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, Activity Recognition, Automated Health Assessment, Wearable/Ubiquitous Computing, Gait Analytics

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CSC8111 "Machine Learning", School of Computing, Newcastle University, 2017-present

• Ratcliffe AM, Zhai B, Guan Y, Jackson DG, Sneyd JR, Minto G, Howell S, Miller F, Retief JL, Webster DA, Veeralakshmanan P, Graterol JF, Kotwinski DP, Maxwell S, Parish B, Spinney S. Patient-centred measurement of recovery from day-case surgery using wrist worn accelerometers: a pilot and feasibility study. Anaesthesia 2021, epub ahead of print.
• Zhou Y, Hu B, He J, Guan Y, Shao L. Dual reference age synthesis. Neurocomputing 2020, 411, 164-177.
• Tang L, Halloran S, Shi JQ, Guan Y, Cao C, Eyre J. Evaluating upper limb function after stroke using the free-living accelerometer data. Statistical Methods in Medical Research 2020, 29(11), 3249-3264.
• Rehman RZU, Zhou Y, Del Din S, Alcock L, Hansen C, Guan Y, Hortobágyi T, Maetzler W, Rochester L, Lamoth CJC. Gait Analysis with Wearables can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders. Sensors 2020, 20(23), 6992.
• Wang S, Guan Y, Shao L. Multi-Granularity Canonical Appearance Pooling for Remote Sensing Scene Classification. IEEE Transactions on Image Processing 2020, 29, 5396-5407.
• Qian B, Jie S, Wen Z, Jha D, Li Y, Guan Y, Puthal D, James P, Yang R, Zomaya A, Rana O, Wang L, Koutny M, Ranjan R. Orchestrating the Development Lifecycle of Machine Learning-based IoT Applications: A Taxonomy and Survey. ACM Computing Surveys 2020, 53(4), 1-47.
• Wang J, Hu B, Long Y, Guan Y. Order matters: Shuffling sequence generation for video prediction. In: 30th British Machine Vision Conference 2019, BMVC 2019. 2020, Cardiff: BMVA Press.
• Brown R, Pearse J, Edmonds G, Nappey T, Ladha K, Jackson D, Guan Y, Basu A. Wrist-worn devices to improve arm movement in hemiplegic cerebral palsy: participatory design workshops. In: RCPCH Conference. 2020, Online.
• Rehman RZU, Del Din S, Shi JQ, Galna B, Lord S, Yarnall AJ, Guan Y, Rochester L. Comparison of walking protocols and gait assessment systems for machine learning based classification of Parkinson’s disease. Sensors 2019, 19(24), 5363.
• Zhai B, Nicolson S, Montague K, Guan Y, Olivier P, Ellis J. Co-sleep: Designing a workplace-based wellness program for sleep deprivation. In: 13th EAI International Conference on Pervasive Computing Technologies for Healthcare. 2019, Trento, Italy: EAI.
• Long Y, Guan Y, Shao L. Generic compact representation through visual-semantic ambiguity removal. Pattern Recognition Letters 2019, 117, 186-192.
• Rehman RZU, Del Din S, Guan Y, Yarnall AJ, Shi JQ, Rochester L. Selecting Clinically Relevant Gait Characteristics for Classification of Early Parkinson’s Disease: A Comprehensive Machine Learning Approach. Scientific Reports 2019, 9, 17269.
• Gao Y, Long Y, Guan Y, Basu A, Baggaley J, Ploetz T. Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2019, 3(1), 12.
• Guan X, Li C-T, Guan Y. Active learning in multi-domain collaborative filtering recommender systems. In: Proceedings of the 33rd Annual ACM Symposium on Applied Computing (SAC'18). 2018, Pau, France: ACM.
• Plotz T, Guan Y. Deep Learning for Human Activity Recognition in Mobile Computing. Computer 2018, 51(5), 50-59.
• 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.
• Centeno MP, Guan Y, van Moorsel A. Mobile based continuous authentication using deep features. In: EMDL 2018 - Proceedings of the 2018 International Workshop on Embedded and Mobile Deep Learning. 2018, Munich, Germany: Association for Computing Machinery, Inc.
• Halloran S, Shi JQ, Guan Y, Chen X, Dunne-Willows M, Eyre J. Remote cloud-based automated stroke rehabilitation assessment using wearables. In: Proceedings - IEEE 14th International Conference on eScience, e-Science 2018. 2018, Amsterdam, Netherlands: IEEE.
• Zhang H, Long Y, Guan Y, Shao L. Triple Verification Network for Generalised Zero-shot Learning. IEEE Transactions on Image Processing 2018, 28(1), 506-517.
• 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 C, Guan Y. Matrix Factorization with Rating Completion: an Enhanced SVD Model for Collaborative Filtering Recommender Systems. IEEE Access 2017, 5, 27668-27678.
• 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.
• Guan Y, Yan J. Pokerprint: Seeing Through Your Playing Cards. 2015. (dataset coming soon!). In Preparation.