Publications

Google Scholar Profile

Peer-Reviewed Articles in Journals

Q. Liu, X. Gu, P. Henderson, H. Dai, F. Deligianni, Certainty-Guided Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation, submitted.
X. Gu, F. Deligianni, J. Han, X. Liu, W. Chen, G.Z. Yang, B. Lo, Beyond supervised learning for pervasive healthcare, IEEE Reviews in Biomedical Engineering, 2023.
N. Lai-Tan, M.G. Philiastides, F. Kawsar, F. Deligianni, Toward Personalized Music-Therapy: A Neurocomputational Modeling Perspective, IEEE Pervasive Computing, 2023.
E. Jacobs, F. Deligianni, F. Pollick, Threat Perception Modulation by Capturing Emotion, Motor and Empathetic System Responses: A Systematic Review, IEEE Transactions on Affective Computing, 2023.
S. Verma, M. Alkan, F. Deligianni, C. Anagnostopoulos, G. Diller, L. Walker, F.C. Johnston, M. Danton, H. Walker, L. Swan, A. Hunter, A. McGuire, M. Dawes, S. Stott, M. Lyndsey, N. Walker, G. Veldtman, Development of a semi-automated database for adult congenital heart disease patients, Canadian Journal of Cardiology, 2022.
S.P. Leighton, J.W. Herron, E. Jackson, M. Sheridan, F. Deligianni, Jonathan Cavanagh, Delirium and the risk of developing dementia: a cohort study of 12 949 patients, Journal of Neurology, Neurosurgery & Psychiatry, 2022.
R. Lee, S. Leighton, L. Thomas, G. Gkoutos, S. Wood, S-J Fenton, F. Deligianni, J. Cavanagh, P. Mallikarjun, Prediction models in first episode psychosis: a systematic review and critical appraisal, British Journal of Psychiatry, 2022.
Y. Guo, D. Freer, F. Deligianni and G.-Z. Yang, Eye-tracking for performance evaluation and workload estimation in space telerobotic training, IEEE Transactions on Human-Machine Systems, 52(1), 2022.
X. Gu, Y. Guo, F. Deligianni, B. Lo and G.-Z. Yang, Cross-subject and cross-modal transfer for generalized abnormal gait pattern recognition, IEEE Transactions on Neural Networks and Learning Systems, 2020.
X. Gu, Y. Guo, F. Deligianni and G.-Z. Yang, Coupled Real-Synthetic Domain Adaptation for Real-World Super-Resolution Depth Enhancement, IEEE Transactions on Image Processing, 2020.
F. Deligianni, Y. Guo and G.-Z. Yang, From Emotions to Mood Disorders: A Survey on Gait Analysis Methodology, IEEE Journal of Biomedical and Health Informatics, 23(6), 2019.
Y. Guo, F. Deligianni, X. Gu, and G.-Z. Yang, 3D Canonical Pose Estimation and Abnormal Gait Recognition, IEEE Robotics and Automation Letters-IROS, 4(4): 3617-3624, 2019.
F. Deligianni, C. Wong, B. Lo, G.Z. Yang, A fusion framework to estimate plantar ground force distributions and ankle dynamics Information Fusion, 41, 255-263, 2018.
D. Ravi, C. Wong, F. Deligianni, M. Berthelot, J. Andreu-Perez, B. Lo, G. Z. Yang, Deep Learning for Health Informatics, IEEE Journal of Biomedical and Health Informatics, 21(1), 2017.
F. Deligianni, D.W. Carmichael, Gary H. Zhang, C.A. Clark and J.D. Clayden, NODDI and tensor-based microstructural indices as predictors of functional connectivity, PLoS ONE, 11(4), 2016. (The raw data are available online)
C.S. Parker, F. Deligianni, M.J. Cardoso, P. Daga, M. Modat, M. Dayan, C.A. Clark and S. Ourseling, Consensus between pipelines in structural brain networks, PLoS ONE, 9(10), 2014.
F. Deligianni, M. Centeno, D.W. Carmichael and J.D. Clayden, Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands, Frontiers in Neuroscience, 8(258), 2014. (The raw data are available online) (Significance). An independent commentary article can be found here.
F. Deligianni, G. Varoquaux, B. Thirion, D.J. Sharp, C. Ledig, R. Leech and D. Rueckert, A Framework for Inter-Subject Prediction of Functional Connectivity from Structural Networks, IEEE Trans on Med Imaging, 32(12), 2200-2214, 2013. pdf
F. Deligianni, E. Robinson, A. Edwards, D. Rueckert, D. Sharp and D. Alexander, Hierarchy in Anatomical Brain Networks Derived from Diffusion Weighted Images in 64 and 15 Directions, Annals of the BMVA, 2012(4), 1-21, 2012. pdf
F. Deligianni, A. Senju, G. Gergely, and G. Csibra, Automated Gaze-Contingent Objects Elicit Orientation Following in 8-months-old infants, Dev Psychol, 47:1499-1503, 2011. pdf
T. Grossmann, M. Johnson, S. Lloyd-Fox, A. Blasi, F. Deligianni, C. Elwell, and G. Csibra, Early Cortical Specialisation for face-to-face Communication in Human Infants, Proc. R. Soc. B, 275, 2803-2811, 2008.
F. Deligianni, A. Chung, and G. Z. Yang, Non-Rigid 2D-3D Registration for Patient Specific Bronchoscopy Simulation with Statistical Shape Modelling, IEEE Trans on Med Imaging, 25(11): 1462-1471, 2006. pdf
A. J. Chung, F. Deligianni, P. Shah, A. Wells, and G. Z. Yang, Patient Specific Bronchoscopy Visualisation through BRDF Estimation and Disocclusion Correction, IEEE Trans of Med Imaging, 25(4): 503- 513, 2006.
A. J. Chung, F. Deligianni, X. P. Hu, and G. Z. Yang, Extraction of Visual Features with Eye Tracking for Saliency Driven 2D3D Registration, Image Vision Comput, 23: 999-1008, 2005.
F. Deligianni, A. Chung, and G. Z. Yang, Patient-Specific Bronchoscope Simulation with pq-Space-Based 2D-3D Registration, Comput Aid Surg, 9(5): 215-226, 2004. pdf
N. Grammalidis, N. Sarris, F. Deligianni, and M. G. Strintzis, Three-Dimensional Facial Adaptation for Mpeg-4 Talking Heads, EURASIP J Appl Si Pr, 10: 1005-1020, 2002.

