Faculty of Science and Technology, Middlesex University

Artificial Intelligence Research Group


JuDDGES


Judicial Decision Data Gathering, Encoding and Sharing EPSRC/CHIST-ERA (ends 1/2026) – P.I. Prof. David Windridge, Co.I Prof Mandeep Dhami


ASTHMA


Machine Learning approaches to detect pre-neoplastic changes in mesothelial cells for early detection of mesothelioma using pleural fluid and liquid biopsies (ends 2025) lead: Imperial College Royal Brompton Hospital, Co-PI: Prof. Xiaohong Gao


Women in STEM


Quam Id Leo Women in STEM MSc Scholarships (2023-2024)

Middlesex University London is pleased to announce the British Council MSc Scholarhships (n=6) for Women in STEM to allow female students from East Asia to study one of our master degrees for the 2023/24 academic year.

4 fellows to work on e-learning, healthcare and digital twin PI: Prof. Xiaohong Gao & Serengul Smith


ChemNLP


OpenBioML initiative with Stability AI and the European Bioinformatics Institute (Dr. Tirunagari/Prof. Windridge): award of extensive GPU resources for training of 3-5 Billion parameter Large Language Models from scratch for the Biosciences


Women in STEM (2022-2023)


Quam Id Leo Women in STEM Scholarships (2022-2023)

Middlesex University London is pleased to announce the British Council Scholarships for Women in STEM for the 2022/23 academic year.

In partnership with the British Council, Middlesex University London is offering six fully funded scholarships for female students studying on STEM subjects, aiming to support girls and women who are under-represented in STEM.


PRISM


Quam Id Leo Machine Learning for Discovery of Pre-neoplastic signature in Mesothelioma (PRISM) (2020-2022)

This project is funded by The Cancer Research UK under Innovation Award and The PRISM project has received funding from CRUK-STFC Early Detection Innovation Award and is to develop a data repository and associated AI tools to improve the diagnosis of malignant mesothelioma. PRISM is led by Imperial College and has collaborators from Warwick University, King’s College London, Oxford University and Middlesex University.


Evolution as an Information Dynamic System (2009-2013)


EPSRC grant EP/H031936/1 (Roman Belavkin, John Aston (Warwick), Alastair Channon (Keel), Chris Knight (Manchester))

The project aims at developing better understanding of the laws of evolution using information dynamics theory. Heredity and mutation are viewed as parameters of an adaptive system, which vary according to changes in information about the environment and fitness. The project is in collaboration with John Aston (University of Warwick, Statistics), Alastair Channon (University of Keele, Computing and Mathematics) and Chris Knight (University of Manchester, Life Sciences).