About
I am an Associate Editor at Nature Energy (Springer Nature), which I joined in July 2026. I am based in the Shanghai office (see the Nature Energy editors page). My editorial interests build on my research background in artificial intelligence for energy systems, covering digital twins, virtual power plants, smart energy systems, and carbon accounting.
Before joining Springer Nature, I was a Postdoctoral Research Associate in the Department of Engineering at Durham University (2023 – 2026), where I contributed to two major EPSRC programmes: VPP-WARD (EP/Y005376/1), leading day-to-day digital twin modelling and risk-aware dispatch for resilient, decarbonised virtual power plants, and CHEDDAR (EP/X040518/1, EP/Y037421/1), working on communication-aware digital twin architectures for real-time monitoring and control of energy networks, in collaboration with industrial partners including Siemens, National Grid, Equinor, and Northern Powergrid. I have published 17+ peer-reviewed papers in venues including Applied Energy, IEEE Transactions on Industrial Informatics, Engineering Applications of Artificial Intelligence, and Scientific Data, including a 2024 ECE Highly Cited Article and a Best Paper Award (IEEE CIEEC 2022). My MSCA Postdoctoral Fellowship proposal was awarded the European Commission's Seal of Excellence.
I received my PhD in Computer and Information Engineering from The Chinese University of Hong Kong in 2023, with a thesis on data-driven high-resolution carbon emission measurement, and my BEng in Electrical Engineering and Automation from North China Electric Power University. I am an Associate Fellow of the Higher Education Academy (AFHEA), with seven years of teaching experience across the UK and China, and I initiated and led the Women in Engineering Society (WES) research programme at Durham.
Selected Publications
View All →Bi-Level Low-Carbon Scheduling of Active Distribution Networks with Multiple Technical Virtual Power Plants in the Integrated Electricity and Carbon Markets
Jinjie Liu, Jiaqi Ruan, Huijun Tang, Behzad Kazemtabrizi, Hailiang Du, Peter C. Matthews, Hongjian Sun
Proc. IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)
Bi-level low-carbon scheduling of active distribution networks with multiple technical VPPs in integrated electricity and carbon markets, developed within EPSRC VPP-WARD.
Real-time industrial carbon emission estimation with deep learning-based device recognition and incomplete smart meter data
Jinjie Liu, Guolong Liu, Huan Zhao, Junhua Zhao, Jing Qiu, Zhao Yang Dong
Engineering Applications of Artificial Intelligence
Deep-learning device recognition that keeps real-time industrial carbon emission estimation accurate even when smart-meter data are incomplete (JCR Q1).
Real-time emission and cost estimation based on unit-level dynamic carbon emission factor
Jinjie Liu, Huan Zhao, Shuyi Wang, Guolong Liu, Junhua Zhao, Zhao Yang Dong
Energy Conversion and Economics
Piecewise unit-level dynamic emission factor model for real-time emission and cost estimation; recognised as a 2024 Energy Conversion and Economics Highly Cited Article.
EWELD: A Large-Scale Industrial and Commercial Load Dataset in Extreme Weather Events
Guolong Liu, Jinjie Liu, Yan Bai, Chengwei Wang, Haosheng Wang, Huan Zhao, Gaoqi Liang, Junhua Zhao, Jing Qiu
Scientific Data
Co-first-author Scientific Data paper releasing EWELD, a six-year 15-minute-resolution load dataset of 386 industrial and commercial users under extreme weather events (JCR Q1).
Bidding Behavior Analysis in Joint Electricity and Carbon Market by Hybrid Experimental Learning
Jianmin Ye, Yarong Hu, Jinjie Liu, Wenxuan Liu, Gaoqi Liang
2022 IEEE 5th International Electrical and Energy Conference (CIEEC)
Hybrid experimental learning analysis of bidding behaviour in joint electricity and carbon markets; CIEEC 2022 Best Paper Award.