Peer-Reviewed Articles-Abstracts in Conferences-Workshops

Q. Liu, P. Henderson, X. Gu, H. Dai, F. Deligianni, Learning Semi-Supervised Medical Image Segmentation from Spatial Registration, submitted.
K.B. Sivangi and F. Deligianni, Knowledge Distillation with Global Filters for Efficient Human Pose Estimation, The 35th British Machine Vision Conference (BMVC), 2024.
N. Lai-Tan, M. Philiastides, F. Deligianni, Fusion of Spatial and Riemannian Features to Enhance Detection of Gait Adaptation Mental States During Rhythmic Auditory Stimulation, International Conference on Affective Computing and Intelligent Interaction (ACII 2024), 2024.
T Aladwani, C Anagnostopoulos, S Puthiya Parambath, F Deligianni, CL-FML: Cluster-based & Label-aware Federated Meta-Learning for On-Demand Classification Tasks, IEEE International Conference on Data Science and Advanced Analytics, 2024.
D. Szczepaniak, M. Harvey, F. Deligianni, ML-Driven Cognitive Workload Estimation in a VR-based Sustained Attention Task, IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2024.
T Aladwani, SP Parambath, C Anagnostopoulos, F Deligianni, The Price of Labelling: A Two-Phase Federated Self-learning Approach, Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2024.
M. Alkan, G. Veldtman, F. Deligianni, Riemannian Prediction of Anatomical Diagnoses in Congenital Heart Disease based on 12-lead ECG's, IEEE International Symposium on Biomedical Imaging (IEEE ISBI), 2024.
A. Tragakis, Q. Liu, C. Kaul, S.K. Roy, H. Dai, F. Deligianni, R. Murray-Smith, D. Faccio, GLFNet: Global-Local (Frequency) Filter Networks for efficient Medical Image Segmentation, IEEE International Symposium on Biomedical Imaging (IEEE ISBI), 2024.
F. Dalla Serra, C. Wang, F. Deligianni, J. Dalton, and A. Q. O'Neil, Controllable Chest X-Ray Report Generation from Longitudinal Representations, Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.
M. Malek-Podjaski and F. Deligianni, Adversarial Attention for Human Motion Synthesis, IEEE Symposium Series on Computational Intelligence (SSCI), 2023.
N. Kaur, F. Deligianni, P. Pellicori, J.G.F. Clelland, Use of machine learning to predict mortality in patients with type 2 diabetes mellitus, according to socioeconomic status, European Heart Journal (abstract), 2023.
N. Kaur, P. Pellicori, F. Deligianni, J.G.F. Clelland, Use of machine learning to predict drivers of incident heart failure in patients with type 2 diabetes mellitus, Heart Failure (abstract), 2023.
Q. Liu, X. Gu, P. Henderson, F. Deligianni, Multi-Scale Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation, BMVC, 2023.
Q. Liu, C. Kaul, J. Wang, C. Anagnostopoulos, R. Murray-Smith, F. Deligianni, Optimizing Vision Transformers for Medical Image Segmentation, IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023.
T. Aladwani, C. Anagnostopoulos, K. Kolomvatsos, I. Alghamdi, F. Deligianni, Query-driven Edge Node Selection in Distributed Learning Environments, IEEE International Conference on Data Engineering, 2023.
F.D. Serra, W. Clackett, H. MacKinnon, C. Wang, F. Deligianni, J. Dalton, A.Q. O�Neil, Multimodal Generation of Radiology Reports using Knowledge-Grounded Extraction of Entities and Relations, Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022.
F.D. Serra, G. Jacenkow, F. Deligianni, J. Dalton, A.Q. O'Neil, Improving Image Representations via MoCo Pre-Training for Multimodal CXR Classification, MIUA, 2022.
