教育背景

博士，图像与信号处理，法国国立应用科学学院 (INSA-Rennes), 2014年

硕士，通信与信息系统，山东大学，2010年

学士，电子信息工程，山东大学，2007年

研究兴趣

研究领域涵盖信号处理与机器学习，近期尤其关注深度神经网络的结构可解释性与轻量化设计，通过融合压缩感知的稀疏约束机制、随机投影的降维优化思想，以及统计学习的理论验证方法，构建理论透明且计算高效的模型体系。

招生启事:  诚邀对机器学习基础原理及应用感兴趣的同学！联系方式: wzlu@sdu.edu.cn

近期论文

• Binary and Ternary Quantization Can Enhance Feature Discrimination

  Weizhi Lu, Mingrui Chen, and Weiyu Li. 

  arXiv, 2025.

• The Sparse Matrix-Based Random Projection: A Study of Binary and Ternary Quantization

  Weizhi Lu, Zhongzheng Li and Mingrui Chen and Weiyu Li

  Transactions on Machine Learning Research (TMLR), 2025.

  
  

(1) 鲁威志.Binary Matrices for Compressed Sensing.IEEE Transactions on Signal Processing.2017

(2) 杨硕.Explicit-to-Implicit Robot Imitation Learning by Exploring Visual Content Change.《IEEE-ASME TRANSACTIONS ON MECHATRONICS》.2022

(3) 李蔚郁.Collaborative Dictionary Learning for Compressed Sensing.IEEE Transactions on Industrial Informatics.2024

(4) 鲁威志.Cascaded Compressed Sensing Networks.IEEE Signal Processing Letters.2023 (30):364

(5) 陈明锐.Deep learning to ternary hash codes by continuation.ELECTRONICS LETTERS.2021,57 (24):925

(6) 饶振环.Visual Navigation With Multiple Goals Based on Deep Reinforcement Learning.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS.2021,32 (12):5445

(7) 张伟.Feature Aggregation With Reinforcement Learning for Video-Based Person Re-Identification.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS.2019,30 (12):3847

(8) 张伟.A Multi-Scale Spatial-Temporal Attention Model for Person Re-Identification in Videos.IEEE Transactions on Image Processing.2019,29 :3365

(9) 张伟.Learning Intra-video Difference for Person Re-identification.IEEE Transactions on Circuits and Systems for Video Technology.2018

(10) 鲁威志.Compressed sensing performance of random Bernoulli matrices with high compression ratio..IEEE Signal Processing Letters.2015,22 :1074

(11) Wang, Tingwei.Action recognition using dynamic hierarchical trees.Visual Communication and Image Representation.2019,61 :315

(12) 鲁威志.Expander Recovery Performance of Bipartite Graphs with Girth Greater than 4. IEEE Transactions on Signal and Information Processing over Networks.2019

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1. 概率统计

2. 概率统计

3. 概率统计

4. 复变函数与拉氏变换