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 at QMUL. I am head of the Applied Machine Learning Lab at QMUL, and a member of the Risk and Information Management (RIM) group, as well as the Centre for Intelligent Sensing. Previously I was a Lecturer ('12-15), and Postdoc ('08-11) coordinating the behaviour monitoring work package for the SAMURAI EU FP7 project at QMUL. During my PhD ('04-08), 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 research focuses on 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

Update: From September 2016, I have moved to Informatics at University of Edinburgh


05/2014: EPSRC Grant Awarded

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

01/2015: EU Horizon 2020 Grant DREAM awarded

02/2015: PAMI paper accepted: Record AwA ZSL 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

02/2016: Expert Systems with Applications paper accepted

03/2016: Three CVPR'16 papers accepted including one Oral!

07/2016: One ECCV'16 paper accepted

07/2016: Two BMVC'16 papers accepted as Orals!

07/2016: Joining IET Computer vision as associate editor

09/2016: Paper accepted to EMNLP'16!

08/2016: Co-chairing upcoming BMVA symposium on Transfer Learning in Computer Vision

09/2016: Guest Editor - IET CV - Special Issue on Deep Learning for Computer Vision

10/2016: Keynote on transfer learning with paramaterised tasks and domains at ECCV 2016 TASK-CV workshop!

10/2016: Giving the zero-shot learning part of ACM Multimedia '16 tutorial Emerging topics in learning from noisy and missing data.

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

03/2016: 800K image+social metadata dataset from our ACM DH'16 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

    Associate Editor

    • IET Computer Vision

    Area Chair

    • IEEE WACV 2016


    • CVPR, ICCV, ECCV, NIPS, SIGGRAPH, ACM MM, 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 (IJCV)
    • Image and Vision Computing
    • Computer Vision and Image Understanding (CVIU)
    • International Journal of Robotics Research
    • International Conference on Robotics & Automation
    • 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
    • International Journal of Multimedia Information Retrieval

    Funding Agencies

    • Member of EPSRC Associate Peer Review college
    • Reviewer: EPSRC, NSERC, Leverhulme

Visit my Google Scholar Profile.











Lifelong and Transfer Learning

Zero-Shot Learning

Active Learning

Behaviour and Action Understanding

Person re-identification

Attribute Learning

Deep Learning

Machine Learning

Zero-shot learning, Vision and Language

Computer Vision




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