The general aim of this project is to develop novel algorithms to discover new knowledge about users’ individual interests, preferences, sentiment and emotional status, and information needs from large scale data, for the purpose of facilitating recommender systems to provide better personalized services for users. To better capture the unique distinctive features of social and pervasive data, this project will adopt advanced machine learning techniques such as reinforcement learning, generative models, deep learning, and semi-supervised machine learning methods. Its outcomes will alleviate the major difficulty--the lacking of accurate user profiles--of many personalisation in many domains such as ecommerce, e-health, and e-learning. This project will contribute to the discovery of new knowledge about human users and the social world, and the new solutions to make better usage and processing of big data. The project will be suitable for a student with a degree in Engineering, Physics, Mathematics, Meteorology, or Computer Science. Good understanding about the theories related to machine learning, optimization, data mining and good scientific programming skills in python or Java is needed.