Outputs

Publications, talks, public engagement activities and other outputs generated by the CDT students.

Publications

2024

Leonardo V Castorina, Suleyman Mert Ünal, Kartic Subr, Christopher W Wood (2024) TIMED-Design: flexible and accessible protein sequence design with convolutional neural networks. Protein Engineering, Design and Selection, Volume 37, 2024, gzae002 https://academic.oup.com/peds/article-abstract/doi/10.1093/protein/gzae002/7591701

Filippo Corponi, Bryan M. Li, Gerard Anmella, Ariadna Mas, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antoni Benabarre,Marina Garriga, Eduard Vieta, Stephen M. Lawrie, Heather C. Whalley, Diego Hidalgo-Mazzei, Antonio Vergari (2024) Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number. Nature: Translational Psychiatry. https://www.nature.com/articles/s41398-024-02876-1

Raman Dutt, Linus Ericsson, Pedro Sanchez, Sotirios A. Tsaftaris, Timothy Hospedales (2024)  Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity. https://arxiv.org/abs/2305.08252

Raman Dutt, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy Hospedales (2024)  FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis. International Conference on Learning Representations (ICLR 2024).  https://arxiv.org/abs/2310.05055

Hitoshi Tabuchi, Justin Engelmann, Fumiatsu Maeda, Ryo Nishikawa, Toshihiko Nagasawa, Tomofusa Yamauchi, Mao Tanabe, Masahiro Akada, Keita Kihara, Yasuyuki Nakae, Yoshiaki Kiuchi, Miguel O Bernabeu (2024) Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images. British Journal of Opthalmology. https://bjo.bmj.com/content/early/2024/03/14/bjo-2023-324923.abstract

Justin Engelmann, Diana Moukaddem, Lucas Gago, Niall Strang, Miguel O Bernabeu (2024) Applicability of oculomics for individual risk prediction: Repeatability and robustness of retinal Fractal Dimension using DART and AutoMorph. Arxiv pre-print. https://arxiv.org/abs/2403.06950

(Preprint) Aryo Pradipta Gema, Michał Kobiela, Achille Fraisse, Ajitha Rajan, Diego A. Oyarzún, Javier Antonio Alfaro (2024) Vaxformer: Antigenicity-controlled Transformer for Vaccine Design Against SARS-CoV-2.  https://arxiv.org/abs/2305.11194

Rohan Gorantla, Alžbeta Kubincová, Benjamin Suutari, Benjamin P. Cossins, Antonia S. J. S. Mey (2024)  Benchmarking Active Learning Protocols for Ligand-Binding Affinity Prediction.  ACS 2024. https://pubs.acs.org/doi/10.1021/acs.jcim.4c00220

Gerard Anmella, Ariadna Mas, Miriam Sanabra, Clàudia Valenzuela-Pascual, Marc Valentí, Isabella Pacchiarotti, Antoni Benabarre, Iria Grande, Michele De Prisco, Vincenzo Oliva, Giovanna Fico, Anna Giménez-Palomo, Anna Bastidas, Isabel Agasi, Allan H. Young, Marina Garriga, Filippo CorponiBryan M. Li, Peter de Looff, Eduard Vieta, Diego Hidalgo-Mazzei (2024)  Electrodermal activity in bipolar disorder: Differences between mood episodes and clinical remission using a wearable device in a real-world clinical setting.  Journal of Affective Disorders. https://www.sciencedirect.com/science/article/pii/S0165032723013149

(Preprint) Robin Williams, Stuart Anderson, Kathrin Cresswell, Mari Serine Kannelonning, Hajar Mozaffar, Xiao Yang (2024)  Domesticating AI in medical diagnosis. Technology in Society. https://www.sciencedirect.com/science/article/pii/S0160791X24000174?via%3Dihub 

2023

Lauren Watson, Zeno Kujawa, Rayna Andreeva, Hao-Tsung Yang, Tariq Elahi, Rik Sarkar (2023)  Accelerated Shapley Value Approximation for Data Evaluation. https://arxiv.org/pdf/2311.05346.pdf

Rayna Andreeva, Anwesha Sarkar, Rik Sarkar (2023)  Machine learning and Topological data analysis identify unique features of human papillae in 3D scans.  https://arxiv.org/abs/2307.06255

