About Me
PhD candidate, Electrical and Computer Engineering, USC (advisor Richard M. Leahy)
I build machine learning models that compress high-dimensional neural/behavioral signals into compact, transferable embeddings.
Previously, I earned my M.Eng. degree in ECE from Cornell and a B.Eng. degree in Communication Engineering from Soochow University.
Contact: yijunl AT usc DOT edu
Selected Projects
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HSTU-BLaIR: Lightweight Contrastive Text Embedding for Generative Recommender
Workshop on Large Language Models for E-Commerce, KDD 2025 [pdf][code] -
sEEG-based Encoding for Sentence Retrieval: A Contrastive Learning Approach to Brain-Language Alignment
Workshop on What is Next in Multimodal Foundation Models, CVPR 2025 [pdf] -
Untamed: Unconstrained Tensor Decomposition and Graph Node Embedding for Cortical Parcellation
Y. Liu, J. Li, J.L. Wisnowski, R.M. Leahy.
bioRxiv 2025 [project page] • expanded from oral at BioKDD 2023 [slides] -
Identification of Overlapping and Interacting Networks Reveals Intrinsic Spatiotemporal Organization of the Human Brain
J. Li, Y. Liu, J.L. Wisnowski, R.M. Leahy.
Neuroimage, 2023 [pdf] -
A Hybrid High-Resolution Anatomical MRI Atlas with Sub-Parcellation of Cortical Gyri using resting fMRI
A.A. Joshi, S. Choi, Y. Liu, M. Chong, G. Sonkar, J. Gonzalez-Martinez, D. Nair, J.L. Wisnowski, J.P. Haldar, D.W. Shattuck, H. Damasio, R.M. Leahy.
Journal of neuroscience methods, 2022 [pdf] -
Brain Network Decomposition for Naturalistic Stimulus Paradigm
Y. Liu, J. Li, J.L. Wisnowski, A.A. Joshi, R.M. Leahy.
Organization for Human Brain Mapping Annual Meeting (OHBM), 2021 [pdf] -
Pancreas Segmentation in Abdominal CT Scans
Y. Liu, S. Liu.
International Symposium on Biomedical Imaging (ISBI), 2018 [pdf][code]