CV

Education

• Ph.D in Electrical Engineering, University of Arkansas, 2023
• B.S. in Electronic Engineering, Tsinghua University, 2017

Work experience

• August 2025 - Now: Manager in E Source - Grid Engineering and Interconnection.
• August 2024 - August 2025: Power system engineer in CF Power Ltd.
• August 2015 - July 2023: Graduate Assistant in University of Arkansas under:
  • Cybersecurity Center for Secure Evolvable Energy Delivery Systems (SEEDS) [Github]
  • Center for Infrastructure Trustworthiness in Energy Systems (CITES) [Github]
  • Supervisor: Jingxian Wu

Skills

• Engineering Software
  • PSSE
  • TARA
  • PSAT/TSAT
  • Aspen OneLiner
• Programming
  • Python
  • MATLAB
• Statistics
  • Time Series Analysis
  • Detection and estimation
• Reinforcement Learning
  • Markov Decision Processes
  • Tensorflow
  • PyTorch

Publications

Optimum Scheduling of Truck-Based Mobile Energy Couriers (MEC) Using Deep Deterministic Policy Gradient

Y. Li, J. Wu and Y. Pan, “Optimum Scheduling of Truck-Based Mobile Energy Couriers (MEC) Using Deep Deterministic Policy Gradient,” in Intelligent and Converged Networks, vol. 6, no. 3, pp. 195-208, September 2025, doi: 10.23919/ICN.2025.0016

Deep Reinforcement Learning for Online Scheduling of Photovoltaic Systems with Battery Energy Storage Systems

Y. Li, J. Wu and Y. Pan, "Deep Reinforcement Learning for Online Scheduling of Photovoltaic Systems with Battery Energy Storage Systems," in Intelligent and Converged Networks, vol. 5, no. 1, pp. 28-41, March 2024, doi: 10.23919/ICN.2024.0003

Low Latency Attack Detection with Dynamic Watermarking for Grid-Connected Photovoltaic Systems

Y. Li, N. Lin, J. Wu, Y. Pan and Y. Zhao, "Low Latency Attack Detection with Dynamic Watermarking for Grid-Connected Photovoltaic Systems," in IEEE Journal of Emerging and Selected Topics in Industrial Electronics, doi: 10.1109/JESTIE.2023.3327051

Low Latency Cyberattack Detection in Smart Grids with Deep Reinforcement Learning

Y. Li and J. Wu, “Low latency cyberattack detection in smart grids with deep reinforcement learning,” International Journal of Electrical Power & Energy Systems, vol. 142, p. 108265, 2022.

Multi-user Multi-channel Computation Offloading and Resource Allocation for Mobile Edge Computing

S. Nath, Y. Li, J. Wu, and P. Fan, “Multi-user multi-channel computation offloading and resource allocation for mobile edge computing,” in ICC 2020-2020 IEEE International Conference on Communications (ICC). IEEE, 2020, pp. 1–6.

Optimum Integration of Solar Energy With Battery Energy Storage Systems

Y. Li and J. Wu, “Optimum integration of solar energy with battery energy storage systems,” IEEE Transactions on Engineering Management, 2020.

Optimum Design of Battery-Assisted Photo-Voltaic Energy System for a Commercial Application

Y. Li and J. Wu, “Optimum design of battery-assisted photo-voltaic energy system for a commercial application,” in Power & Energy Society General Meeting (PESGM). IEEE, 2019.

Other Scholarly Outputs

• Energy Storage & Stationary Battery Committee Poster Session for IEEE Power & Energy Society General Meeting (PESGM) 2019.

Teaching

• Teaching Assistant for ELEG 5693 Wireless Communication, 2020 Spring
• Teaching Assistant for ELEG 4603/5173L Digital Signal Processing, 2021 Spring
• Teaching Assistant for ELEG 3124 Systems and Signals, 2021 Fall

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