I am a Professor 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.
Previously I was Reader ('16-'20) at Edinburgh and 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 data-efficient and robust machine learning using techniques such as meta-learning and lifelong transfer-learning, in both probabilistic and deep learning contexts. I have looked at a variety application areas including computer vision, vision and language, reinforcement learning for robot control, finance and beyond.
10/2017: Program co-chair of BMVC2018!
02/2018: Nine papers accepted at CVPR'18!
07/2018: Our Meta Learning Active Learning paper awarded Best Paper Prize at ICML AutoML'18!
08/2018: Congratulations Kunkun Pang! Dynamic Ensemble Active Learning wins Best Student Paper Award @ ICPR2018!
03/2019: Two papers in ICML'19!
06/2019: Congratulations Carl Allen! Analogies Explained paper wins Honorable Mention @ ICML'19!
08/2019: TuckER model for fast and effective knowledge graph completion accepted at EMNLP2019!
09/2019: Two papers in NeurIPS'19!
12/2019: Joining T-PAMI as AE!
02/2020: Four papers at CVPR'20!
04/2020: Check out our new Survey on meta-learning!
07/2020: Four papers in ECCV'20!
08/2020: Promoted to Full Professor.
09/2020: Paper in Siggraph Asia 2020!
09/2020: Paper on online meta-RL in NeurIPS'20!
09/2020: Paper on neurosymbolic learning at AAAI'21!
02/2021: Four papers at CVPR'21!
07/2021: Associate Program Co-Chair of AAAI'22!
07/2021: Three papers in ICCV'21!
09/2021: Papers in NeurIPS'21 and ACML'21!
11/2021: Tim recognised as an ELLIS fellow.
01/2022: Three papers in ICLR'22!
04/2022: Check out our new book, Visual Adaptation in the Deep Learning Era!
05/2022: Check out our SPM tutorial on self-supervision!
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.
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.
05/2020: Keynote @ DIRA workshop in CVPR2020
08/2020: Tutorial on Domain Adaptation @ ECCV2020
09/2020: Open positions for PhD and Postdoc researchers.
10/2020: Check out our Special Issue on Learning with Fewer Labels in IEEE PAMI.
12/2020: Invited Talk at the Meta Learning Workshop in NeurIPS-20
02/2021: Co-organizing learning-to-learn workshop at ICLR-21! Submission deadline Feb 26.
02/2021: Co-organizing learning-to-learn workshop at ICRA-21!
01/2022: Talk at IBM Neuro-symbolic AI workshop 2022.
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.
06/2021: How Well do Self-Supervised models Transfer? Code.
04/2022: P>M>F: State of the art Few-Shot Learning Code.
Visit my Google Scholar Profile.