Hi, I'm Gabe Sarch

I'm a third-year Ph.D. student at Carnegie Mellon University in the Neural Computation and Machine Learning joint PhD program under the supervision of Dr. Katerina Fragkiadaki and Dr. Mike Tarr. My work is supported by the National Science Foundation Graduate Research Fellowship. Previously, I received a B.S. in Biomedical Engineering from the University of Rochester, where I studied the marmoset visual system under Dr. Jude Mitchell.

profile photo

Embodied intelligence

Animals utilize self-supervision, commonsense reasoning, and interaction to make sense of sensory inputs and perform embodied tasks without a significant amount of explicit labels or instructions. However, most state-of-the-art embodied systems require millions of human annotations and are not able to generalize their previously learned knowledge to accurately reason about novel inputs or tasks. My research focuses on embodied artificial agents that learn, act and reason by interactive and active means, drawing from psychological and neuroscientific literature when it is useful.

Computer vision models of the primate visual system

Deep neural networks optimized for visual tasks have been shown to be good predictive models of neural responses in visual areas (e.g. fMRI, electrophysiology - see here). By modeling the representations and behaviors of primates with AI systems optimized for different tasks and inputs, we can better understand the neural representations underlying naturalistic stimuli processing in primates.


TIDEE: Tidying Up Novel Rooms using Visuo-Semantic Commonsense Priors

GH SarchZ FangAW HarleyP SchydloMJ TarrS GuptaK Fragkiadaki
ECCV 2022

Beyond Fixation: detailed characterization of neural selectivity in free-viewing primates

JL YatesSH CoopGH SarchR WuD ButtsM Rucci Jude Mitchell

Move to See Better: Towards Self-Improving Embodied Object Detection

GH Sarch*Z Fang*A Jain*AW Harley K Fragkiadaki
*equal contribution
BMVC 2021

See all my publications