M. Malek-Podjaski, F. Deligianni, Towards Explainable, Privacy-Preserved Human-Motion Affect Recognition, IEEE Symposium Series on Computational Intelligence, 2021.
I. Domingos, G.Z. Yang and F. Deligianni, Intention Detection of Gait Adaptation in Natural Settings�, IEEE Symposium Series on Computational Intelligence, 2021. (Best Runner Up Award - IEEE Brain)
Y. Jones, F. Deligianni and J Dalton, Improving ECG Classification Interpretability Using Saliency Maps, IEEE BIBE, 2020. (Best paper award)
F. Deligianni, J. Clayden and G-Z. Yang, Comparison of Brain Networks based on Predictive Models of Connectivity, IEEE BIBE, 2019. (Best paper award)
D. Freer, F. Deligianni and G.Z. Yang, Adaptive Riemannian BCI for Enhanced Motor Imagery Training Protocols, IEEE BSN, 2019. (ORAL PRESENTATION)
F. Deligianni, H. Singh, H. Modi, A. Darzi, D.R. Leff, G.Z Yang, Expertise Related Disparity in Prefrontal-Motor Brain Connectivity, HSMR, 2018. (ORAL PRESENTATION) pdf
I. Domingos, F. Deligianni, G.Z. Yang, Dry versus Wet EEG electrode systems in Motor Imagery Classification, The UK-RAS Network Conference on Robotics and Autonomous Systems, Bristol, 2018
D.D. Zhang, J.Q. Zheng, J. Fathi, M. Sun, F. Deligianni, G.Z Yang, Motor Imagery Classification based on RNNs with Spatiotemporal-Energy Feature Extraction, The UK-RAS Network Conference on Robotics and Autonomous Systems, Bristol, 2018.
X. Gu, F. Deligianni, B. Lo, W. Chen, G.Z. Yang, Markerless gait analysis based on a single RGB camera, IEEE BSN, 42-45, 2018. pdf
F. Deligianni, D.W. Carmichael, C.A. Clark and J.D. Clayden, NODDI and Tensor-based Microstructural Indices as Predictors of Functional Connectivity, ISMRM British Chapter, 2015. (ORAL PRESENTATION)
F. Deligianni, D.W. Carmichael, C.A. Clark and J.D. Clayden, A prediction framework of functional from structural connectomes reveals relationships between NODDI and tensor-based micro-structural indices, Symposium on Big Data Initiatives for Connectomics Research, International conference on Brain Informatics and Health, 2015. (ORAL PRESENTATION)
F. Deligianni, C.A. Clark and J.D. Clayden, Prediction of functional from structural connectomes across micro-structural indices, ISMRM British Chapter, 2014. (ORAL PRESENTATION)
F. Deligianni, M. Centeno, D.W. Carmichael and J.D. Clayden, Relating resting-state fMRI and EEG brain connectivity across frequency bands, ISMRM, 2014. (ORAL PRESENTATION) (OHBM14 pdf)
F. Deligianni, C.A. Clark and J.D. Clayden, Evaluating structural brain networks based on their performance in predicting functional connectivity, ISMRM, 2014.
C.S. Parker, F. Deligianni, M.J. Cardoso, P. Daga, M. Modat, C.A. Clark, S. Ourselin, J.D. Clayden, Consensus between pipelines in whole brain structural connectivity networks, ISMRM, 2014. (ORAL PRESENTATION)
F. Deligianni, C.A. Clark, and J.D. Clayden, A Framework to Compare Tractography Algorithms Based on their Performance in Predicting Functional Networks, MICCAI-MBIA, 2013. (ORAL PRESENTATION) pdf
F. Deligianni, M. Centeno, D.W. Carmichael and J.D. Clayden, Quantitative Agreement between fMRI and EEG Brain Connectivity Matrices in Different Frequency Bands, BaCI, 2013.
F. Deligianni, G. Varoquaux, B. Thirion, E. Robinson, D.J. Sharp, A. D. Edwards and D. Rueckert, Relating brain functional connectivity to anatomical connections: Model Selection, NIPS-MLNI, 2011. (ORAL PRESENTATION) pdf
F. Deligianni, G. Varoquaux, B. Thirion, E.Robinson, D.Sharp, A.Edwards, and D.Rueckert, A Probabilistic Framework to Infer Brain Functional Connectivity from Anatomical Connections, IPMI, 296-307, 2011. pdf
