Chenewi Xu is a master’s student in Computer Science at Northwestern University with a strong research background and a keen interest in developing machine learning tools for real-world applications. His current research focus revolves around Tabular Learning, where he has achieved a significant milestone by creating a State-Of-The-Art model, soon to be detailed in a forthcoming paper. In addition to his academic pursuits, Chenewi is actively involved in research at Fermilab, applying Reinforcement Learning to optimize the Mu2e simulator’s spill regulation. Beyond research, he enjoys cooking and maintains a strong commitment to fitness.

Selected Publications

BISHOP: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model.
Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu, Weijian Li, Ammar Gilani, Hsi-Sheng Goan, Han Liu
ICML 2024 Paper [Link]

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e.
Chenwei Xu, Jerry Yao-Chieh Hu, et al.
NeurIPS 2023 Workshop Paper [Link]

On Sparse Modern Hopfield Model.
Jerry Yao-Chieh Hu, Donglin Yang, Dennis Wu, Chenwei Xu, Bo-Yu Chen, and Han Liu.
NeurIPS 2023 Poster Paper [Link]

Feature Programming for Multivariate Time Series Prediction.
Alex Reneau, Jerry Yao-Chieh Hu, Chenwei Xu, Weijian Li, Ammar Gilani, and Han Liu.
ICML 2023 Poster Paper [Link]

Open-Ended Multi-Modal Relational Reasoning for Video Question Answering.
Haozheng Luo, Qin Ruiyang, Chenwei Xu, Guo Ye and Zening Luo.
IEEE RO-MAN 2023 Poster Paper [Link]

Using deep learning for the automated identification of cone and rod photoreceptors from adaptive optics imaging of the human retina.
Mengxi Zhou, Nathan Doble, Stacey S. Choi, Tianyu Jin, Chenwei Xu, Srinivasan Parthasarathy, and Rajiv Ramnath.
Biomedical Optics Express [Link]