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, wearables, ubiquitous computing, computer vision and biometrics, etc. Before joining Newcastle University, I received my PhD degree at the Department of Computer Science, University of Warwick in 2015.

Services:

  • Associate Editor, ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT/UbiComp Core A*) 2017-Now
  • Session Chair, ACM UbiComp (Core A*), 2017
  • TPC Members, IEEE Int'l Symposium on Wearable Computers (ISWC, Core A*), 2017, IEEE Int'l Workshop on Biometrics and Forensics (IWBF), 2017, IEEE Int'l Conf. Multimedia and Expo (ICME), 2014
  • Regular Reviewers, IEEE Trans. Pattern Analysis and Machine Intelligence (T-PAMI, Core A*), IEEE Trans. Information Forensics and Security (T-IFS), IEEE Trans. Circuits and Systems for Video Technology (T-CSVT), IEEE Trans. Cybernetics (T-CYB), IEEE Signal Processing Letters (SPL), ACM Multimedia (ACM-MM, Core A*), IEEE ISWC (Core A*), ACM UbiComp (Core A*), Pattern Recognition Letters (PRL), Image and Vision Computing (IVC), IET Biometrics, etc.

Teaching and Tutoring:

  • Module Organiser, CSC8111 "Machine Learning", School of Computing, Newcastle University, 2017-2018
  • Tutorial Lecturer, "Deep Learning For Ubiquitous Computing", ACM UbiComp (Core A*), (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.
  • Guest Lecturer, "Machine Learning for Biometric Applications", for BSc Module "Machine Learning", Department of Computer Science, University of Warwick, Dec. 2014
  • Guest Lecturer, "An Introduction to Gait Recognition", for MSc Module "Multimedia Processing Communications and Storage", Department of Computer Science, University of  Warwick, Nov. 2012

Selected Publications (google scholar citations):

  • Y. Guan and T. Ploetz, "Ensembles of Deep LSTM Learners for Activity Recognition using Wearables ",  ACM IMWUT/UbiComp (Core A*), 2017
  • R. Li, C.-T. Li, and Y. Guan,  "Inference of a Compact Representation of Sensor Fingerprint for Source Camera Identification", Pattern Recognition (PR, Core A*), 2017
  • Y. Guan, C.-T. Li, and F. Roli, "On Reducing the Effect of Covariate Factors in Gait Recognition: a Classifier Ensemble Method",  IEEE T-PAMI (Core A*), 2015

 

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 IEEE T-PAMI, CVPR, IJCAI, ACM-MM, IMWUT/UbiComp, PR, CVIU, etc.  Please contact me if you want to collaborate with us in such exciting fields!

Recent News:

  • Yang's Paper "Zero-shot Learning Using Synthesised Unseen Visual Data with Diffusion Regularisation" has been accepted by IEEE T-PAMI (Core A*)!  Well Done and Congrats!

 Group Members:

  • Yu Guan (Faculty, Deep Learning, Behaviour Analysis, Wearables, Computer Vision and Biometrics)
  • Yang Long (PostDoc, Deep Learning, Zero-shot Learning, Computer Vision, Wearables)
  • Telmo Amaral (PostDoc, Deep Learning, Computer Vision, Anomaly Detection)
  • Rob Thompson (PhD, Wearables, Animal Behaviour Analysis)
  • Shane Halloran (PhD, Deep Learning, Statistical Methods, Behaviour Assessment for Health)

Visiting Researchers:

  • Tom White (PhD, Cambridge University), Feb. 2017

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