F. Deligianni, E. C. Robinson, D. Sharp, A. D. Edwards, D. Rueckert, and D. C. Alexander, Exploiting Hierarchy in Structural Brain Networks, ISBI, 871-874, 2011. (ORAL PRESENTATION) pdf
F. Deligianni, E. C. Robinson, C. F. Beckmann, D. Sharp, A. D. Edwards, and D. Rueckert, Inference of Functional Connectivity from Direct and Indirect Structural Brain Connections, ISBI, 849-852, 2011. pdf
F. Deligianni, E. C. Robinson, C. F. Beckmann, D. Sharp, A. D. Edwards, and D. Rueckert, Inference of Functional Connectivity from Structural Brain Connectivity, ISBI, 1113-1116, 2010. pdf
E. C. Robinson, F. Deligianni, A. Hammers, D. Rueckert and A. D. Edwards, A Probabilistic White Matter Atlas Approach to Assessing Age Related Changes in the Brain, ISMRM, 2010.
A. Senju, F. Deligianni, G. Gergely, and G. Csibra, Gaze Following Depends on a Preceding Ostensive Signal in Early Infancy, Workshop on Pragmatic Development, Lyon, France, 2009.
F. Deligianni, A. Chung, and G.-Z. Yang, Non-Rigid 2D-3D Registration with Catheter Tip EM Tracking for Patient Specific Bronchoscope Simulation, MICCAI, 281-288, 2006. (ORAL PRESENTATION) pdf
B. Lo, F. Deligianni, and G.-Z. Yang, Source Recovery for Body Sensor Network, BSN, 199-202, 2006.
D. Leff, H. Peck, R. Aggarwal, F. Deligianni, C. Elwell, D. Delpy, G. Yang, and A. Darzi, Optical Mapping of the Frontal Cortex During Learning of a Surgical Knot-Tying Task, a Pilot Study, HBM, 140-147, 2006.
D. Leff, P. Koh, R. Aggarwal, J. Leong, F. Deligianni, C. Elwell, D. Delpy, A. Darzi, G. Yang, Optical Mapping of the Frontal Cortex During a Surgical Knot-Tying Task, Feasibility Study, MICCAI, 140-7, 2006.
F. Deligianni, A. Chung, and G. Z. Yang, Predictive Camera Tracking for Bronchoscope Simulation with Condensation, MICCAI, 910-916, 2005. pdf
D. Stoyanov, G. P. Mylonas, F. Deligianni, A. Darzi, and G. Z. Yang, Soft-Tissue Motion Tracking and Structure Estimation for Robotic Assisted Mis Procedures, MICCAI, 139-146, 2005.
G. P. Mylonas, D. Stoyanov, F. Deligianni, A. Darzi, and G. Z. Yang, Gaze-Contingent Soft Tissue Deformation Tracking for Minimally Invasive Robotic Surgery, MICCAI, 843-850, 2005.
A. Chung, F. Deligianni, M. Elhelw, P. Shah, A. Wells, and G. Z. Yang, Assessing Realism of Virtual Bronchoscopy Images Via Specialist Survey and Eye-Tracking, MIPS XI, 2005.
A. J. Chung, F. Deligianni, P. Shah, A. Wells, and G. Z. Yang, Video Driven Finite Element Deformation Models for Surgical Simulation, Communication, MICCAI, 2005.
F. Deligianni, A. Chung, and G. Z. Yang, Decoupling of Respiratory Motion with Wavelet and Principal Component Analysis, MIUA, 13-16, 2004. (ORAL PRESENTATION) pdf
A. J. Chung, P. J. Edwards, F. Deligianni, and G. Z. Yang, Freehand Cocalibration of an Optical and Electromagnetic Tracker for Navigated Bronchoscopy, MIAR, 320-328, 2004.
A. J. Chung, F. Deligianni, P. Shah, A. Wells, and G. Z. Yang, Enhancement of Visual Realism with BRDF for Patient Specific Bronchoscopy Simulation, MICCAI, 486-493, 2004.
A. J. Chung, F. Deligianni, X.-P. Hu, and G. Z. Yang, Visual Feature Extraction Via Eye Tracking for Saliency Driven 2D-3D Registration, ETRA, 49-54, 2004.
F. Deligianni, A. Chung, and G. Z. Yang, pq-Space Based 2D-3D Registration for Endoscope Tracking, 'MICCAI’, 311-318, 2003. (ORAL PRESENTATION) pdf
J. X. Gao, S. Masood, F. Deligianni, and G. Z. Yang, Reconstruction of 3D Deformation from 2D MR Velocity Mapping with Incompressibility Constraints, IEEE EMBS, 134-137, 2003.

