Jacob Yeung

Hello! I am a 1st year Ph.D. student in Neural Computation at Carnegie Mellon University supported by an NSF Graduate Research Fellowship.

My primary interests lie in understanding how vision can be used to guide motor behavior and using inspiration from biology towards improving computational models. To this end, my recent research explores subspace identification in neural and behavioral data, and self-supervised learning for images.

I recently graduated with a B.S. in Electrical Engineering and Computer Science (EECS) from UC Berkeley. My research was advised by Dr. Kristofer Bouchard and Dr. Ji Hyun Bak at the Lawrence Berkeley National Laboratory. I also worked with Medhini Narasimhan and Prof. Trevor Darrell at Berkeley AI Research (BAIR).

Email  /  Github  /  LinkedIn

profile photo
edca formulation photo Discovery of Linked Neural and Behavioral Subspaces with External Dynamic Components Analysis
Jacob Yeung, Ji Hyun Bak, Kristofer Bouchard
COSYNE, 2023
description / pdf / poster

We introduce external Dynamics Components Analysis (eDCA), a linear dimensionality reduction method that finds subspaces of past neural data that have maximal mutual information with subspaces of future behavior data.

hangul fonts photo Hangul Fonts Dataset: a Hierarchical and Compositional Dataset for Investigating Learned Representations
Jesse Livezey, Ahyeon Hwang, Jacob Yeung, Kristofer Bouchard
International Conference on Image Analysis and Processing, 2022
description / pdf

We introduce a dataset with known hierarchical and compositional structure and show deep unsupervised models poorly learn the latent generative structures.


I have been a teaching assistant for the following course:

I have been a tutor for the following courses:

berkeley logo University of California, Berkeley
Aug 2018 - Dec 2022

B.S. in Electrical Engineering and Computer Science
lbnl logo Lawrence Berkeley National Laboratory
Aug 2020 - July 2023

Research Intern
Advisor: Dr. Kristofer Bouchard and Dr. Ji Hyun Bak

Cloned from here!
Last updated: Sep 13, 2023