CV

Innovation Fellow

Defense Advanced Research Projects Agency (DARPA)

Entrepreneurial two-year postdoctoral fellowship developing, funding, and managing exploratory high-risk research and technology development.

• Co-lead for DARPA CRYSTAL (Crystal Substrate Bonding Technologies and Algorithms) program, including solicitation development, source selection, and program management
• Co-manager for DARPA DUF (Discovering Unknome Function)

PhD

Stanford University

Electrical Engineering

• Computational and experimental visual neuroscience under the supervision of Prof. E.J. Chichilnisky.
• Developed generative image decoder for reconstructing natural images from large-scale MEA recordings of macaque monkey retina with convex optimization and deep denoiser neural network image priors. Achieved state-of-the-art image fidelity (first-author, NeurIPS), first blind motion deblurring demonstration with eye movements from retinal recordings (first-author, Nature Communications).
• Convex optimization and machine learning for identifying neuron cell types from recorded voltage signals (first-author, Journal of Neural Engineering).
• Prototyping for BCI. Built electrophysiology rig (mechanical, electrical, software development) for retinal recordings with 3D microelectrode arrays (second-author, Science Advances).
• Extensive software development for spike-sorting, large scale neural data infrastructure, signal processing, etc.

MS

Stanford University

Electrical Engineering

• solid state devices, nanofabrication, MEMS device design, machine learning, deep learning, convex optimization, systems neuroscience
• Research in MEMS under supervision of Prof. Roger T. Howe. Design, simulation, and nanofabrication for wafer-scale thermionic energy converter.

BS

University of California, Berkeley

Electrical Engineering and Computer Science

• analog integrated circuits, digital integrated circuits, semiconductor devices, digital signal processing, algorithms and CS theory, data structures, artificial intelligence, quantum mechanics
• Research in electronics for wearable sweat stimulation and sensing under supervision of Prof. Ali Javey. Author on 5+ peer-reviewed journal articles
• Teaching assistant for EE40 and EE16B introductory courses in electrical engineering

National Defense Science and Engineering Graduate (NDSEG) Fellowship

United States Department of Defense

The National Defense Science and Engineering Graduate (NDSEG) Fellowship program was established in 1989 by direction of Congress as an approach to increasing the number of United States (U.S.) citizens receiving doctoral degrees in science and engineering (S&E) disciplines of military importance.

Maximum a posteriori natural scene reconstruction from retinal ganglion cells with deep denoiser priors

NeurIPS

Nonlinear inverse problem for decoding static natural images from retinal neural spikes trains, combining interpretable generalized linear neural encoding models with deep denoising neural network image priors for MAP decoding. Demonstrated state-of-the-art decoded image fidelity (on ImageNet) using electrophysiologically-recorded spike trains from large populations of retinal ganglion cells (700+ cells), while using orders-of-magnitude fewer model parameters than competing methods.

Fixational eye movements enhance the precision of visual information transmitted by the primate retina

Nature Communications

Simultaneous decoding of natural movies and eye movements from retinal neural spike trains using nonlinear inverse problem formulation (combining generalized linear neural encoding models, deep denoising neural network image priors, and expectation maximization for approximate MAP decoding). First experimental demonstration of blind motion deblurring and super-resolution imaging from electrophysiologically-recorded spike trains of retinal ganglion cells, showing that the primate visual system can exploit fine eye movments to improve fidelity of the visual signal.

Decomposition of retinal ganglion cell electrical images for cell type and functional inference

Journal of Neural Engineering

Non-convex optimization algorithm to estimate and isolate axonal, dendritic, and somatic signal components from extracellularly-recorded spike voltage templates of retinal ganglion cells. Featurizations produced by this algorithm enabled significant gains in accuracy over state-of-the-art for predicting receptive fields and retinal ganglion cell types from voltage signals alone, with applications for retinal prosthetic devices that restore vision.

Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform

PNAS

Integrated electronic system for wearable sweat stimulation and sweat metabolite and electrolyte chemical sensing, applied to cystic fibrosis diagnosis and real-time glucose monitoring. I designed the sensor interface and sweat stimulation electronics, wrote all of the embedded firmware, and participated in experimental evaluation for the system.