I am a Lecturer in Data Science and I lead the Machine Learning Group in Open Lab at the School of Computing. My research interests are machine learning and its various applications such as behaviour analysis, wearable and ubiquitous computing, computer vision and biometrics, etc.

The research agenda of my team is to develop practical AI tools on solving the challenges for real-world applications. In essence, it is to model the practical problems using mathematical languages and develop machine learning algorithms for the optimal solution,  bridging the gap between signal/data and human understandable knowledge. We have comprehensive experience in processing data from different sources such as video, time series data, text, etc. for different purposes, e.g., physical behaviour assessment for health and well-beings, online behaviour analysis for cyber criminal activity detection, etc.  We are also developing mechanisms on increasing the transparency/interpretability of the complex AI models, which is crucial for many applications such as automated medical diagnosis. 

Area of expertise: Machine Learning, Behaviour Analysis, Ubiquitous Computing, Data Integration

Google Scholar: Click here.

• Guan Y, Yan J. Pokerprint: Seeing Through Your Playing Cards. 2015. (dataset coming soon!). In Preparation.
• Guan Y, Ploetz T. Ensembles of deep LSTM Learners for Activity Recognition using Wearables. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2017, 1(2), 11.
• Guan X, Li CT, Guan Y. Enhanced SVD for Collaborative Filtering. In: Advances in Knowledge Discovery and Data Mining (PAKDD 2016). 2016, Auckland, New Zealand: Springer.
• Guan Y, Li C-T, Roli F. On Reducing the effect of Covariate Factors in Gait Recognition: A Classifier Ensemble Method. IEEE Transactions on Pattern Analysis and Machine Intelligence 2015, 37(7), 1521-1528.
• Li R, Li C-T, Guan Y. Inference of a compact representation of sensor fingerprint for source camera identification. Pattern Recognition 2018, 74, 556-567.
• Guan X, Li C, Guan Y. Matrix Factorization with Rating Completion: an Enhanced SVD Model for Collaborative Filtering Recommender Systems. IEEE Access 2017, 5, 27668-27678.
• Plotz T, Guan Y. Deep Learning for Human Activity Recognition in Mobile Computing. Computer 2018, 51(5), 50-59.
• Long Y, Guan Y, Shao L. Generic compact representation through visual-semantic ambiguity removal. Pattern Recognition Letters 2019, 117, 186-192.