Rayna Andreeva, Katharina Limbeck, Bastian Rieck, Rik Sarkar (2023)  Metric Space Magnitude and Generalisation in Neural Networks.  Proceedings of 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), PMLR 221:242-253. https://proceedings.mlr.press/v221/andreeva23a/andreeva23a.pdf

Leonardo V Castorina, Filippo Grazioli, Pierre Machart, Anja Moesch, Federico Errica (2023) Assessing the Generalization Capabilities of TCR Binding Predictors via Peptide Distance Analysis. Biorxiv. https://www.biorxiv.org/content/10.1101/2023.07.29.551100.abstract

Filippo Grazioli, Pierre Machart, Anja Mösch, Kai Li, Leonardo V Castorina, Nico Pfeifer, Martin Renqiang Min (2023) Attentive Variational Information Bottleneck for TCR–peptide interaction prediction.  Bioinformatics, Volume 39, Issue 1, January 2023, btac820. https://academic.oup.com/bioinformatics/article-abstract/39/1/btac820/6960920

Leonardo V. Castorina, Rokas Petrenas, Kartic Subr, Christopher W Wood (2023) PDBench: Evaluating Computational Methods for Protein-Sequence Design. Bioinformatics https://doi.org/10.1093/bioinformatics/btad027

Gerard Anmella,   Filippo Corponi, Bryan M Li, Ariadna Mas, Miriam Sanabra, Isabella Pacchiarotti, Marc Valenti, Iria Grande, Antoni Benabarre , Anna Giménez-Palomo, Marina Garriga, Isabel Agasi, Anna Bastidas, Myriam Cavero, Tabatha Fernández-Plaza, Néstor Arbelo, Miquel Bioque, Clemente García-Rizo, Norma Verdolini, Santiago Madero, Andrea Murru, Silvia Amoretti, Anabel Martínez-Aran, Victoria Ruiz, Giovanna Fico, Michele De Prisco, Vincenzo Oliva, Aleix Solanes, Joaquim Radua, Ludovic Samalin, Allan H Young, Eduard Vieta, Antonio Vergari, Diego Hidalgo-Mazzei (2023) Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study.  JMIR Mhealth Uhealth 2023;11:e45405.  https://mhealth.jmir.org/2023/1/e45405

Filippo Corponi, Antoine Lefrere, Marion Leboyer, Frank Bellivier, Ophelia Godin, Josephine Loftus, Philippe Courtet, Caroline Dubertret, Emmanuel Haffen, Pierre Michel Llorca, Paul Roux, Mircea Polosan, Raymund Schwan, Ludovic Samalin, Emilie Olié, Bruno Etain, FACE-BD (FondaMental Academic Centers of Expertise for Bipolar Disorder) Groups, Peggy Seriès, Raoul Belzeaux (2023) Definition of early age at onset in bipolar disorder according to distinctive neurodevelopmental pathways: insights from the FACE-BD study. Psychological Medicine.  https://www.cambridge.org/core/journals/psychological-medicine/article/abs/definition-of-early-age-at-onset-in-bipolar-disorder-according-to-distinctive-neurodevelopmental-pathways-insights-from-the-facebd-study/DD12195A96AC2375D3B20EC5B19A93B1

Bryan M. Li, Filippo Corponi, Gerard Anmella, Ariadna Mas, Miriam Sanabra, Diego Hidalgo-Mazzei, Antonio Vergari (2023) Inferring mood disorder symptoms from multivariate time-series sensory data. NeurIPS.  https://openreview.net/forum?id=awjU8fCDZjS

Eleanor Davyson, Xueyi Shen, Danni A. Gadd, Elena Bernabeu, Robert F. Hillary, Daniel L. McCartney, Mark Adams, Riccardo Marioni, and Andrew M. McIntosh (2023)  Metabolomic Investigation of Major Depressive Disorder Identifies a Potentially Causal Association With Polyunsaturated Fatty Acids. Society of Biological Psychiatry.  https://www.biologicalpsychiatryjournal.com/article/S0006-3223(23)00055-0/fulltext#%20 and mental Elf blog https://www.nationalelfservice.net/mental-health/depression/does-what-you-eat-affect-how-you-feel/

Justin Engelmann, Amos Storkey, Miguel O. Bernabeu (2023); Deep learning (DL) identifies age as key axis of perceptual variation in fundus images – without training on fundus images. Invest. Ophthalmol. Vis. Sci. 2023;64(9):PB004.  https://iovs.arvojournals.org/article.aspx?articleid=2791219

