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Machine learning in science colloquium
Machine learning in science colloquium

Machine Learning in Science Colloquium

Mon, 04 Dec 2023 09:39:08 GMT

The integration of Machine Learning (ML) and Artificial Intelligence (AI) across scientific disciplines presents a unique opportunity for researchers to come together and ignite collaboration. The Machine Learning in Science (MLiS) Colloquium serves as a platform to facilitate conversations and collaborations leading to upskilling, knowledge-sharing, and innovation.

Next-generation hearing aids

Mon, 16 Oct 2023 16:39:00 BST

Hearing loss is a debilitating condition that impacts huge numbers of the population worldwide, with approximately 430 million people suffering from hearing impairments. Professors Qammer H. Abbasi, Muhammad Imran and their teams are working on an EPSRC-funded project focusing on next-generation hearing aids, achievable through radio frequency (RF) sensing of lip and mouth movements.

A screenshot of the MAVERIC software
A screenshot of the MAVERIC software

MAVERIC (Modelling of Autonomous Vehicle Environments using Robust, Intelligent Computing)

Sun, 01 Jan 2023 10:06:56 GMT

In the James Watt School of Engineering, Dr David Anderson, a Reader in the Autonomous Systems and Connectivity section, has led the development of a multi-resolution, multi-agent autonomous systems simulation engine and complementary software toolset called MAVERIC.

Busy street in Brazil
Busy street in Brazil

New methods in data linkage to tackle health inequalities

Sun, 01 Jan 2023 09:26:00 GMT

Within the School of Health and Wellbeing, the MRC/CSO Social and Public Health Sciences Unit conducts high quality research that has a real impact on reducing health inequalities both at home and across the globe.

Protecting society through digital classification of sensitive material

Sun, 01 Jan 2023 09:50:00 GMT

Colleagues in the School of Computing Science have developed machine learning models for accelerating the identification of context-dependent sensitive information to assist with the sensitivity review of digital data documents in Government departments.

Waterproofing data in urban sustainability

Sun, 01 Jan 2023 09:47:36 GMT

Researchers at the Urban Big Data Centre in the College of Social Sciences have developed a resource that pulls together data to help predict when flooding will occur, addressing a major data gap regarding the local impacts of climate hazards on vulnerable communities.