Chenhui Xu

About Me

Welcome to Chenhui Xu’s home page.

I am now a first-year doctoral student in X-Lab of Department of Computer Science and Engineering at Univeristy at Buffalo. Prior to this, I spent two years in IF Lab of Department of Electrical and Computer Engineering at Geroge Mason University under the guidance of Prof. Xiang Chen. I received my Bachelor’s degree in Statistics from University of Science and Technology of China.

I am advised by Prof. Jinjun Xiong at University at Buffalo and co-advised by Prof. Xiang Chen at Peking University.

My current research interests include machine learning theory, backbone neural networks in computer vision, out-of-distribution detection. In backbone networks, I am now working on high-order neural networks and the inner product of feature space; I am also working on machine learning theory of language models. At the same time, I am actively studying quantum computing and attempting to get some inspiration from it.

News

• 02/2025: One collaborative paper is accepted by DAC 2025.
• 01/2025: One collaborative paper is accepted by ICLR 2025.
• 09/2024: One paper is accepted by NeurIPS 2024.
• 05/2024: One paper on Out-of-Distribution Detection is accepted by ICML 2024.
• 01/2024: I will join University at Buffalo to continue my Ph.D. career under the guidance of Prof. Jinjun Xiong.
• 10/2023: One paper is accepted by ASP-DAC 2024 and received Best Paper Nomination.
• 10/2022: Serve as session chair of IEEE Cloud Summit.
• 07/2022: I left USTC and will join George Mason University (GMU) to pursue a Ph.D. degree under guidance of Dr. Xiang Chen.
• 06/2021: I graduated and obtained my bachelor’s degree from University of Science and Technology of China.

Publications

• [DAC 2025] Dancheng Liu, Chenhui Xu, Jiajie Li, Amir Nassereldine, Jinjun Xiong. Ensembler: Protect Collaborative Inference Privacy from Model Inversion Attack via Selective Ensemble, in Design Automation Conference, 2025.
• [ICLR 2025] Jiajie Li, Brian R Quaranto, Chenhui Xu, Ishan Mishra, Ruiyang Qin, Dancheng Liu, Peter C W Kim, Jinjun Xiong. Recognize Any Surgical Object: Unleashing the Power of Weakly-Supervised Data, in International Conference on Learning Representations, 2025. (Spotlight. 5.1% out of all Submissions )
• [NeurIPS 2024] Chenhui Xu, Fuxun Yu, Maoliang Li, Zihao Zheng, Zirui Xu, Jinjun Xiong, and Xiang Chen. Infinite-Dimensional Feature Interaction, in Annual Conference on Neural Information Processing Systems, 2024.
• [ICML 2024] Chenhui Xu, Fuxun Yu, Zirui Xu, Nathan Inkawhich, and Xiang Chen. Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble, In International Conference on Machine Learning, 2024.
• [ASP-DAC 2024] Chenhui Xu, Fuxun Yu, Zirui Xu, Chenchen Liu, Jinjun Xiong, and Xiang Chen. QuadraNet: Improving High-Order Neural Interaction Efficiency with Hardware-Aware Quadratic Neural Networks, Asia and South Pacific design automation conference, IEEE 2024. (Best Paper Nomination. 10 out of 482 Submissions)

Preprints

• [arxiv 2025] Chenhui Xu, Dancheng Liu, Yuting Hu, Jiajie Li, Ruiyang Qin, Qingxiao Zheng, Jinjun Xiong. Sub-Sequential Physics-Informed Learning with State Space Model, arXiv preprint arXiv:2502.00318, 2025.
• [arxiv 2024] Ruiyang Qin, Dancheng Liu, Gelei Xu, Zheyu Yan, Chenhui Xu, Yuting Hu, X Sharon Hu, Jinjun Xiong, Yiyu Shi. Tiny-Align: Bridging Automatic Speech Recognition and Large Language Model on the Edge, arXiv preprint arXiv:2411.13766, 2024.
• [arxiv 2024] Ruiyang Qin, Dancheng Liu, Chenhui Xu, Zheyu Yan, Zhaoxuan Tan, Zixuan Pan, Zhenge Jia, Amir Nassereldine, Jiajie Li, Meng Jiang, Ahmed Abbasi, Jinjun Xiong, Yiyu Shi. Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices, arXiv preprint arXiv:2406.03777, 2024.
• [arxiv 2024] Amir Nassereldine, Dancheng Liu, Chenhui Xu, Jinjun Xiong. PI-Whisper: An Adaptive and Incremental ASR Framework for Diverse and Evolving Speaker Characteristics, arXiv preprint arXiv:2406.15668, 2024.
• [arxiv 2024] Dancheng Liu, Amir Nassereldine, Ziming Yang, Chenhui Xu, Yuting Hu, Jiajie Li, Utkarsh Kumar, Changjae Lee, Jinjun Xiong. Large Language Models have Intrinsic Self-Correction Ability, arXiv preprint arXiv:2406.15673, 2024.
• [arxiv 2024] Chenhui Xu, Xinyao Wang, Fuxun Yu, Jinjun Xiong, Xiang Chen. QuadraNet V2: Efficient and Sustainable Training of High-Order Neural Networks with Quadratic Adaptation, arXiv preprint arXiv:2405.03192, 2024.

Services

• Reviewer, International Conference on Machine Learning (ICML), 2025
• Reviewer, International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
• Reviewer, International Conference on Learning Representation (ICLR), 2025
• Reviewer, NeurIPS Workshop on MATH-AI, 2024
• Session Chair, IEEE Cloud Summit, 2022,2023
• Publication Committee, International Green and Sustainable Computing Conference, 2022, 2023

Contact Information

Davis Hall, Room 341

Computer Science & Engineering Department

University at Buffalo

Buffalo, NY, USA 14260

Email: cxu26@buffalo.edu

Phone: +1(703)973–0703