Machine Learning for Computer Vision and Natural Language Processing
Focus of our research
Machine learning has changed major industries around the world, and its impact is felt in many areas of our day-to-day life. New machine learning methods are needed to tackle the big data world we live in, especially in challenging areas such as computer vision and natural language processing. Such new methods need to effectively train very large models, usually in the form of deep neural networks or large probabilistic models. This is a big challenge both algorithmically and in its implementation on high-performance computers.
Research on deep and other machine learning methods is done in the context of:
- real-world computer vision problems from biomedical and health applications
- smart cities and autonomous driving
- challenging natural language processing tasks.
Our Postgraduate Researchers (PGRs)
|Maria Tariq||Detection of Diabetic Retinopathy and Diabetic Maculopathy using Deep Learning||Vasile Paladefirstname.lastname@example.org|
|Ruchita Mehta||Multi-sensor and AI Enabled System Design for Remote Monitoring of Physiological Signals and Activities in COVID-19 Imposed Conditions’||Sara Sharifzadehemail@example.com|
|Thoufeeq Ahmed Syed||Building Personalised Recommenders in Learning Management Systems and Social Learner Networks||Vasile Paladefirstname.lastname@example.org|
|Uche Abiola Onyekpe||Learning Uncertainties in Ego Motion Sensors for Autonomous Vehicle Localisation in GNSS-deprived Environments||Vasile Paladeemail@example.com|
|Yordanka Karayenava||Machine Learning for Human Activity Recognition with Non-Intrusive Sensors||Sara Sharifzadehfirstname.lastname@example.org|
|Ankur Deo||Efficient Machine Learning For Car Situational Awareness||Vasile Paladeemail@example.com|