Dr. Jin Zheng

Dr. She has been a Lecturer in Data Science since 2021. Before that, she worked as a quantitative researcher in London for about three years. She leads a wide range of research in machine learning, deep learning, data science, natural language processing, and quantitative methods in finance and energy economics. Additionally, she has an interest in sports prediction.

Professional Experience

Program Director of MSc Financial Technology with Data Science: University of Bristol (2024-present)
Lecturer: University of Bristol (2021-present)
Quantitative Researcher: White Swan Data Ltd (2018-2021)
Research Fellow: University of Nevada Las Vegas (2016-2017)

Educational Background

Ph.D.: Department of Mathematics, University of Liverpool (2011-2015)
BSc: Department of Mathematics, University of Liverpool/Xi’an Jiaotong-Liverpool University (2007-2011)

Selected Recent Publications

Yang, J., Wen, Y. & Zheng, J., 8 September 2025, (Accepted/In press) Prediction of Homeowners' Renovation Tendency Based on Multi-Head Attention Mechanism, Energy & Buildings.

Pei, Y., Zheng J. & Cartlidge, J., 29 July 2025, (Accepted/In press) DGRCL: A Dynamic Contrastive Graph Learning Framework for Modeling Stock Market Evolution, Lecture Notes in Artificial Intelligence.

Liu, R., Zheng, J. & Cartlidge, J., 29 June 2025, (Accepted/In press) Deep Reinforcement Learning for Optimal Asset Allocation Using DDPG with TiDE, MAS 2025

Hua, H., Zou, Y., Chen, X., Yu, K., Gan, L., Lei, S., Gertrudes, J. B., Zheng, J. & Sidorov, D., 25 August, 2025, (Accepted/In press) Dynamic Network Partitioning for A Large-scale Microgrid Cluster, IEEE Transactions on Smart Grid.

Zhang P., Harris R.D.F., Zheng J., 2025, GNN-based social media sentiment analysis for stock market forecasting and trading, Expert Systems with Applications, Volume 291, 128425.

Zhang Z., Hua H., Chen X., Shao J., Zheng J., Wang B., Gan L., Yu K., 2025, Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process, 2025, 21st International Conference on the European Energy Market (EEM), pages 1-6.

Pei Y., Zheng J., Cartlidge J., 2025, Dynamic Graph Representation with Contrastive Learning for Financial Market Prediction: Integrating Temporal Evolution and Static Relations, in: 17th International Conference on Agents and Artificial Intelligence (ICAART), ACM, Vol. 2, pp. 298-309. Best Paper Award

Wei W. and Zheng J., 2024, Option Data Fusion Incorporating Moment-Matching and Dynamic-Matching Simulations, 2024 IEEE International Conference on e-Business Engineering (ICEBE), Shanghai, China, pp. 106-111.

You Z., Zhang P., Zheng J. and Cartlidge J., 2024, Multi-Relational Graph Diffusion Neural Network with Parallel Retention for Stock Trends Classification, ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Republic of Korea, pp. 6545-6549.

Jin, Q., Zheng, J. (2024). Sentiment Analysis for Predicting the Variation Trend of Stocks: A Case Study of Vanke Co., Ltd. In: Arai, K. (eds) Intelligent Computing. SAI 2024. Lecture Notes in Networks and Systems, vol 1017.

Recruitment

She is looking for prospective PhD students, visiting students, and interns for the 2026 entry. If you are interested in undertaking research projects in the areas of financial technology (tech focused), energy economics, or more generally in data science and machine learning, please feel free to contact at jin.zheng@bristol.ac.uk.