Jun Woo Chung

I am a fourth year PhD candidate in the Computing and Information Sciences program at Rochester Institute of Technology (RIT), under supervision of Professor Weijie Zhao. My current research focuses on graph-based approximate nearest neighbor search methods and the security of gradient boosting decision tree models.

Previously, after graduating with a bachelor's and master's degree in physics from University of Cambridge, I worked for three years as a researcher at Silicon Display co. Ltd, a thin film transistor company in South Korea.

Publications/Patents

J. Chung, Y. Lao, and W. Zhao. Robust Watermarking on Gradient Boosting Decision Trees. Accepted to The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026).
Paper: J. Chung, L. Huawei, and W. Zhao. Locality-Sensitive Indexing for Graph-Based Approximate Nearest Neighbor Search. 48th International ACM SIGIR Conference (SIGIR 2025).
Paper: J. Chung, A. Sim, B. J. Quiter, Y.Wu, W. Zhao, and K. Wu. Preparing Spectral Data for Machine Learning: A Study of Geological Classification from Aerial Surveys. Machine Learning and the Physical Sciences Workshop at the 37th conference on Neural Information Processing Systems, December 16th 2023.
Paper: L. Huawei, J. Chung, Y. Lao, and W. Zhao. Machine Unlearning in Gradient Boosting Decision Trees. In Proceedings of the 29th AC SIGKDD Conference on Knowledge Discovery and Data Mining, Published August 6th 2023.
Patent: J. Jin, J. Yu, H. Jin, J. Chung and Y. Nam, Fingerprint recognition sensor and display device having the same, US10977475B2, Filed July 5th 2019, Issued April 13th 2021.

Skills

Programming: C++, R, Visual Basic, Python. Java and SQL in a pinch.
Computer aided design/engineering: TFT IC design (LayoutEditor), Circuit simulation (SPICE/SMARTSpice), Image analysis (ImageJ), Finite element analysis (COMSOL, Silvaco ATLAS)

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