师资队伍

王浩

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个人详情

个人详情

王浩

办公室:我校南校区致信楼N306

Email: haowang@szu.edu.cn


简介

王浩,男,19901月,博士,澳门3044永利助理教授。主要研究领域为机器学习、神经网络、深度学习、大数据挖掘。2018年于香港城市大学电子工程专业获得博士学位。2018.10-2019.04担任香港城市大学助理研究员,2019.04-2021.03于腾讯公司从事基于机器学习的金融数据挖掘算法研究。目前共发表SCIEI论文余篇,其中多篇发表在IEEE TNNLS等机器学习、神经网络算法领域顶级期刊上,并多次在国际会议口头宣讲论文。目前主持国家自然科学基金项目1项,深圳市高端人才科研启动项目1项,同时被评为深圳市海外高层次人才(孔雀计划C类)。担任多个相关领域顶级期刊审稿人。


工作经历

2021.4—现在 我校担任助理教授

2019.4—2021.3  腾讯(财付通支付科技有限公司)担任高级应用研究员

2018.10—2019.4香港城市大学担任助理研究员


教育背景

2015.9—2019.2 香港城市大学 电子工程专业 博士(导师:LEUNG, Chi-Sing

2012.9—2015.6 郑州大学 物理电子学 硕士

2008.9—2012.6 郑州大学 电子信息与科学技术 本科


研究方向

1. 基于模拟神经网络的优化问题求解与应用;

2. 复杂噪声环境下的神经网络模型压缩、训练和节点选择;

3. 股票期货走势预测(时间序列预测);

4.大数据挖掘;

5. 深度学习模型设计与理论研究


主持项目

1. 国家自然科学基金——青年科学基金项目,2023.012025.12,主持,30

2. 新引进高端人才科研启动项目,2021.062024.12,主持,270万,在研

3.高水平二期,主持,在研



部分奖项

2019-2024深圳市高层次人才计划(孔雀计划C类人才)

2020  腾讯公司内部个人奖

2015-2018 香港政府UGC奖学金


近期录用期刊:

1. Hao Wang, et al. "A Globally Stable LPNN model for Sparse Approximation." accepted by IEEE Transactions on Neural Networks and Learning Systems. 2021.10. SCI收录; JCR分区Q1; 影响因子10.451;

2. Zhanglei Shi, Hao Wang, et al. " Constrained Center Loss for Convolutional Neural Networks." Accepted by IEEE Transactions on Neural Networks and Learning Systems, 2021.07. SCI收录; JCR分区Q1; 影响因子10.451;

3. Zhanglei Shi, Hao Wang (co-author), et al. “Robust Ellipse Fitting based on Lagrange Programming Neural Network and Locally Competitive Algorithm.” Neurocomputing (2020): Volume 399, pp. 399-413. SCI收录; JCR分区Q1影响因子4.072; DOI: 10.1016/j.neucom.2020.02.100.

4. Zhanglei Shi, Hao Wang (co-author), et al. “Robust MIMO Radar Target Localization based on Lagrange Programming Neural Network.” Signal Processing (2020): 107574. SCI收录JCR分区Q1影响因子4.086; DOI: 10.1109/ACCESS.2019.2945807.

5. Hao Wang, et al. "An L0-Norm-Based Centers Selection for Failure Tolerant RBF Networks." IEEE Access (2019): Volume 7, pp. 151902-151914. SCI收录JCR分区Q1影响因子4.098; DOI:10.1016/j.sigpro.2020.107574.

6. Hao Wang, et al. "ADMM-Based Algorithm for Training Fault-Tolerant RBF Networks and Selecting Centers." IEEE Transactions on Neural Networks and Learning Systems (2018): Volume 29, Issue 8, pp. 3870-3878. SCI收录JCR分区Q1影响因子11.683; DOI: 10.1109/TNNLS.2017.2731319.

7. Hao Wang, et al. "Lagrange Programming Neural Network Approaches for Robust Time-of-Arrival Localization." Cognitive Computation (2018): Volume 10, Issue: 1, pp 23–34. SCI收录JCR分区Q1影响因子3.479; DOI: 10.1007/s12559-017-9495-z.

8. Hao Wang, et al. "An Analog Neural Network Approach for the Least Absolute Shrinkage and Selection Operator Problem." Neural Computing and Applications (2018): Volume 29, Issue 9, pp 389–400. SCI收录JCR分区Q1影响因子4.213; DOI: 10.1007/s00521-017-2863-5.


近期在投论文:

9. Hao Wang, et al. "ADMM-MCP Framework for Sparse Recovery with Global Convergence." Prepare for submitting to IEEE Transactions on Signal Processing. arXiv: https://arxiv.org/abs/1805.00681.

10. Ruibin Feng, Hao Wang, et al. "Lagrange Programming Neural Network for Compressive Sensing with Lp-norm-like Sparsity Measurement." Prepare for submitting to IEEE Transactions on Signal Processing.

11. Hao Wang, et al. "Lagrange Programming Neural Networks for Sparse Portfolio Design." Submitted to IEEE Transactions on Neural Networks and Learning Systems.


已录用会议:

1. Hao Wang, et al. "A Robust TOA Source Localization Algorithm Based on LPNN." International Conference on Neural Information Processing (2016): pp. 367-375. EI收录; DOI: 10.1007/978-3-319-46687-3_41.

2. Hao Wang, et al. "A Lagrange Programming Neural Network Approach for Robust Ellipse Fitting." International Conference on Neural Information Processing (2017): pp. 686-696. EI收录; DOI: 10.1007/978-3-319-70090-8_69.

3. Hao Wang, et al. "MCP Based Noise Resistant Algorithm for Training RBF Networks and Selecting Centers," International Conference on Neural Information Processing (2018), pp. 668-679. EI收录; DOI: 10.1007/978-3-030-04179-3_59.

4. Zhanglei Shi, Hao Wang, et al. “Constrained Center Loss for Image Classification”. International Conference on Neural Information Processing (2020), pp. 70-78. EI收录; DOI:10.1007/978-3-030-63823-8_9.


硕士研究生招生方向:

 104 澳门3044永利:

信息与通信工程,081000

  166 广东省数字创意技术工程实验室:

新一代电子信息技术,085401


长期招收神经网络、机器学习算法相关研究方向博士后,研究助理,有意者欢迎咨询。


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