. Preprint: https://arxiv.org/abs/2002.10567.

Christopher H. Stock, Sarah E. Harvey, Samuel A. Ocko, Surya Ganguli. (2021). Synaptic balancing: a biologically plausible local learning rule that provably increases neural network noise robustness without sacrificing task performance. PLOS Computational Biology (link). Preprint: https://arxiv.org/abs/2107.08530.

Todd Karin, Xiayu Linpeng, M. M. Glazov, M. V. Durnev, E. L. Ivchenko, Sarah Harvey, Ashish K. Rai, Arne Ludwig, Andreas D. Wieck, and Kai-Mei C. Fu. July 2016. Giant permanent dipole moment of two-dimensional excitons bound to a single stacking fault. Physical Review B, 94(4). doi:10.1103/physrevb.94.041201. (link)

Education

University of Washington               B.S., Physics and Astronomy, summa cum laude, 2015

Stanford University                 Ph.D., Applied Physics, 2022

Talks

Teaching

Honors, Awards, Programs

Some other stuff I enjoy

OEIS
Ham radio: KI7UXI
Drawing
Ben Sorscher's Website
US mail: Sarah Harvey
         ChEM-H / Neuro research complex
         290 Jane Stanford Way
         Stanford, CA 94305
Email:   harveys@stanford.edu
Twitter: @SarahLizHarvey

Sarah Harvey < harveys@stanford.edu>
Last modified: 10/21