Justin Engelmann, Amos Storkey, Miguel O. Bernabeu (2023); Exclusion of poor quality fundus images biases health research linking retinal traits and systemic health. Invest. Ophthalmol. Vis. Sci. 2023;64(8):2922. https://iovs.arvojournals.org/article.aspx?articleid=2789909

Justin Engelmann, Jamie Burke, Charlene Hamid, Megan Reid-Schachter, Dan Pugh, Neeraj Dhaun, Diana Moukaddem, Lyle Gray, Niall Strang, Paul McGraw, Amos Storkey, Paul J Steptoe, Stuart King, Tom MacGillivray, Miguel O Bernabeu, Ian JC MacCormick (2023) Choroidalyzer: An open-source, end-to-end pipeline for choroidal analysis in optical coherence tomography. Arxiv pre-print. https://arxiv.org/abs/2312.02956v1

Jamie Burke, Justin Engelmann, Charlene Hamid, Megan Reid-Schachter, Tom Pearson, Dan Pugh, Neeraj Dhaun, Amos Storkey, Stuart King, Tom J MacGillivray, Miguel O Bernabeu, Ian JC MacCormick (2023) An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography. Translational Vision Science & Technology. https://tvst.arvojournals.org/article.aspx?articleid=2793042

Justin Engelmann, Amos Storkey, Miguel O Bernabeu (2023) QuickQual: Lightweight, convenient retinal image quality scoring with off-the-shelf pretrained models. International Workshop on Ophthalmic Medical Image Analysis, Lecture Notes in Computer Science pp 32–41. https://link.springer.com/chapter/10.1007/978-3-031-44013-7_4

Alessandro Fontanella, A Antoniou, W Li, J Wardlaw, G Mair, E Truco, A Storkey (2023)  ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging. To appear at the International Conference on Machine Learning (ICML).  https://arxiv.org/abs/2303.15421

Wenwen Li, Grant Mair, Alessandro Fontanella, Antreas Antoniou, Eleanor Platt , Chloe Martin, Paul Armitage , Emanuele Trucco, Amos Storkey, Joanna Wardlaw (2023) Challenges of building medical image datasets for development of deep learning software in stroke. https://arxiv.org/abs/2309.15081

Georges Bedran, Hans-Christof Gasser, Kenneth Weke, Tongjie Wang, Dominika Bedran, Alexander Laird, Christophe Battail, Fabio Massimo Zanzotto, Catia Pesquita, Håkan Axelson, Ajitha Rajan, David J. Harrison, Aleksander Palkowski, Maciej Pawlik, Maciej Parys, J. Robert O'Neill, Paul M. Brennan, Stefan N. Symeonides, David R. Goodlett, Kevin Litchfield, Robin Fahraeus, Ted R. Hupp, Sachin Kote, Javier A. Alfaro (2023)  The Immunopeptidome from a Genomic Perspective: Establishing the Noncanonical Landscape of MHC Class I-Associated Peptides. Cancer Immunol Res (2023) 11 (6): 747–762. https://doi.org/10.1158/2326-6066.CIR-22-0621

Hans-Christof Gasser, Diego Oyarzun, Ajitha Rajan, Javier Alfaro (2023)  Comparing a language model and a physics-based approach to modify MHC Class-I immune-visibility for the design of vaccines and therapeutics. bioRxiv 2023. https://www.biorxiv.org/content/10.1101/2023.07.10.548300v3

(Preprint) Aryo Pradipta Gema, Michał Kobiela, Achille Fraisse, Ajitha Rajan, Diego A Oyarzún, Javier Antonio Alfaro, (2023).  Vaxformer: Antigenicity-controlled Transformer for Vaccine Design Against SARS-CoV-2. ArXiv.  https://arxiv.org/pdf/2305.11194.pdf

(Preprint) Aryo Pradipta Gema, Dominik Grabarczyk, Wolf De Wulf, and Piyush Borole, Javier Antonio Alfaro, Pasquale Minervini, Antonio Vergari, Ajitha Rajan, (2023) Knowledge Graph Embeddings in the Biomedical Domain: Are They Useful? A Look at Link Prediction, Rule Learning, and Downstream Polypharmacy Tasks.   ArXiv. https://arxiv.org/abs/2305.19979

