Yu Guan

I am an Associate Professor in the Dept. of Computer Science (DCS) at Warwick, and I lead Ubiquitous & Visual Computing Lab (UVLab) . I received my PhD degree from DCS, Warwick in 2015, and later worked as RA and lecturer in Newcastle University, before moving back to Warwick at 2022.

Research:

My research agenda is centred on machine learning for practical applications. That is, I develop robust machine learning algorithm for data modelling (e.g., for time-series sensor data, image/video data, etc.) and processing with an emphasis on solving the challenges facing in various real-world scenarios, to bridge the gap between theoretical research of machine learning and its practical applications. I am particularly interested in Computational Behaviour Analysis (e.g., activity/action recognition, 3D pose estimation, gait analysis), AI for healthcare (e.g., sleep assessment, vital sign analysis), multimodal sensing (mmWave sensing, wearable and visual sensing), Applied Machine Learning (e.g., cross-modal learning, physics informed learning, domain generalisation). Currently, I am an Associate Editor of ACM Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), an Associate Editor of Frontier in Computer Science. I've published 80+ peer-reviewed papers including top-venues like T-PAMI, T-IP, ICML, CVPR, ICCV, ECCV, ACL, IMWUT, etc. My paper (collaborated with Prof. Thomas Ploetz, Georgia Tech) "Ensembles of Deep LSTM Learners for Activity Recognition using Wearable" ranks 2nd in citations in IMWUT (out of about 2000 papers)!

Selected Publications:

J. Li, G. Wang, S. Zheng, M. Ni, X. Lu, G. Ye, and Y. Guan, "Towards Mitigating Modality Bias in Vision-Language Models for Temporal Action Localization", ACL, 2026 (oral, top-1%)
J.Li, S.Zheng, Y.Shen, J.Huang, X.Lu, M.Ni, and Y.Guan, "Keeping the Evidence Chain: Semantic Evidence Allocation for Training-Free Token Pruning in Video Temporal Grounding", ECCV, 2026
S. Zheng, J. Li, X. Lu, S. He and Y. Guan, "Doppler Prompting for Stable mmWave-based Human Pose Estimation", ICML, 2026
S. Zheng, J. Li, G. Wang, M. Ni, A. Palit, G. Montana, and Y. Guan, "Person Parametric Physics-informed Representation for mmWave-based Human Pose Estimation", IMWUT, 2026
Y. Chen, Y. Jiang, L. Zhou, J. Cao, Y. Guan, M. Yang, Q. Guo, "Engage for All: Making Ordinary Image Descriptions Appealing Again!" ICCV 2025
Y Chen, J Jia, J Lu, S Li, Y Guan, M Yang, Q Guo, "VQAGuider: Guiding Multimodal Large Language Models to Answer Complex Video Questions". ACL, 2025
Y. Han, Q. Guo, L. Pan, L. Liu, Y. Guan, M. Yang, "DynFocus: Dynamic Cooperative Network Empowers LLMs with Video Understanding", CVPR 2025
S. Shao, Y. Guan, B. Zhai, P. Missier, T. Ploetz, “ConvBoost: Boosting ConvNets for Sensor-based Activity Recognition” IMWUT, 2023
Y. Bai, D. Zhou, S. Zhang, J. Wang, E. Ding, Y. Guan, Y. Long, J. Wang “Action Quality Assessment with Temporal Parsing Transformer”, ECCV, 2022
J. Su, T. Lin, Z. Wen, Y. Guan “Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition”, IMWUT, 2022
Y. Bai, J. Wang, Y. Long, B. Hu, Y. Song, M. Pagnucco, and Y. Guan “Discriminative Latent Semantic Graph for Video Captioning”, ACM MM, 2021
T. Chen, D. Zhou, J. Wang, S. Wang, Y. Guan, E. Ding, and X. He “Learning Multi-granular Spatio-temporal Graph Network for Skeleton-based Action Recognition”, ACM MM, 2021
J. Wang, Y. Bai, Y. Long, B. Hu, Z. Cai, Y.Guan, X. Wei “Query Twice: Dual Mixture Attention Meta Learning for Video Summarisation”, ACM MM, 2020
B. Zhai, I. Perez-Pozuelo, E.Clifton, J. Palotti, and Y. Guan, “Making Sense of Sleep: Multimodal Sleep Stage Classification in a Large, Diverse Population using Movement and Cardiac Sensing”, IMWUT, 2020
J. Wang, Y.Guan, and L. Shao “Multi-Granularity Canonical Appearance Pooling for Remote Sensing Scene Classification”, T-IP, 2020
Y. Gao, Y. Long, Y. Guan, A. Basu, J. Baggaley, and T. Ploetz, “Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants using Wearable Accelerometers”, IMWUT, 2019
H. Zhang, Y. Long, Y. Guan and L. Shao “Triple Verification Network for Generalised Zero-shot Learning”, T-IP, 2019
Y. Zhu, Y. Long, Y. Guan, S. Newsam, and L. Shao, “Towards Universal Representation for Unseen Action Recognition”, CVPR, 2018
Y. Guan, and T. Ploetz, “Ensemble of Deep LSTM Learners for Activity Recognition using Wearables”, IMWUT, 2017
Y. Guan, C.-T.Li, and F. Roli “On Reducing the Effect of Covariate Factors in Gait Recognition: a Classifier Ensemble Method”, T-PAMI, 2015

A full list of my publications can be found via my google scholar citationLink opens in a new window.


Contact Details Email: yu.guan[at]warwick.ac.uk Address: Office 2.32, Department of Computer Science, University of Warwick, 6 Lord Bhattacharyya Way, Coventry, UK, CV4 7EZ Office Hour (26/27, term 1) 1.30pm-3.30pm, Tuesday

Useful Links:

Funding:

0. New Fundings

1. ISPF (Intel Sci Partnership Fund)

2. NoI form

3. Horizon Europe Fundings (via RIS)

4. Impact Acceleration Award

5. Warwick Horizon Europe Seed Fund

6. Huo Family Foundation

Support:

Global Research Priorities

Warwick Impact Academy