I am a Reader within IPAB in the School of Informatics at the University of Edinburgh, and Visiting Reader at Queen Mary University of London. Previously I was Senior Lecturer/Lecturer ('12-16) at QMUL within the Risk and Information Management (RIM) group and Centre for Intelligent Sensing, where I founded the Applied Machine Learning Lab. I recieved my PhD in Neuroinformatics from Edinburgh in 2008, working with Sethu Vijayakumar in the Statistical Machine Learning and Motor Control group, and my BA in Computer Science from the University of Cambridge in 2002.
My research focuses on machine learning, particularly life-long transfer and active learning, with both probabilistic and deep learinng approaches. I have looked at a variety application areas including computer vision (behaviour understanding, person re-identification, attribute and zero-shot learning), robotics, sensor fusion, novel human-computer interfaces, computational social sciences, theoretical neuroscience and business data analytics.
05/2014: EPSRC Grant Awarded
07/2014: 2 papers on Open World Re-identification
01/2015: EU Horizon 2020 Grant DREAM awarded
05/2015: UAI 2015 paper on Bayesian Net transfer!
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!
02/2016: Expert Systems with Applications paper accepted
03/2016: Three CVPR'16 papers accepted including one Oral!
07/2016: Joining IET Computer vision as associate editor
09/2016: Paper accepted to EMNLP'16!
09/2016: Moved from QMUL to IPAB at UoE
11/2016: Paper in AAAI'17!
01/2017: Deep Multi-task learning in ICLR'17!
04/2017: Transfer learning for Control paper accepted in IJCAI'17!
07/2017: Three papers accepted to ICCV'17!
08/2016: Co-chairing 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)
Code and Data for BMVC04 Fine-grained SBIR paper.
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
05/2017: LIMA dataset for re-id and tracking at CVPR'17
Visit my Google Scholar Profile.