Research output per year
Research output 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).
Research interests
Artificial Intelligence
Statistical Pattern Recognition
Optimisation
Teaching
Python Programming
Education/Academic qualification
MSc, University of Exeter - 2003
PhD, University of Exeter - 2006
Person Types
- Staff
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Dive into the research topics where Yang Liu is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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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
106 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
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A flood inundation modelling using v-support vector machine regression model
Liu, Y. & Pender, G., Nov 2015, In: Engineering Applications of Artificial Intelligence. 46, p. 223-231 9 p.Research output: Contribution to journal › Article › peer-review
35 Citations (Scopus) -
Carlisle 2005 urban flood event simulation using cellular automata-based rapid flood spreading model
Liu, Y. & Pender, G., Jan 2013, In: Soft Computing. 17, 1, p. 29-37 9 p.Research output: Contribution to journal › Article › peer-review
19 Citations (Scopus)