Alan Turing Institute Fellows
The Alan Turing Institute (known as the Turing) was created in 2015 as the national Institute for Data Science and AI. The University of Exeter is one of 13 partner Universities that the Turing has. Over 400 researchers collaborate at the Turing, including 147 Turing Fellows from across the 13 partner Universities. Exeter formally joined the Turing network in April 2018. In October 2018 22 Exeter researchers were awarded prestigious Turing Fellowships, and in February 2019 a further three Exeter researchers were awarded Fellowships; taking Exeter's total number up to 25.
Turing Fellows are established scholars with proven research excellence in data science, artificial intelligence, or a related field. They contribute to new ideas, drive collaborative projects, secure external funding and provide research expertise which is actively connected with the Institute and its network of universities and industry partners.
| Name | Turing Fellowship title/details |
|---|---|
| David Llewellyn | Advanced machine learning for dementia identification and targeted interventions |
| Guangtao Fu | Data analytics for smart urban water infrastructure |
| Danny Williamson | Development of UQ technology for tuning climate models/Foundations research on how the product of data science/AI can be defensibly interpreted as “uncertainty” and can be used to make optimal decisions |
| Mark Kelson | Data science for accelerometry for health/Data science for clinical trials data on mental health |
| Leon Danon | Infectious disease surveillance tool using mobile phone records/Targeting antimicrobial stewardship efforts in primary care using prescription data |
| Hywel Williams | Digital media & climate change. |
| Tim Dodwell | Data-driven, simulation informed, high value manufacturing |
| Federico Caprotti | Integrating smart health data and policy frameworks: mobile DNA sequencing and smart healthcare/ |
| Krasimira Tsaneva-Atanasova | Virtual Reality Based Diagnosis and Therapy for Mental Health/Learning in the Model Space and Data Assimilation for large biomedical datasets |
| Jonathan Phillips | Controlling protein molecules to perform biochemical computing: Uniquely addressable protein logic gates/Protein computing |
| Niccolo Tempini | The social role of data in health artificial intelligence/Soft methodologies for data analytics infrastructure design and development |
| Susan Banducci | Information, Negativity and Democracy/ (Mis)Information & Trust -- Large Scale Online Randomized Experiments |
| Nicolas Pugeault | Computer vision, Machine Learning and Autonomous Robotics: Developmental scaffolding for Deep Reinforcement Learning/Learning Visual Attention for Driving |
| Anastasios Roussos | Statistical 3D skull modelling/3D vision and machine learning for sign language translation |
| Peter Challenor | Uncertainty Quantification (UQ) for Black-Box Computational Models with Application to Machine Decisions |
| Sabina Leonelli | From Field Data to Global Indicators: Towards a Framework for Intelligent Plant Data Linkage |
| Gavin Shaddick | Data Science for Sustainable Development: Environment, Climate and Health |
| Tim Lenton | Data Science for Sustainable Development: Environment, Climate and Health |
| Lora Fleming | Data Science for Sustainable Development: Environment, Climate and Health |
| Karyn Morrissey | Data Science for Sustainable Development: Environment, Climate and Health |
| Richard Everson | Data Science for Sustainable Development: Environment, Climate and Health |
| Alberto Arribas | Data Science for Sustainable Development: Environment, Climate and Health |
| David Lopez | Personalised Education |
| Alan Brown | Accelerating the Impact of Artificial Intelligence in UK Government |
| David Plans | Workplace Organisational Neuroscience Deployment (Intervention/Pre-Diagnostic) / Mental Health Risk Modelling |