Shuo Wang is currently a Research Fellow at the Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA) in the School of Computer Science at the University of Birmingham.
She is currently working on an EPSRC-funded project DAASE -- Dynamic Adaptive Automated Software Engineering. DAASE seeks to use computational search as an overall approach to achieve the software's full potential for flexibility and adaptivity. As one of the theme leaders on predictive modelling, she explore and develop machine learning approaches to facilitate software engineering process, especially in software testing.
Before, she worked on the European funded project i-Sense: Making Sense of Nonsense. The mission of the i-Sense project is to develop intelligent data processing methods for analyzing and interpreting the data such that faults are detected (and whereas possible anticipated), isolated and identified as soon as possible, and accommodated for in future decisions or actuator actions. Her current focus was on online learning techniques for cognitive fault diagnosis.
Prior to this position, she completed the Ph.D. on Ensemble Diversity for Class Imbalance Learning under the supervision of Professor Xin Yao in 2011. Her Ph.D. was funded by the Overseas Research Students Award (ORSAS) from the British Government (2007).
Her research interests include class imbalance learning, ensemble learning, online learning, machine learning techniques and data mining.