Projects per year
Personal profile
Personal profile
Yang graduated with an MSc in Autonomous System and a PhD in Engineering from University of Exeter, UK. He worked at University of Manchester and University of Edinburgh on optimisation until moving to Bank of America Merrill Lynch to work on Artificial Intelligence model validation for financial forecasting. After working on Artificial Intelligence model development for UK industries at University of Sheffield, UK , he is now appointed senior associate professor at Xi’an Jiaotong-Liverpool University. Research interests are in artificial intelligence, statistical pattern recognition and optimisation. Particular current interests are in real time anomaly detection and forecasting for industry problems using advanced artificial intelligence techniques (e.g. deep learning, AI with big data, computer vision and explainable AI).
Welcome excellent students to apply for PhD studies in Artificial Intelligence (e.g., Computer Vision, Big Data and Deep Learning and Explainable AI) and anomaly detection for engineering and medical applications.
Research interests
Artificial Intelligence
Statistical Pattern Recognition
Optimisation
Teaching
- Python Programming
- Pattern Recognition (Module Leader)
Awards and honours
- The Excellent Presentation Winner for the 7th IEEE International Conference on Pattern Recognition and Artificial Intelligence (PRAI 2024).
- The Best Oral Presentation Winner for the 4th ACM International Joint Conference on Robotics and Artificial Intelligence (JCRAI 2024).
Education/Academic qualification
MSc, University of Exeter
PhD, University of Exeter
Person Types
- Staff
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Projects
- 0 Active
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A Fast Optimisation Using Advanced Artificial Intelligence Model for Fitness Estimation and Differential Evolution Optimisation
1/07/24 → 30/06/27
Project: Internal Research Project
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A Novel Decision Support System for Early Flood Warning Using Cellular Automata and Support Vector Machine
Liu, Y., Feb 2025, The 4th International Joint Conference on Robotics and Artificial Intelligence (JCRAI 2024). Association for Computing Machinery (ACM), 10 p.Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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Deep Learning with Gated Recurrent Unit Recurrent Neural Networks and Multi-objective Optimisation for Portfolio Management
Liu, Y. & Yu, L., 2025, the 7th International Conference on Pattern Recognition and Artificial Intelligence. IEEE, 6 p.Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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Novel Volatility Forecasting Using Deep Learning - Long Short Term Memory Recurrent Neural Networks
Liu, Y., 2019, In: Expert Systems with Applications. 132, p. 99 109 p., 132.Research output: Contribution to journal › Article › peer-review
139 Citations (Scopus) -
A novel battery network modelling using constraint differential evolution algorithm optimisation
Liu, Y., Rowe, M., Holderbaum, W. & Potter, B., 1 May 2016, In: Knowledge-Based Systems. 99, p. 10-18 9 p.Research output: Contribution to journal › Article › peer-review
Open Access4 Citations (Scopus) -
A Novel Fast Optimisation Algorithm Using Differential Evolution Algorithm Optimisation and Meta-Modelling Approach
Liu, Y., Kwan, A., Rezgui, Y. & Li, H., 2016, Yang XS. (eds) Nature-Inspired Computation in Engineering. Studies in Computational Intelligence. Springer, Vol. 637. p. 177-193Research output: Chapter in Book or Report/Conference proceeding › Chapter › peer-review