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.

Shen Wang and Professor Feng Hao from the Systems and Security theme at the Department of Computer Science and Ehsan Toreini from Durham University, have had the paper ‘Anti-Counterfeiting for Polymer Banknotes Based on Polymer Substrate Fingerprinting’, published in the journal IEEE Transactions on Information Forensics and Security, in which they propose a novel technique called Polymer Substrate Fingerprinting, which can identify each banknote’s own unique, unclonable fingerprint.

The researchers have found that every polymer banknote has a unique "fingerprint", which is caused by the inevitable imperfection in the physical manufacturing process, whereby the opacity coating, a critical step during the production of polymer notes, leaves an uneven coating layer with a random dispersion of impurities in the ink. This imperfection results in random translucent patterns when a polymer banknote is back-lit by a light source.

Prof. Graham Cormode of the Department of Computer Science has been named among the 2020 Association for Computing Machinery (ACM) Fellows, for contributions to computer science. The ACM is the world's leading learned society for computer science. Prof. Cormode is recognised for his contributions to data summarisation and privacy enabling data management and analysis. His work on data streams and sketching has been widely implemented in many high tech companies and organisations.