Yu Guan

Yu.Guan@ncl.ac.uk | Faculty

Yu Guan

I am a lecturer in data science and I lead the machine learning group in open lab. My research interests are machine learning and its various applications such as behaviour analysis, wearable and ubiquitous computing, computer vision and biometrics, etc. My publication list can be found through google scholar citations. Before joining Newcastle University, I received my PhD degree at the department of computer science, University of Warwick in 2015.


  • Associate Editor, ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT/UbiComp) 2017-Now
  • Session Chair, ACM UbiComp, 2017
  • TPC Members, IEEE Int'l Symposium on Wearable Computers (ISWC), 2017, IEEE Int'l Conf. Multimedia and Expo (ICME), 2014
  • Regular Reviewers, IEEE Trans. Pattern Analysis and Machine Intelligence (T-PAMI), International Journal on Computer Vision (IJCV), Pattern Recognition, ACM Multimedia (MM), IEEE ISWC, ACM UbiComp, IEEE Trans. Information Forensics and Security (T-IFS), IEEE Trans. Circuits and Systems for Video Technology (T-CSVT), IEEE Trans. Cybernetics (T-CYB), IEEE Pervasive Computing, etc.

Teaching and Tutoring:

  • Module Organiser, CSC8111 "Machine Learning", School of Computing, Newcastle University, 2017-2018
  • Guest Lecturer, "Deep Learning for Human Activity Recognition", for MSc Module "Introduction to Deep Learning", Department of Computer Science, UCL, London, Oct. 2017
  • Tutorial Lecturer, "Deep Learning For Ubiquitous Computing", ACM UbiComp, (Co-hosting with T. Ploetz, Georgia Tech, N. Lane, Oxford University&Bell Labs, and S. Bhattacharya, Bell Labs), Maui, Hawaii, US. Sept. 2017.
  • Guest Lecturer, "Deep Neural Networks", for MSc Module "Machine Learning", School of Computing Science, Newcastle University, Dec. 2016
  • Tutorial Lecturer, "Deep Learning and its Mobile Applications", the 8th Int'l Conference on Mobile Computing, Application and Services (MobiCASE), (Co-hosting with T. Ploetz, Georgia Tech, N. Lane, UCL&Bell Labs, and S. Bhattacharya, Bell Labs), Cambridge, Nov. 2016.


About Machine Learning Group

Our research agenda is to develop state-of-the-art machine learning algorithms for real-world applications. One of our major research directions is computational behaviour analysis in different scenarios (e.g., identification/activity recognition/anomaly detection) based on various data sources (e.g., from videos/wearable sensors). In terms of methodologies, we are very interested in deep learning, zero-shot learning, and multimodal fusion. Our group members have substantial experience in publishing papers at top-tier (applied) machine learning venues such as T-PAMI, CVPR, AAAI, ACM-MM, IMWUT/UbiComp, PR, CVIU, etc.  Please contact me if you want to collaborate with us in such exciting fields!

Recent News:

  • Our Paper "Towards Universal Representation for Unseen Action Recognition" has been accepted by CVPR 2018
  • Yang's Paper "Towards Affordable Semantic Searching: Zero-shot Retrieval via Dominant Attributes" has been accepted by AAAI 2018
  • Yu gave a guest lecture on "Deep Learning for Human Activity Recognition" at UCL!
  • Yang's Paper "Zero-shot Learning Using Synthesised Unseen Visual Data with Diffusion Regularisation" has been accepted by IEEE T-PAMI

 Group Members:

  • Yu Guan (Faculty, Deep Learning, Behaviour Analysis, Wearables, Computer Vision and Biometrics)
  • Yang Long (Research Fellow, Deep Learning, Zero-shot Learning, Computer Vision, Wearables)
  • Rob Thompson (Research Associate, Wearables, Animal Behaviour Analysis)
  • Bingzhang Hu (Research Associate, Deep Learning, Metric Learning)
  • Bing Zhai (MRes, Wearables, Sleep Quality Assessment)

BSc/MSc Student Projects:

  • Joss Cousins (Automated Archery Skill Assessment using Wearables)
  • Guillermo Chibas Puente (Stock Market Prediction using Machine Learning Techniques)
  • Robert Nixon (Behaviour Analysis for Tennis Players using Wearables)
  • Cameron Smith (Image Analysis using Machine Learning Algorithms)

Visiting Researchers:

  • Ruoshui Liu (PhD, Hanwei Ltd & Cambridge University), Nov. 2017
  • Tom White (PhD, Cambridge University), Feb. 2017


Inference of a compact representation of sensor fingerprint for source camera identification
Li R, Li C-T, Guan Y, Pattern Recognition556-567


Matrix Factorization with Rating Completion: an Enhanced SVD Model for Collaborative Filtering Recommender Systems
Guan X, Li C, Guan Y, IEEE AccessEpub ahead of print
Ensembles of deep LSTM Learners for Activity Recognition using Wearables
Guan Y, Ploetz T, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies


Enhanced SVD for Collaborative Filtering
Guan X, Li CT, Guan Y, Advances in Knowledge Discovery and Data Mining (PAKDD 2016)503-514


On Reducing the effect of Covariate Factors in Gait Recognition: A Classifier Ensemble Method
Guan Y, Li C-T, Roli F, IEEE Transactions on Pattern Analysis and Machine Intelligence1521-1528
Copyright 2015 Open Lab