AI for precision mental health: Data-driven healthcare solutions Developing a cost-effective clinical decision support system to help clinicians
Towards incoherent speech as a predictor of psychosis risk Investigating whether quantitative markers of speech can detect psychotic disorders and help predict clinical outcomes
Harms arising from targeted online 'nudging' Exploring what can be done to ensure that the influences of online ‘nudges’ do not become manipulative or harmful to vulnerable groups
Simulating cities with AI agents Developing new approaches for modelling human behaviour in cities, for simulating urban dynamics
AI for precision mental health Producing AI tools than can personalise mental health profiles and advance the precision of early diagnosis and subsequent treatment
Robotics and AI for health and social care Monday 28 Oct 2019 - Tuesday 29 Oct 2019 Time: 10:00 - 17:30 Alessandro Di Nuovo Borghese Nunzio Alberto Farshid Amirabdollahian Katrin Solveig Lohan Luc de Witte Praminda Caleb-Solly Ray Jones Amelia DeFalco Erica Palmerini Yoshio Matsumoto, Samia Nefti-Meziani
Vocal interactivity in-and-between humans, animals and robots Thursday 29 Aug 2019 - Friday 30 Aug 2019 Time: 09:00 - 17:00 Sonja Vernes Mohamed Chetouani Tecumseh Fitch Verena Rieser
Towards Autonomous Robotic Systems Conference (TAROS) Wednesday 03 Jul 2019 - Friday 05 Jul 2019 Time: 09:00 - 18:00
The future of sleep health: A data-driven revolution in sleep science and medicine In recent years, there has been a significant expansion in the development and use... Perez-Pozuelo, I., Zhai, B., Palotti, J. et al. The future of sleep health: a data-driven revolution in sleep science and medicine. npj Digit. Med. 3, 42 (2020). https://doi.org/10.1038/s41746-020-0244-4
What the success of brain imaging implies about the neural code The success of fMRI places constraints on the nature of the neural code. The... Guest, O., & Love, B. C. (2017). What the success of brain imaging implies about the neural code. eLife, 6, e21397. http://doi.org/10.7554/eLife.21397