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
- PhD training : autumn 2019, spring 2020
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 Marta Garcia-Finana (equality, diversity, inclusion) is an expert in Biostatistics.
- Dr Paolo Paoletti is a Senior Lecturer in Control in the School of Engineering.
- Dr Roberto Ferrero is a Lecturer in Electrical Engineering and Electronics.
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PhD projects: first cohort from Autumn 2019
- Student : Muizdeen Raji. Supervisors :
Nagesh Kalakonda,
Vitaliy Kurlin,
Joseph Slupsky.
Project : A study of cellular diversity in health and disease using mass cytometry.
Partner : Clatterbridge Cancer Centre, Wirral. -
Student : Peter Wright. Supervisors :
Paolo Paoletti,
Shan Luo,
Iain Hennessey.
Project : Machine Learning for the next generation of paediatric wheelchairs.
Partner : Alder Hey Children's Hospital, Liverpool. -
Student : Omar Elnaggar. Supervisors :
Shan Luo,
Paolo Paoletti,
Andrew Hopkinson.
Project : Deep Feature Learning for Distributed Rehabilitation Robots with Wearable Tactile Sensing.
Partner : Sensor City, Liverpool. -
Student : Aidan Watmuff. Supervisors :
Mark Green,
Shagufta Scanlon,
Huw Jenkins.
Project : Using AI to leverage new forms of data in modelling cycling behaviours in the Liverpool City Region.
Partner: Liverpool City Region Combined Authority. -
Student : Weiqiang Chen. Supervisors :
Yaochun Shen,
Yalin Zheng,
Stephen Kaye.
Project : An intelligent imaging technology for automatic characterisation of the refractive power of human eye.
Partner: Royal Liverpool and Broadgreen University Hospital Trust. -
Student : Yanhua Xu. Supervisors :
Dominik Wojtczak,
Neil French,
Roberto Vivancos.
Project : Machine Learning of Epidemic Models.
Partner: Public Health England. -
Student : Jing Qi. Supervisors :
Shagufta Scanlon,
Girvan Burnside,
Paul Charnley.
Project : An Intelligent Assistant for Medical Doctors when Prioritising Pathology Results.
Partner: Wirral University Teaching Hospital. -
Student : Mohamed Elhalwagy. Supervisors :
Philip Johnson,
Ahmed Elsheikh,
Vinzent Rolny.
Project : Application of AI systems to develop novel diagnostic and prognostic tools for Hepatocellular Carcinoma.
Partner: Roche Diagnostics.
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Call for supervisors to submit PhD projects to start in October 2020, deadline : 14 February 2020.
- Call for PhD projects in 2020 (doc, 46K)
- Example project proposal in 2019 (pdf, 94K)
- Blank advert for FindAPhD.com in 2020 (doc, 192K)
- Example advert for FindAPhD.com in 2019 (pdf, 123K)
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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 between 11.00-14.00 for about 20 PhD students as follows.
- In the spring 2020 the session are in GHolt 223 on Thursdays starting from Thursday 30th January 2020.
- The presentation at 11-12.00 will be on AI or Data Science topics given by Dr Vitaliy Kurlin or another speaker.
- The lunch at 12.00-12.30 is provided for free, but should be well-deserved by an active participation in learning.
- The moderated workshop at 12.30-14.00 is for students to discuss exercises or present on-going PhD projects.
- The underpinning modules are Introduction to Data Science (semester 1) and Advanced Data Science (semester 2).
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Introductory topics on Data Science covered in autumn 2019.
- 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 : linear maps (Dr Olga Anosova)
- 26 November 2019 : invariants of linear maps
- 3 December 2019 : how to change a linear basis
- 10 December 2019 : Principal Component Analysis
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Advanced topics on AI and Data Science covered in spring 2020.
- 6 February 2020 : Bayes theorem with examples
- 13 February 2020 : AI for Health (Prof Frans Coenen)
- 20 February 2020 : TBA
- 27 February 2020 : TBA
- 5 March 2020 : TBA
- 12 March 2020 : TBA
- 19 March 2020 : TBA
- 23 April 2020 : TBA
- 30 April 2020 : TBA
- 7 May 2020 : TBA
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