研究方向：

1. 电力人工智能——数智驱动的电力设备状态评估+；
2. 新型电工材料绝缘老化放电机理。

主持或参与科研项目：

1. 2030国家重大专项：超高压电力变压器用植物基绝缘油研制关键技术；
2. 博士后面上基金：高压电缆缓冲层复合材料电学特性研究；
3. 企业横向课题：基于非侵入式信号注入的输电电缆接地回路中潜在缺陷的带电检测及危险评估方法研究、基于短时交流电压激励的10kV配电电缆绝缘测试及高阻性故障预定位技术研究、电缆局部放电精确定位技术研究。

代表性工作：

1. Yan Y, Trinchero R, Stievano I S, and Li H J, "Implementation of Adaptive Partial Discharge Denoising in Resource-Limited Embedded Systems via Efficient Time-Frequency Matrix Factorization," in IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-13, 2024. 
2. Yan Y, Zhao Y, He W, et al. On-line Partial Discharge Localization of 10-kV Covered Conductor Lines[J]. IEEE Transactions on Power Delivery, vol. 38, no. 3, pp. 1688-1698, June 2023. 
3. Yan Y, Trinchero R, Stievano I S, et al. An automatic tool for partial discharge de-noising via short-time Fourier transform and matrix factorization[J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 1-12. 
4. Yan Y, Tao J, Trinchero R, et al. A Compact Detector for Flexible Partial Discharge Monitoring of 10-kV overhead Covered Conductor Lines[J]. IEEE Transactions on Power Delivery, 2022, 37(6): 5492-5495. 
5. Yan Y, Ren S, Lu Y, et al. Efficient and low-cost PD monitoring and locating system for MV switchgears using TEV detectors[J]. IEEE Transactions on Power Delivery, 2021, 36(5): 3266-3269. 
6. Yan Y, Zhao Y, Zhao K, et al. A high‐efficiency portable system for insulation condition assessment of wind farm inter‐array cables with double‐sided partial discharge detection and localisation[J]. IET Generation, Transmission & Distribution, 2023, 17(11): 2523-2534.