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About 个人简介
I am an Associate Professor and Ph.D./Master's supervisor with the School of Artificial Intelligence at Anhui University, and a member of the Anhui Association for Artificial Intelligence. I received my bachelor's degree from Hefei University of Technology in 2016 and my Ph.D. from Beijing Jiaotong University in 2021. I joined Anhui University in the same year.
My research focuses on generative foundation model optimization, computer vision, neural network compression, and embedded AI systems and deployment, with an emphasis on hardware-software co-design for efficient deep learning under resource constraints.
我现为安徽大学人工智能学院副教授、博士生/硕士生导师,安徽省人工智能学会会员。2016 年于合肥工业大学获得学士学位,2021 年于北京交通大学获得博士学位,同年加入安徽大学人工智能学院。
我的研究聚焦生成式大模型优化、计算机视觉、神经网络模型压缩,以及嵌入式 AI 系统与部署,重点关注资源受限场景下深度学习模型从算法设计、优化到高效部署的软硬件协同方法。
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Research 研究方向
I study efficient and deployable artificial intelligence across model optimization, visual perception, compression, and hardware-aware deployment. 我围绕模型优化、视觉感知、模型压缩和硬件感知部署,研究高效且可落地的人工智能方法。
- 01 Generative foundation model optimization — GPT compression and deployment 生成式大模型优化——GPT 模型压缩与部署
- 02 Computer vision — visual perception for autonomous driving and industrial anomaly detection 计算机视觉——自动驾驶视觉感知、工业异常检测等
- 03 Neural network compression — quantization, pruning, distillation, and neural architecture search 神经网络模型压缩——量化、剪枝、蒸馏与神经网络架构搜索
- 04 Embedded AI systems and deployment — deep learning deployment on GPU, CPU, ASIC, and NPU platforms 嵌入式 AI 系统与部署——GPU、CPU、ASIC、NPU 深度学习算法部署
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Recent News 最新动态
Research milestones, publications, and academic updates. 研究进展、论文发表与学术动态。
GAZE and PEQuant were accepted by the ACM International Conference on Multimedia 2026. GAZE 与 PEQuant 两项工作被 ACM Multimedia 2026 接收。
Quantized Elastic Precision Transformers with one-shot calibration for multi-bit switching. 面向多比特切换、采用一次校准的弹性精度 Transformer 量化方法。
Training once for multi-bit quantization of neural networks. 一次训练即可支持多比特神经网络量化。