Cheol Jun Cho

Hi, I am a PhD student in EECS at UC Berkeley. I am co-advised by Dr. Gopala K. Anumanchipalli and Dr. Jack L. Gallant. I closely collaborate with Chang Lab led by Dr. Edward Chang at UCSF. I am the recipeint of the Eli Jury Award from UC Berkele EECS, and I am supported by Kwanjeong Educational Foundation Fellowship. Before I came to Berkeley, I received a B.S. in Computer Science and Engineering at Seoul National University in Korea.

My main research focus is on investigating the representational basis of intelligence - How do intelligent systems represent complex behaviors and concepts? Can we design representations that are more grounded and interpretable? Currently, I am answering these questions in speech domain using diverse techniuqes in machine learning, AI, and neuroscience.

Email / CV / Google Scholar

Research Topics:

Grounded, interpretable, and efficient representation for spoken language modeling (SPARC, Sylber)
AI-empowered brain-computer interfaces and brain-AI foundational models (NLA, streaming speech BCI )
Computational neuroscience of spoken language

Publications

	A streaming brain-to-voice neuroprosthesis to restore naturalistic communication Cheol Jun Cho, Kaylo T. Littlejohn, Jessie R. Liu, Alexander B. Silva, Bohan Yu, Vanessa R. Anderson, Cady M. Kurtz-Miott, Samantha Brosler, Anshul P. Kashyap, Irina P. Hallinan, Adit Shah, Adelyn Tu-Chan, Karunesh Ganguly, David A. Moses, Edward F. Chang & Gopala K. Anumanchipalli Equal contribution Nature Neuroscience* 2025 paper
	Sylber: Syllabic Embedding Representation of Speech from Raw Audio Cheol Jun Cho, Nicholas Lee, Akshat Gupta, Dhruv Agarwal, Ethan Chen, Alan W Black, Gopala K. Anumanchipalli ICLR 2025 paper code
	Coding Speech through Vocal Tract Kinematics Cheol Jun Cho, Peter Wu, Tejas S. Prabhune, Dhruv Agarwal, Gopala K. Anumanchipalli JSTSP 2024 paper code
	SD-HuBERT: Sentence-Level Self-Distillation Induces Syllabic Organization in HuBERT Cheol Jun Cho, Abdelrahman Mohamed, Shang-Wen Li, Alan W Black, Gopala K. Anumanchipalli ICASSP 2024 paper code
	Self-Supervised Models of Speech Infer Universal Articulatory Kinematics Cheol Jun Cho, Abdelrahman Mohamed, Alan W Black, Gopala K. Anumanchipalli ICASSP 2024 paper
	Unconstrained Dysfluency Modeling for Dysfluent Speech Transcription and Detection Jiachen Lian, Carly Feng, Naasir Farooqi, Steve Li, Anshul Kashyap, Cheol Jun Cho, Peter Wu, Robbie Netzorg, Tingle Li, Gopala K. Anumanchipalli ASRU 2023 paper
	A variational autoencoder provides novel, data-driven features that explain functional brain representations in a naturalistic navigation task Cheol Jun Cho, Tianjiao Zhang, Jack L. Gallant VSS 2023 paper
	Neural Latent Aligner: Cross-trial Alignment for Learning Representations of Complex, Naturalistic Neural Data Cheol Jun Cho, Edward F, Chang, Gopala K. Anumanchipalli ICML 2023 paper
	Speaker-Independent Acoustic-to-Articulatory Speech Inversion Peter Wu, Li-Wei Chen, Cheol Jun Cho, Shinji Watanabe, Louis Goldstein, Alan W Black, Gopala K. Anumanchipalli ICASSP 2023 paper
	Evidence of Vocal Tract Articulation in Self-Supervised Learning of Speech Cheol Jun Cho, Peter Wu, Abdelrahman Mohamed, Gopala K. Anumanchipalli ICASSP 2023 paper
	Cross-trial alignment reveals a low-dimensional cortical manifold of naturalistic speech production Cheol Jun Cho, Edward F. Chang, Gopala K. Anumanchipalli COSYNE 2023
	A bird’s-eye view of brain activity in socially interacting mice through mobile edge computing (MEC) Jisoo Kim, Chaewoo Kim, Hio-Been Han, Cheol Jun Cho, Wooseob Yeom, Sung Q. Lee, Jee Hyun Choi Science Advances 2020 paper

Template from Jon Barron's website.