个人信息：

姓名：许芳源

职称：讲师

职务：

电话：

邮箱：fangyuanxu@ytu.edu.cn

办公地点：院馆214

教育背景：

2021.04-2024.03，名古屋大学，工学研究科，工学博士

2019.04-2021.03，名古屋大学，工学研究科，工学硕士

2013.09-2017.07，山东科技大学，机械电子工程学院，工学学士

工作履历：

2024.07-至今，烟台大学，机电汽车工程学院，讲师

研究方向：

信息物理系统，故障检测，图论，稀疏重建，多智能体控制，神经网络

科研项目：

1.Artificial Intelligence with Supervision from A Mathematical Model Research Project, Grant-in-Aid for Challenging Research (Exploratory), from the Ministry of Education, Culture, Sports, Science and Technology of Japan, 2019-2022,参与.

2.Diagnosis of Demand Response Implementation: The Challenge of 10x Performance and the Creation of On-Demand Information Acquisition Studies,Grant-in-Aid for Scientific Research (A), from the Ministry of Education, Culture, Sports, Science and Technology of Japan, 2021-2026,参与.

3.大规模需求响应中的异常检测技术，国家建设高水平大学公派研究生项目，2021-2024，主持.

研究成果：

一．学术论文

1.F. Xu, S. Azuma, K. Kobayashi, N. Yamaguchi, R. Ariizumi, and T. Asai:Default Detection in Demand Response Based on Block-Sparse Structure, International Journal of Electrical Power & Energy Systems, 2024.

2.F. Xu, S. Azuma, R. Ariizumi, and T. Asai: Performance Limitation of Group Testing in Network Failure Detection, IEEE Access, 2023.

3.F. Xu, R. Ariizumi, S. Azuma, and T. Asai: Tamper-Resistant Controller Using Neural Network and Time-Varying Quantization, Artificial Life and Robotics, 2020.

4.F. Xu, S. Azuma, K. Kobayashi, N. Yamaguchi, R. Ariizumi, and T. Asai: Detection of Defaulting Participants With Time-Varying Failure Rates in Demand Response, IFAC-PapersOnLine, 2020.

二．国际学会

1.F. Xu, S. Azuma, R. Ariizumi, and T. Asai: Minimum Number of Measurements in Enhanced Group Testing for Failure-edge Detection in Networks, 13th Asian Control Conference, 2022.

2.F. Xu, S. Azuma, K. Kobayashi, N. Yamaguchi, R. Ariizumi, and T. Asai: Diagnosis of Demand Response Based on Grouping Participants: A method to increase performance up to 20 times, 8 th Multi-symposium on Control Systems, 2021.

3.F. Xu, S. Azuma, K. Kobayashi, N. Yamaguchi, R. Ariizumi, and T. Asai: Detection of Defaulting Participants With Time-Varying Failure Rates in Demand Responses, 21st IFAC World Congress, 2020.

4.F. Xu, R. Ariizumi, S. Azuma, and T. Asai: Tamper-Resistant Controller Using Neural Network for Time-varying Quantized Control, SWARM2019, 2019.

三．获奖情况

1. 2022年日本电子情报通信学会优秀发表奖

2. 2021年名古屋大学博士研究助成金

3. 2020年服部国际奖学财团服部奖学金

4. 2020年日本电子情报通信学会优秀发表奖