Book Chapters - White Papers

Y. Jones, F. Deligianni, J. Dalton, P. Pellicori, J.G.F. Cleland, Consensus of state of the art mortality prediction models: From all-cause mortality to sudden death prediction, 2023.
T. Aladwani, K. Kolomvatsos, F. Deligianni, and C. Anagnostopoulos, Intelligent Data Management in UAV-enabled Mobile Edge Computing: A Review, in Emerging Intelligent Decision Management Systems: Applications and Challenges, Eds. P. Pattnaik; H. Das, Wiley, 2021.
S. Khan, B. Rosa, P. Kassanos, C.F. Miller, F. Deligianni, and G.-Z. Yang, Physiological adaptations in space and wearable technology for biosignal monitoring, in Space Robotics and Autonomous Systems, IET, 2021.
F. Deligianni, D. Freer and Y. Guo, BCI for Mental Workload Detection and Performance Evaluation in Space Applications, in Space Robotics and Autonomous Systems, in Space Robotics and Autonomous Systems, IET, 2021. (pdf)
D. Freer, Y. Guo, F. Deligianni and G-Z. Yang, A multi-modal Sensing Platform to Monitor Workload During Telerobotic Operations in Space, 2020.
F. Deligianni et al. Expertise and Task Pressure in fNIRS-based brain Connectomes, 2020.
F. Deligianni, G. Dagnino, G.Z. Yang (eds), Proceedings of the Hamlyn Symposium on Medical Robotics 2019.
F. Deligianni, G.Z. Yang (eds), Proceedings of the Hamlyn Symposium on Medical Robotics 2018.
R. J. Varghese, D. Freer, F. Deligianni, J. Liu, G.Z. Yang, Wearable Robotics for Upper-Limb Rehabilitation and Assistance: A Review on the State-of-the-art, Challenges and Future Research, Chapter in Wearable Technology in Medicine and Healthcare, Elsevier, 2018.
J. Andreu-Perez, F. Deligianni, D. Ravi, G. Z. Yang, Artificial Intelligence and Robotics, UK-RAS White Papers, 2017.

