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Xuan Shen Cornell Tech, Roosevelt Island, NY
I obtained my PhD degree in ECE Department of Northeastern University at Boston in August 2025, advised by Prof. Yanzhi Wang . Previously, I received my M.S. degree at Northeastern University in 2020 and my B.S. degree at Nanjing University of Science and Technology in 2018.
My research interests center on efficient deep learning, with a particular focus on optimizing large foundation models and diffusion models for text and visual generation. I emphasize scalability, latency reduction, and deployment efficiency across a wide range of hardware platforms, including GPUs, mobile devices, FPGAs, and ASICs.
I am currently a Postdoctoral Associate in the Department of Electrical and Computer Engineering at Cornell Tech , Cornell University, where I work with Prof. Tianyi Chen on developing efficient AI models tailored for analog computing devices.
Nov 05, 2025 Got one paper accepted in AAAI 2026 AI for Social Impact Track. Aug 14, 2025 Ph.D. Defense Completed! Jun 30, 2025 Got one paper accepted in ICCAD 2025. Mar 06, 2025 Our paper accepted in ICLR 2025 SCI-FM Workshop. Feb 26, 2025 Got one paper accepted in CVPR 2025. Feb 02, 2025 Release efficient reasoning work with paper and code . Jan 23, 2025 Release the code of LazyDiT . Jan 22, 2025 Got one paper accepted in ICLR 2025. Dec 09, 2024 Got Adobe Reward: 2024 Key Innovations (Tech Transfer Small LLM on Acrobat). Dec 09, 2024 Got three papers accepted in AAAI 2025. Nov 19, 2024 Multimodal Opioid Benchmark released on HuggingFace: opioidarchive/oida-qa . Oct 30, 2024 Our paper about PTQ of LLMs on Mobile and FPGA has been accepted to TCAD. Sep 25, 2024 Got two papers accepted in NeurIPS 2024.
OIDA-QA: A Multimodal Benchmark for Analyzing the Opioid Industry Documents Archive
Xuan Shen , Brian Wingenroth, Zichao Wang, Jason Kuen, Wanrong Zhu, Ruiyi Zhang, Yiwei Wang, Lichun Ma, Anqi Liu, Hongfu Liu, Tong Sun, Kevin S. Hawkins, Kate Tasker, G. Caleb Alexander, and Jiuxiang Gu†
Association for the Advancement of Artificial Intelligence, Artificial Intelligence for Social Impact , 2026
Squat: Quant Small Language Models on the Edge
Xuan Shen , Dong Peiyan, Zhenglun Kong, Yifan Gong, Changdi Yang, Zhaoyang Han, Yanyue Xie, Lei Lu, Cheng Lyu, Chao Wu, Yanzhi Wang† , and Pu Zhao†
International Conference on Computer-Aided Design , 2025
QuartDepth: Post-Training Quantization for Real-Time Depth Estimation on the Edge
Xuan Shen , Weize Ma, Jing Liu, Changdi Yang, Rui Ding, Quanyi Wang, Henghui Ding, Wei Niu, Yanzhi Wang, Pu Zhao† , Jun Lin† , and Jiuxiang Gu†
Conference on Computer Vision and Pattern Recognition , 2025
Sparse Learning for State Space Models on Mobile
Xuan Shen* , Hangyu Zheng* , Yifan Gong, Zhenglun Kong, Changdi Yang, Zheng Zhan, Yushu Wu, Xue Lin, Yanzhi Wang, Pu Zhao, and Wei Niu†
International Conference on Learning Representations , 2025
Numerical Pruning for Efficient Autoregressive Models
Xuan Shen , Zhao Song, Yufa Zhou, Bo Chen, Jing Liu, Ruiyi Zhang, Ryan A Rossi, Hao Tan, Tong Yu, Xiang Chen, Yufan Zhou, Tong Sun, Pu Zhao, Yanzhi Wang† , and Jiuxiang Gu†
Association for the Advancement of Artificial Intelligence , 2025
LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers
Xuan Shen , Zhao Song, Yufa Zhou, Bo Chen, Yanyu Li, Yifan Gong, Kai Zhang, Hao Tan, Jason Kuen, Henghui Ding, Zhihao Shu, Wei Niu, Pu Zhao, Yanzhi Wang† , and Jiuxiang Gu†
Association for the Advancement of Artificial Intelligence , 2025
Search for Efficient Large Language Models
Xuan Shen , Pu Zhao, Yifan Gong, Zhenglun Kong, Zheng Zhan, Yushu Wu, Ming Lin, Chao Wu, Xue Lin, and Yanzhi Wang†
Conference on Neural Information Processing Systems , 2024
HotaQ: Hardware Oriented Token Adaptive Quantization for Large Language Models
Xuan Shen , Zhaoyang Han, Lei Lu, Zhenglun Kong, Peiyan Dong, Zhengang Li, Yanyue Xie, Chao Wu, Miriam Leeser, Pu Zhao, Xue Lin, and Yanzhi Wang†
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , 2024
Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge
Xuan Shen* , Peiyan Dong* , Lei Lu, Zhenglun Kong, Zhengang Li, Ming Lin, Chao Wu, and Yanzhi Wang†
Association for the Advancement of Artificial Intelligence , 2024
DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network
Xuan Shen* , Yaohua Wang* , Ming Lin, Yilun Huang, Hao Tang, Xiuyu Sun, and Yanzhi Wang†
Conference on Computer Vision and Pattern Recognition , 2023
Data Level Lottery Ticket Hypothesis for Vision Transformers
Xuan Shen , Zhenglun Kong, Minghai Qin, Peiyan Dong, Geng Yuan, Xin Meng, Hao Tang, Xiaolong Ma, and Yanzhi Wang†
International Joint Conference on Artificial Intelligence , 2023
Best way to reach me is via e-mail.