Doctoral Network in Artificial Intelligence for Future Digital Health is a doctoral training centre funded by the University of Liverpool from October 2019 to train the next generation of world-leading experts in Artificial Intelligence to solve data intensive problems in healthcare.
- Vision of the doctoral network
- Leadership team of the network
- PhD projects: current and future
- Cohort-based training for PhD students
Vision of the doctoral network
- The network will create a community of AI health care experts who will develop new AI tools for medical applications.
- The vision is to establish a world-class centre providing high-quality doctoral training in AI for Future Digital Health.
- The cohort-based training in a collaborative environment will feature peer-to-peer and cohort-to-cohort learning.
- Each PhD project is carefully co-created in collaboration with a health provider and/or a healthcare commercial partner.
- On completion students will be well-placed to take up rewarding careers within the domain of AI and Digital Health.
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Leadership team of the network
- Prof Frans Coenen (director) supervised 50+ successful PhDs in Computer Science.
- Dr Vitaliy Kurlin (co-director, training champion) leads the TDA group in the MIF.
- Prof Katie Atkinson (recruitment) is an expert in AI and the dean of EEECS school.
- Prof Marta Garcia-Finana (equality, diversity, inclusion) is an expert in Biostatistics.
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PhD projects: first cohort from Autumn 2019
- Project :
A study of cellular diversity in health and disease using mass cytometry.
Student : Muizdeen Raji. Supervisors : Nagesh Kalakonda, Vitaliy Kurlin, Joseph Slupsky.
Partner : Clatterbridge Cancer Centre, Wirral. - Project : Machine Learning for the next generation of paediatric wheelchairs.
Student : Peter Wright. Supervisors : Paolo Paoletti, Shan Luo, Iain Hennessey.
Partner : Alder Hey Children’s Hospital, Liverpool. - Project : Deep Feature Learning for Distributed Rehabilitation Robots with Wearable Tactile Sensing.
Student : Omar Elnaggar. Supervisors : Shan Luo, Paolo Paoletti, Andrew Hopkinson.
Partner : Sensor City, Liverpool. - Project :
Using AI to leverage new forms of data in modelling cycling behaviours in the Liverpool City Region.
Student : Aidan Watmuff. Supervisors : Mark Green, Shagufta Scanlon, Huw Jenkins.
Partner: Liverpool City Region Combined Authority. - Project :
An intelligent imaging technology for automatic characterisation of the refractive power of human eye.
Student : Weiqiang Chen. Supervisors : Yaochun Shen, Yalin Zheng, Stephen Kaye.
Partner: Royal Liverpool and Broadgreen University Hospital Trust. - We hope to advertise projects for the next cohort in early 2020.
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Cohort-based training for PhD students
- Dr Vitaliy Kurlin leads the following cohort-based PhD training programme in the doctoral network from 8th October 2019.
- Students with complementary skills can be paired to encourage peer learning, e.g. PhD students from the networks DTC Materials Chemistry, EPSRC CDT in Distributed Algorithms, Technologies for Healthy Ageing and TDA group are welcome.
- Dr Vitaliy Kurlin runs weekly 3-hour sessions on Tuesdays between 11.00-14.00 for about 20 PhD students as follows.
- The presentation at 11-12.20 will be based on a taught module in Data Science or will be given by an external speaker.
- The lunch at 12.20-12.50 will be provided for free, but should be well-deserved by an active participation in learning.
- The moderated workshop at 12.50-14.00 is for students to present and discuss their solutions to practical exercises.
- The underpinning modules are Introduction to Data Science (semester 1) and Advanced Data Science (semester 2).
- The sessions are usually in room 223 of the Holt building, see the Holt and Ashton buildings in the image above.
- 8 October 2019 : descriptive statistics
- 15 October 2019 : probability theory
- 22 October 2019 : statistical hypotheses
- 29 October 2019 : correlation and regression
- 5 November 2019 : clustering problems
- 12 November 2019 : equivalences and vectors
- 19 November 2019 : matrices of linear maps
- 26 November 2019 : invariants of linear maps
- 3 December 2019 : a change of a linear basis
- 10 December 2019 : Principal Component Analysis
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