I am a 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 active, life-long and transfer 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
08/2013: Paper accepted to ICCV 2013
08/2013: Paper accepted to IEEE PAMI
10/2013: Yongxin Yang joins the lab
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 ZSL benchmark results!
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!
MSc, Neuroinformatics, University of Edinburgh, 2004
Thesis: Functional Organization & Plasticity in the Vestibulo-Ocular Reflex
Advisor: Mayank Dutia
MSc, Informatics, University of Edinburgh, 2003
Thesis: Optimal Learning in Neurons with Active Dendritic Spines
Advisor: David Barber
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
Visit my Google Scholar Profile.