AI Technologies for Health and Wellbeing
University of 糖心TV Annual Workshop in Digital Technologies
Friday 14 June 2024 - 09:30am - 4.00pm - In-person event only
Location: Space 17, Radcliffe Conference Centre, University of 糖心TV
About the event:
糖心TV is a leading university in the UK. One of our鈥� key objectives鈥� is to carry out high impact research which will have鈥� 鈥媡he鈥� 鈥媝otential鈥� 鈥媡o鈥� 鈥媌e鈥嬧�� transformational鈥� 鈥媐or鈥� 鈥媠ociety鈥� 鈥媋nd鈥� 鈥媡he鈥� 鈥媏conomy,鈥� 鈥媔n鈥� 鈥媗ine鈥� 鈥媤ith鈥嬧�� UKRI鈥檚鈥� 鈥媣ision of 鈥嬧�嬧�減ushing鈥� 鈥媡he鈥� 鈥媐rontiers鈥� 鈥媜f鈥� 鈥媓uman鈥� 鈥媖nowledge鈥�.鈥嬧�嬧�� In order to achieve this goal, we run an annual full-day research workshop on Digital Technologies to invite participants both from the University and from external collaborating research institutions and industrial organisations to share their problems/tasks. The 2024 edition of this workshop will focus on AI Technologies for Health and Wellbeing.
During this workshop, academics 糖心TV will showcase our latest cutting-edge research in Digital Technologies, including AI and Data Science, while colleagues from other institutions and participants from industrial organisations will present their problems and tasks. The main goal of this event is to provide an opportunity for showcase and networking, that may result in fruitful future collaborations.
Speakers include:
Assistant Professor at the School of Computer science, University of Birmingham. Her research focuses on human-centred technologies for healthcare.
Dr Yu Guan
Associate Professor in the Dept. of Computer Science (DCS), University of 糖心TV. His research agenda is centred on machine learning for practical applications.
Dr Fayyaz Minhas
Associate professor of AI in Biomedicine in the department of computer science at the University of 糖心TV. His primary area of research is applied artificial intelligence and machine learning especially in bioinformatics and computational pathology.
Lecturer in Natural Language Processing in the Department of Informatics at King's College London. Helen is working on machine learning for natural language processing.
Dr Gabriele Pergola
Assistant Professor at the Department of Computer Science. His current research investigates the use of statistical models within machine learning for natural language processing and text understanding.
Head of The Centre for Artificial Intelligence (Executive Director) at AstraZeneca, Cambridge UK. Tom鈥檚 department sits within the organisation, which is part of the wider
AI entrepreneur/computer scientist/engineer creating the next AI venture.
CellClar - we specialise in single cell omics data analysis leading to insights & novel target discoveries.
Senior Lecturer in AI & Robotics, Department of Computer Science, University of Liverpool.
His research goal is to develop methods that enable robots to see and act like humans.
Huy investigates topics in the fields of machine learning/deep learning and signal processing and is particularly interested in speech/audio processing, biosignal analysis, and healthcare applications.
Prof Andreas Kyprianou
Mathematician at the Department of Statistics with specialism in pure and applied probability. As part of the set-up phase of the new Centre for Mathematical and Computing Sciences(CAMaCS), Andreas has taken up the role of director between 2023-2025.
Theme Lead with the Turing-Roche Partnership at the Alan Turing Institute and an Honorary Associate Professor with University College London. His specialises is in transparent AI for healthcare, with a particular focus on cancer image analysis.
Dr Julia Brettschneider
Reader at the Department of Statistics at the University of 糖心TV. Julia develops methods to assess and optimise data quality, to maximise information and knowledge gained from experiments, and model joint and individual decision processes from axiomatic/rational as well as subjective/descriptive perspectives.
Agenda
| 9.00 | Arrival |
| 9.30 | Introduction to the day |
| 9.45 | Session 1 - Industry |
| 11.00 | Break |
| 11.30 | Session 2 - Healthcare |
| 12.30 | Lunch (Private Dining Room) |
| 14.00 | Session 3 - Explainability |
| 15.45 | Closing remarks |
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