(Preprint) Aryo Pradipta Gema, Luke Daines, Pasquale Minervini, Beatrice Alex (2023).  Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain. ArXiv. https://arxiv.org/pdf/2307.03042.pdf

(Preprint) Bryan M. Li, Isabel M. Cornacchia, Nathalie L. Rochefort, Arno Onken (2023)  V1T: large-scale mouse V1 response prediction using a Vision Transformer.  https://arxiv.org/abs/2302.03023

(Preprint) Filippo CorponiBryan M. Li, Gerard Anmella, Clàudia Valenzuela-Pascual, Ariadna Mas, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antonio Benabarre, Marina Garriga, Eduard Vieta, Allan H Young, Stephen M. Lawrie, Heather C. Whalley, Diego Hidalgo-Mazzei, Antonio Vergari (2023)  Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised learning. https://arxiv.org/abs/2311.04215

(Preprint) Filippo Corponi*, Bryan M. Li*, Gerard Anmella, Ariadna Mas, Miriam Sanabra, Eduard Vieta, INTREPIBD Group, Stephen M. Lawrie, Heather C. Whalley, Diego Hidalgo-Mazzei, Antonio Vergari (2023)  Automated mood disorder symptoms monitoring from multivariate time-series sensory data: Getting the full picture beyond a single number. https://www.medrxiv.org/content/10.1101/2023.03.25.23287744v1

Gerard Anmella*, Filippo Corponi*, Bryan M. Li*, Ariadna Mas, Miriam Sanabra, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antoni Benabarre, Anna Giménez-Palomo, Marina Garriga, Isabel Agasi, Anna Bastidas, Myriam Cavero, Tabatha Fernández-Plaza, Néstor Arbelo, Miquel Bioque, Clemente García-Rizo, Norma Verdolini, Santiago Madero, Andrea Murru, Silvia Amoretti, Anabel Martínez-Aran, Victoria Ruiz, Giovanna Fico, Michele De Prisco, Vincenzo Oliva, Aleix Solanes, Joaquim Radua, Ludovic Samalin, Allan H. Young, Eduard Vieta, Antonio Vergari, Diego Hidalgo-Mazzei (2023) Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study. Journal of Medical Internet Research (JMIR) mHealth and uHealth. https://www.medrxiv.org/content/10.1101/2023.03.25.23287744v1

Charlotte Merzbacher, Diego Oyarzun (2023) Applications of artificial intelligence and machine learning in dynamic pathway engineering. Biochemical Society Transactions. https://pubmed.ncbi.nlm.nih.gov/37656433/

Charlotte Merzbacher , Barry Ryan , Thibaut Goldsborough, Robert F Hillary , Archie Campbell , Lee Murphy , Andrew M McIntosh, David Liewald, Sarah E Harris, Allan F McRae , Simon R Cox , Timothy I Cannings , Catalina A Vallejos, Daniel L McCartney, Riccardo E Marioni (2023) Integration of DNA methylation datasets for individual prediction of DNA methylation-based biomarkers. Genome Biology. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-023-03114-5

Charlotte Merzbacher, Oisin Mac Aodha, Diego Oyarzun (2023) Bayesian optimization for design of multiscale biological circuits. ACS Synthetic Biology. ACS Synthetic Biology. https://pubs.acs.org/doi/10.1021/acssynbio.3c00120

Jonathan Feldstein, Dominic Phillips, Efthymia Tsamoura (2023)  Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical Models.  Proceedings of the AAAI Conference on Artificial Intelligence, 37. 10 edn, vol. 37. https://arxiv.org/abs/2302.04599

Dominic Phillips, Charles Matthews, Benedict Leimkuhler (2023)  Numerical Methods with Coordinate Transforms for Efficient Brownian Dynamics Simulations. https://arxiv.org/abs/2307.02913

Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy Hospedales (2023)   Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn.  IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023. https://openaccess.thecvf.com/content/CVPR2023/html/Bohdal_Meta_Omnium_A_Benchmark_for_General-Purpose_Learning-To-Learn_CVPR_2023_paper.html

2022

(Preprint) Laura Watson, Rayna Andreeva, Hao-Tsung Yang, Rik Sarkar (2022) Differentially Private Shapley Values for Data Evaluation. https://arxiv.org/abs/2206.00511

