Yijun Liu

About Me

I’m an Applied Scientist at Amazon Ads, currently working on agentic systems for advertising sales.

I received my Ph.D. in Electrical and Computer Engineering from the University of Southern California (advised by Richard M. Leahy), an M.Eng. degree from Cornell University, and a B.Eng. degree from Soochow University.

Contact: yijun DOT liu AT perfectroc DOT com

Selected Projects

• Untamed: Unconstrained Tensor Decomposition and Graph Node Embedding for Cortical Parcellation
  Y. Liu, J. Li, J.L. Wisnowski, R.M. Leahy.
  Human Brain Mapping, 2026 [project page]

• HSTU-BLaIR: Lightweight Contrastive Text Embedding for Generative Recommender
  Workshop on Large Language Models for E-Commerce, KDD 2025 [pdf][code] • Starred by HSTU author

• 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]

• 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]

Engineering Achievements & Contributions

• Bronze Medal (Top 8%), Optiver “Trading at the Close” price movement prediction competition, 2024
  Solo submission among 4,436 teams using LightGBM ensemble with lagged volatility and order book features.
  [certificate]

• Discovered and reported a bug in MATLAB’s silhouette function for clustering evaluation using the correlation metric.
  Identified output deviations from the documented formula and scikit-learn; confirmed by MathWorks and fixed in R2021b.
  [MathWorks confirmation email][Issue submitted]

• Reported and debated a behavioral mismatch in SciPy’s csgraph.laplacian for normalized Laplacians.
  Initiated discussion around handling of self-loops, leading to long-term reconsideration by core developers.
  [GitHub issue #14490]

• 2nd Place, Columbia Health Hackathon, 2018
  Team of 4 across 4 countries. Developed a Flask-based web app for pancreas segmentation using deep learning.
  [project link]

• Poster Session Winner (Bio-Signals Track), Cornell University ECE M.Eng. program, 2017
  Independent project on heart ventricle separation in low-dose CT scans.
  [annoucement]