I am a Lecturer (Assistant Professor) in the Vision, Learning and Control (VLC) group within the school of Electronics and Computer Science (ECS) at the University of Southampton . I mainly research generative computer vision and continual machine learning for artificial general intelligence. My currently focused machine learning methodologies include generative modelling, continual learning, and language prompting. The ultimate quest of my research is to empower machines with rational, emotional and imaginal intelligence.
I am looking for motivated and talented researchers/students to join our research group. Please have a look at the Openings and reach me if you are interested.
(2019) Video Quality Mapping Tutorial - From Image Restoration to Enhancement and Beyond (FIRE), ICCV 2019, Seoul, Korea: slides (co-presented with Danda Pani Paudel)
Continual Computer Vision: A Path Towards Artificial General Intelligence, Seminar Talk, Vision, Learning and Vision (VLC) group, University of Southampton, Feb 9th, 2023
NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results , Oral Presentation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) workshop, June 15th, 2020
Sliced Wasserstein Generative Models for Image & Video Generation and Enhancement , Invited Talk, Automatic Control Lab, ETH Zürich, June 13th, 2019
Deep Learning on Lie Groups for Skeleton-based Action Recognition , Spotlight Presentation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 22nd, 2017
Deep Manifold Learning for Human-focussed Video Classification , Postdoc Talk, Computer Vision Lab, ETH Zürich, Nov. 30th, 2016
Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold, Oral Presentation, International Conference on Machine Learning (ICML), July 10th, 2015
Learning Euclidean-to-Riemannian Metric for Point-to-Set Classification, Invited Talk, Vision And Learning Seminar (VALSE) Webinar, Dec. 11th, 2014
Learning Euclidean-to-Riemannian Metric for Point-to-Set Classification, Oral Presentation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 25th, 2014