Timothy Hospedales

Senior Lecturer
(Associate Professor)

RIM Group
Electronic Engineering and Computer Science
Queen Mary University, London
E1 4NS
t.hospedales at qmul.ac.uk

I am a Senior Lecturer in Computer Science with the Risk and Information Management (RIM) group at QMUL. Previously, I coordinated the behaviour monitoring work package for the SAMURAI EU FP7 project at QMUL ('08-11). During my PhD, I worked with Sethu Vijayakumar in the Statistical Machine Learning and Motor Control group and Edinburgh's IPAB and ANC institutes.

My background spans informatics & neuroscience (PhD Neuroinformatics, Edinburgh, 2008; MSc Neuroinformatics, Edinburgh 2004), machine learning (MSc Informatics, Edinburgh, 2003) and computer science (BA Computer Science, University of Cambridge, 2002).

My academic interests include probabilistic modelling and machine learning, particularly life-long, transfer and active learning. I have looked at a variety application areas including computer vision (behaviour understanding, person re-identification, attribute and zero-shot learning), sensor fusion, robotics, motion-capture, novel human-computer interfaces, theoretical neuroscience and business data analytics


05/2014: EPSRC Grant Awarded

06/2014: 3x Papers accepted to ECCV 2014

07/2014: 2 papers on Open World Re-identification

10/2014: Kunkun Pang and Ryan Layne join the lab

01/2015: Paper accepted to IEEE PAMI

01/2015: Tanmoy Mukherjee joins the lab

01/2015: EU Horizon 2020 Grant DREAM awarded

02/2015: PAMI paper accepted: Record AwA ZSL benchmark results!

03/2015: 2x papers accepted to CVPR 2015!

03/2015: ICLR 2015 paper on multi-task/domain!

05/2015: UAI 2015 paper on Bayesian Net transfer!

06/2015: PAMI paper accepted on Robust Ranking!

07/2015: Welcome Chenyang Zhao to the lab

07/2015: BMVC 2015 Oral: Our Sketch recognition Deep Neural Network is the first to surpass human performance!

09/2015: Our BMVC'15 sketch recognition paper wins Best Science Paper prize!

09/2015: Welcome Marija Jegorova to the lab

04/2015: 1x Fully Funded (including international) PhD Studentship in Autonomous Machine Learning (DREAM project). Closed 01 May 2015. Start Date: Late 2015.

Sample code for active learning & discovery (PAKDD'11,TKDE'11,ECCV'12)

Unsegmented sports news dataset available (ICDM'11). Includes reference extracted STIP features and ground-truth multi-label annotation.

Sample code for MCTM (ICCV'09, IJCV'11) and WSJTM (ACCV'10, PAMI'11)

Attribute Dataset for Heterogeneous Face Recognition (ACCV'14)

02/2015: Code for the famous ELF descriptor in re-id. First ever public release!

06/2015: Ground-truth Anomaly Annotation for ICCV'09 and IJCV'11 papers.

07/2015: Code for Sketch-a-Net BMVC'15 paper.

09/2015: Code for our ICLR'15 Multi-Task/Multi-domain paper

09/2015: Multi-camera video surveillance dataset from our TCSVT'15 paper

Grants & Funding


  1. Ph.D. Neuroinformatics, University of Edinburgh, 2008
    Thesis: Bayesian Multisensory Perception
    Advisor: Sethu Vijayakumar
    Examiners: Carl Rasmussen and Amos Storkey

  2. MSc, Neuroinformatics, University of Edinburgh, 2004
    Thesis: Functional Organization & Plasticity in the Vestibulo-Ocular Reflex
    Advisor: Mayank Dutia

  3. MSc, Informatics, University of Edinburgh, 2003
    Thesis: Optimal Learning in Neurons with Active Dendritic Spines
    Advisor: David Barber

  4. BA, Computer Science, University of Cambridge, 2002
    Dissertation: A Probabilistic Approach for Commodity Eye-Tracking
    * Best Dissertation Prize, University of Cambridge Computer Laboratory
    * UK SET Computer Science Student of the Year Award
    Advisor: David Mackay

Professional Experience

  1. Vision Semantics Limited, United Kingdom
    Consultant, 2009-Present
    Projects: MCT (Reidentification), Super Resolution, Egocentric Behaviour Profiling
  2. Queen Mary University of London, United Kingdom
    Postdoctoral Researcher, 2008-2012
    Projects: SAMURAI

Academic and Services

    Area Chair

    • IEEE WACV 2016


    • CVPR, ICCV, ECCV, ACCV, AVSS, ICPR, ACPR, BMVC (* Distinguished Reviewer Award 2012), ECCV-ReId, CISP, ICNC-FSKDD

    Journal Reviewer

    • IEEE Transactions on Pattern Analysis and Machine Intelligence
    • IEEE Transactions on Knowledge and Data Engineering
    • IEEE Transactions on Image Processing
    • IEEE Transactions on Systems, Man and Cybernetics, Part B
    • IEEE Transactions on Cybernetics
    • IEEE Transactions on Human Machine Systems
    • IEEE Transactions on Neural Networks
    • IEEE Transactions on Circuits and Systems for Video Technology
    • ACM Transactions on Intelligent Systems and Technology
    • Artificial Intelligence
    • International Journal of Computer Vision
    • Image and Vision Computing
    • International Journal of Robotics Research
    • Neurocomputing
    • IEEE Signal Processing Letters
    • Journal of Statistical Planning and Inference
    • Journal of Electronic Imaging
    • SPIE Optical Engineering
    • Advances in Artificial Intelligence
    • IET Intelligent Transport Systems

    Reviewer for Funding Agencies

    • EPSRC, NSERC, Leverhulme

Visit my Google Scholar Profile.










Zero-Shot Learning

Active Learning

Behaviour and Action Understanding

Person re-identification

Attribute Learning

Deep Learning

General Computer Vision and Machine Learning




Bookchapter / Workshop / Thesis


  • Person Re-identification, Attributes, Transfer Learning

PhD Students

Yongxin Yang
  • Lifelong Learning
Kunkun Pang
  • Active Learning & Perception
Tanmoy Mukherjee
  • Semantic Embeddings & Lifelong learning
Chenyang Zhao
  • Lifelong learning for Robotics and Control
Marija Jegorova
  • Lifelong learning for Robotics and Control

PhD Students, Co-supervisor

  • Weakly Supervised Learning, Attributes
  • Visual Surveillance, Action Recognition, Transfer Learning
  • Cross-domain matching, Sketches, SBIR
Shuxin Ouyang
  • Cross-domain matching, Sketches, Face Recognition

PhD Students, Graduated

  • Transfer Learning, Zero-shot Learning, Attributes, Learning to Rank
  • Now at Disney research
  • Transfer Learning in Bayesian Networks
  • Now at Goldsmiths


2015/16: Semester A
  • Data Mining, Machine Learning, Procedural Programming
2014/15: Semester A
  • Data Mining, Procedural Programming
2014/15: Semester B
  • Java (BUPT)
2013/14: Semester A
  • Data Mining
2013/14: Semester B
  • Semantic Web
2012/13: Semester A
  • Information Systems
2012/13: Semester B
  • Semantic Web