Online Available Datasets

J. Clayden and F. Deligianni, EEG, fMRI and NODDI Dataset, Open Science Framework, 2016.

Graduate Research

Invited talks

Invited lecture on Artificial Intelligence in Pervasive Well-Being and Health at the ML in Science conference at University of Glasgow, August 2024.
Invited lecture on The Role of AI in Pervasive Well-Being & Health, at University of Limassol, February 2024.
Invited talk on AI in Healthcare Applications, at BioTech AI-pocalypse: Unleashing the Future of Biotechnology, Pint of Science Festival, May 2025.
Invited lecture on Human Centered ML, at Nordic Probabilistic AI School, June 2022 (slides can be found here).
Invited talk on Predictive Modelling with Neurophysiological Data, at MSc Biorobotics University of Bristol, November 2021.
Invited talk on Predictive Modelling with Medical Imaging Data, at Summer School in Photonic Imaging, Sensing & Analysis, June 2021.
Invited talk on Artificial Intelligence in Wearable Sensing: Challenges and Opportunities, at at Institute for Digital Communications, Edinburgh University, November 2020.
Invited talk on From Wearable Sensing to Human-AI Augmentation Models, at Colloquia in Intelligent Sensing, Measurement and Actuators, The Future of Intelligent Sensing and Measurement, November 2020.
Departamental talk on Predictive Analytics in Brain Networks and Gait Analysis, Computer Science Department, Aston University, July 2019.
Invited talk on Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands at the NIHR Biomedical Research Center, King�s College on the 14th of January 2015.
Invited talk on Inter-Subject Relationships of Brain Connectomes Across Modalities at the CUBRIC, Cardiff University on the 1st of December 2014.

Media Attention

How robots in space could lead to better healthcare on Earth
Imperial College podcast: Moon Landing Special
- Human-Robotic-Interactions in Space
Imperial Lates: Smart Fashion - wearable technology for human-robot collaborative tasks in space

Other Awards and Activities

Associate Member of the IEEE Bio Imaging and Signal Processing (BISP) Technical Committee, 2023-present.
Associate Edittor of Royal Society Open Science, 2023-present.
Associate Edittor of IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022-present.
BMVC industrial chair, 2024.
Program committee of ICRA workshop, 2024.
Co-organiser of IEEE 8th World Forum on Internet of Things (WF-IoT), 2022.
Co-chair of IEEE Engineering in Medicine and Biology Society - Novel Sensing and Applications, 2022.
Co-chair of Computational Intelligence for Brain Computer Interfaces, IEEE SSCI 2021, 2022, 2023.
Special Issue on Wearable and Ambient Sensing: Technological Advances in Human Motion Analysis in Digital Health, Frontiers.
Co-editor and organiser of the Hamlyn Symposium on Medical Robotics, 2019.
Organiser of the Workshop on BCI and Human AI augmentation - HSMR, 2019.
Co-editor and organiser of Hamlyn Symposium on Medical Robotics, 2018.
Organiser of the Workshop on BCI and Human AI augmentation - HSMR, 2018.
EPSRC New Investigator Award, 2022-2025.
Semi-flex Grant, Royal Society, 2022-2023.
EPSRC Network grant: Human Motion Analysis - Agency, Negotiation and Legibility in Data Handling, 2020-2021.
Best Runner Up Award - IEEE Brain (IEEE Symposium Series on Computational Intelligence), 2021.
Best Paper Award in Bioengineering (IEEE 20th International Conference on Bioinformatics and Bioengineering), 2020.
Best Paper Award (IEEE 19th International Conference on Bioinformatics and Bioengineering), 2019.
MRC Training Fellow, 2008 - 2011.