We are delighted to report that Dr Greg Watson and Dr Lin Gui have been promoted to, respectively, Senior Teaching Fellow and Senior Research Fellow, effective from 1 August 2021. Quoting from their recommendations,

What particularly stands out ... is the virtuous circle of (1) Dr Watson’s continual striving for advancing his teaching expertise, evidenced by the extensive courses he has both attended and contributed to, (2) the strong two-way links between Dr Watson’s development and his teaching practice (and that of his peers), evidenced by the various different changes and improvements that he introduced in the classroom based on his scholarly educational investigations, and (3) the consistent very positive feedback from different groups of students as well as colleagues.

and

Dr Lin Gui is one of the most successful postdoctoral researchers in the recent history of the Department, and is continuing his research career with us after a prestigious two-year Marie Curie fellowship. He has been building a solid and high-flying international reputation, underpinned by an impressive trajectory of high-quality publications. Dr Gui’s initiative and emerging independence are in particular reflected in his contributions to substantial successful funding proposals.

it remains to say many congratulations!

Dr. Tanaya Guha (PI) has been awarded a research grant by Ford Motor Company through their Global University Research Program to develop the project "Multimodal Learning for In-Car Driver's Activity Monitoring". This 2-year project aims at developing an AI system that can monitor driver's and passengers' safety through audiovisual scene analysis integrated with short-term driving patterns. For example, by creating alerts when a driver is distracted. The project will be developed in collaboration with Ford's AI research at Michigan.

Congratulations to third-year Computer Science student Hengrui Zhang, who has had an abstract accepted at the British Conference of Undergraduate Research 2021 (BCUR 2021). Hengrui’s abstract, titled "Emotional Adjusted Chinese Sentiment Analysis", proposes a new and enhanced sentiment analysis model, SETCM, which combines the advantages of sentiment lexicon, emoji and neural computing technology. The proposed method overcomes the shortcomings of existing sentiment analysis on Chinese-language text. It is based on the work that Hengrui has completed as part of his third-year project, supervised by Dr Greg Watson.