What do visual prosthesis users see, and why? Clinical studies have shown that the vision provided by current devices differs substantially from normal sight.
Jacob Granley is a PhD student in the Department of Computer Science.
Prior to joining UCSB, he received his Masters and Bachelors in Computer Science from Colorado School of Mines. He is pursuing his PhD under Dr. Beyeler as part of the Bionic Vision lab, where he hopes to use Computer Science and Machine Learning methods to help improve artificial vision technologies with the ultimate goal of restoring sight to the blind.
MS in Computer Science, 2020
University of Colorado, School of Mines
BS in Computer Science, 2019
University of Colorado, School of Mines
What do visual prosthesis users see, and why? Clinical studies have shown that the vision provided by current devices differs substantially from normal sight.
Rather than predicting perceptual distortions, one needs to solve the inverse problem: What is the best stimulus to generate a desired visual percept?
pulse2percept is an open-source Python simulation framework used to predict the perceptual experience of retinal prosthesis patients across a wide range of implant configurations.
We systematically incorporated neuroscience-derived architectural components into CNNs to identify a set of mechanisms and architectures that comprehensively explain neural activity in V1.
Galen Pogoncheff, Jacob Granley, Michael Beyeler 37th Conference on Neural Information Processing Systems (NeurIPS) ‘23
We propose a personalized stimulus encoding strategy that combines state-of-the-art deep stimulus encoding with preferential Bayesian optimization.
Jacob Granley, Tristan Fauvel, Matthew Chalk, Michael Beyeler 37th Conference on Neural Information Processing Systems (NeurIPS) ‘23
We retrospectively analyzed phosphene shape data collected form three Argus II patients to investigate which neuroanatomical and stimulus parameters predict paired-phosphene appearance and whether phospehenes add up linearly.
Yuchen Hou, Devyani Nanduri, Jacob Granley, James D. Weiland, Michael Beyeler medRxiv:2023.07.21.23292908v1
We show that a neurologically-inspired decoding of CNN activations produces qualitatively accurate phosphenes, comparable to phosphenes reported by real patients.
Jacob Granley, Alexander Riedel, Michael Beyeler Shared Visual Representations in Human & Machine Intelligence (SVRHM) Workshop, NeurIPS ‘22
What is the required stimulus to produce a desired percept? Here we frame this as an end-to-end optimization problem, where a deep neural network encoder is trained to invert a known, fixed forward model that approximates the underlying biological system.
Jacob Granley, Lucas Relic, Michael Beyeler 36th Conference on Neural Information Processing Systems (NeurIPS) ‘22
We present a phenomenological model that predicts phosphene appearance as a function of stimulus amplitude, frequency, and pulse duration.
Jacob Granley, Michael Beyeler IEEE Engineering in Medicine and Biology Society Conference (EMBC) ‘21
We propose HBA-U-Net: a U-Net backbone with hierarchical bottleneck attention to highlight retinal abnormalities that may be important for fovea and optic disc segmentation in the degenerated retina.
Shuyun Tang, Ziming Qi, Jacob Granley, Michael Beyeler MICCAI Workshop on Ophthalmic Image Analysis - OMIA ‘21