What do we do?
You can join the group of any of the 6 academics below. Each academic has offered a number of topics they are recruiting into.
Dima Damen: Professor of Computer Vision with research interests in egocentric vision, video understanding and fine-grained action understanding.
- Problems using EPIC-KITCHENS (+VISOR, EPIC Fields) or Ego4D datasets
- Long-Tail Video Understanding
- Fine-Grained Video Descriptions
- Audio-visual fine-grained action recognition, localisation or retrieval
Peter Flach: Professor of Artificial intelligence with research interests in evaluation and improvement of machine learning models, mining highly structured data, and human-centred AI.
- Classifier calibration
- Uncertainty representation and propagation
- Knowledge-intensive AI
- Explainability and interpretability
Majid Mirmehdi: Professor of Computer Vision with research interests in human and animal behaviour understanding and medical image/volume analysis
- Human action understanding and assessment, e.g. in healthcare for action quality scores
- Animal action analysis and understanding using camera-trap, drone for other footage
- Segmentation, Classification, and Prediction in medical images and volumes
Raul Santos-Rodriguez: Associate Professor in Data Science and AI with research interests in the foundations of (human-centric) machine learning and its applications to healthcare and climate science.
- Explainability, transparency and fairness
- Weakly supervised learning
- Human visual perception in machine learning
- Human/agent interaction and collaboration
Michael Wray: Assistant Professor of Computer Vision with research interests in video understanding and Natural Language Processing.
- Understanding Biases in Vision Language Models
- Video Moment Retrieval and Video Corpus Moment Retrieval for Long Videos
- Fine-grained Vision-Language Retrieval
- Compositionality for Video-Language models
Zahraa S. Abdallah: Assistant Professor in Data science and Machine Learning with research interest in time series and its healthcare applications and learning from multiple modalities.
- Time series analysis (classification, clustering, explainability)
- Adaptive and active learning
- Genomic data analysis e.g., protein analysis for early detection of cancer
- Data fusion and multi-modalities for combining various types of data sources
Telmo Silva Filho: Assistant Professor in Data Science with research interests in evaluation of machine learning models, explainability, latent-variable models, and medical applications of computer vision.
- Explainable evaluation, i.e. when/why is a model expected to fail?
- Latent-variable models for evaluation
- Segmentation and synthetic generation of medical images
Tilo Burghardt: Associate Professor in Computer Science with research interests in animal biometrics, imageomics and applications of computer vision to animal welfare, farming, and conservation
- Deep learning for the detection of animal species, individuals, and morphological traits
- Recognition of animal poses, behaviours, and social configurations
- Integration of methods in computer vision, taxonomics, genetics, and ecology
- Autonomous visual navigation of conservation drones and related robotic platforms