I am a Reader within IPAB in the School of Informatics at the University of Edinburgh, where I head the Machine Intelligence Research group; Principal Scientist at Samsung AI Research Centre, Cambridge; Turing Fellow of the Alan Turing Institute; 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 learning approaches. I have looked at a variety application areas including computer vision (behaviour understanding, person re-identification, attribute and zero-shot learning), vision and language, robotics, sensor fusion, computational social sciences, theoretical neuroscience and business data analytics.
01/2015: EU Horizon 2020 Grant DREAM awarded
07/2015: BMVC 2015: Our Sketch recognition CNN is the first to surpass human performance, wins Best Science Paper prize!
11/2016: Paper in AAAI'17: Guaranteeing rationality in neural networks!
01/2017: Deep Multi-task learning in ICLR'17!
04/2017: Transfer learning for Control paper accepted in IJCAI'17!
10/2017: Program co-chair of BMVC2018!
11/2017: EPSRC ORCA Hub in Robotics and AI awarded!
11/2017: Paper at AAAI'18: Meta-learning for domain generalization!
02/2018: Nine papers accepted at CVPR'18!
07/2018: Our Meta Learning Active Learning paper awarded Best Paper Prize at ICML AutoML'18!
07/2018: Three papers accepted at ECCV'18!
08/2018: Congratulations Kunkun Pang! Dynamic Ensemble Active Learning wins Best Student Paper Award @ ICPR2018!
03/2019: Two papers in CVPR'19!
03/2019: Two papers in ICML'19!
06/2019: Congratulations Carl Allen! Analogies Explained paper wins Honorable Mention @ ICML'19!
08/2019: Three papers at ICCV'19!
08/2019: TuckER model for fast and effective knowledge graph completion accepted at EMNLP2019!
09/2019: Two papers in NeurIPS'19!
11/2019: Two papers in AAAI'20!
12/2019: Joining T-PAMI as AE!
01/2020: Paper accepted to ICLR'20, congrats Miguel!
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.
10/2017: Program co-chair of BMVC 2018
03/2018: Keynote at Vision & Language Conference.
03/2018: Talk on sanity guarantees for deep learning at Deep Learning in Finance Summit London 2018.
09/2018: Hiring a postdoc research associate on deep learning, 2.5yr post, international applicants welcome. Closing date 4th October 2018. Apply.
05/2019: Teaching the Advanced Topics in Deep Learning Summer School, May 2019 in Verona.
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
01/2018: Demo code CVPR'18 learning to compare few-shot learning
07/2018: Neural Decision tree Example Code.
05/2019: Hypernetwork KB Completion Code.
05/2019: Tucker Decomposition Link Prediction Code.
Visit my Google Scholar Profile.