Leonardo V. Castorina, Kartic Subr, Christopher W. Wood (2022) TIMED-Design: Efficient Protein Sequence Design with Deep Learning. Zenodo https://doi.org/10.5281/zenodo.6997495 

Justin Engelmann, Alice D. McTrusty, Ian J. C. MacCormick, Emma Pead, Amos Storkey & Miguel O. Bernabeu (2022) Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning. Nature machine intelligence. https://www.nature.com/articles/s42256-022-00566-5

Justin Engelmann, Ana Villaplana-Velasco, Amos Storkey & Miguel O. Bernabeu (2022) Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation. Ophthalmic Medical Image Analysis. OMIA 2022. Lecture Notes in Computer Science, vol 13576. https://link.springer.com/chapter/10.1007/978-3-031-16525-2_9

Dominic Phillips, Hans-Christof Gasser, Sebestyén Kamp, Aleksander Pałkowski, Lukasz Rabalski, Diego A. Oyarzún, Ajitha Rajan, Javier Antonio Alfaro (2022)  Generating Immune-aware SARS-CoV-2 Spike Proteins for Universal Vaccine Design.  Proceedings of the 1st Workshop on Healthcare AI and COVID-19, ICML 2022, PMLR 184:100-116, 2022. https://proceedings.mlr.press/v184/phillips22a.html 

(Preprint)  Olivier Labayle Pabet, Kelsey Tetley-Campbell, Mark Van Der Laan, Chris P. Ponting, Sjoerd Viktor Beentjes, Ava Khamseh (2022) Dispensing with unnecessary assumptions in population genetics analysis  https://www.biorxiv.org/content/10.1101/2022.09.12.507656v1

Bryan M. Li, Leonardo V. Castorina, Maria del C. Valdés-Hernández, Una Clancy, Stewart J. Wiseman, Eleni Sakka, Amos J. Storkey, Daniela Jaime Garcia, Yajun Cheng, Fergus Doubal, Michael T. Thrippleton, Michael Stringer, Joanna M. Wardlaw (2022)  Deep attention super-resolution of brain magnetic resonance images acquired under clinical protocols. Frontiers in Computational Neuroscience. https://www.frontiersin.org/articles/10.3389/fncom.2022.887633/full

Bryan M. Li*, Filippo Corponi*, Gerard Anmella, Ariadna Mas, Miriam Sanabra, Diego Hidalgo-Mazzei, Antonio Vergari (2022)  Inferring mood disorder symptoms from multivariate time-series sensory data. NeurIPS Workshop on Learning from Time Series for Health. https://openreview.net/forum?id=awjU8fCDZjS

2021

Beltramo, G., Skraba, P., Andreeva, Rayna, Sarkar, R., Giarratano, Y. and Bernabeu, M., (2021). Euler characteristic surfaces. Foundations of Data Sciences http://dx.doi.org/10.3934/fods.2021027

Saadat-Yazdi A., Andreeva Rayna, Sarkar R. (2021) Topological Detection of Alzheimer’s Disease Using Betti Curves. In: Reyes M. et al. (eds) Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data. IMIMIC 2021, TDA4MedicalData 2021. Lecture Notes in Computer Science, vol 12929. Springer, Cham. https://doi.org/10.1007/978-3-030-87444-5_12

Angeletos Chrysaitis Nikitas, Jardri R, Denève S, Seriès P (2021) No increased circular inference in adults with high levels of autistic traits or autism. PLOS Computational Biology 17(9): e1009006. https://doi.org/10.1371/journal.pcbi.1009006

Leonardo V. Castorina, Bryan M. Li, Amos Storkey, Maria. Valdés Hernández (2021) Metrics for quality control of results from super-resolution machine-learning algorithms – Data extracted from publications in the period 2017- May 2021. University of Edinburgh. Centre for Clinical Brain Sciences and School of Informatics. https://doi.org/10.7488/ds/3062

Filippo Corponi, Zorkina, Y., Stahl, D., Murru, A., Vieta, E., Serretti, A., Morozova, А., Reznik, A., Kostyuk, G. and Chekhonin, V.P. (2021). Frontal lobes dysfunction across clinical clusters of acute schizophrenia. Revista de Psiquiatría y Salud Mental. https://doi.org/10.1016/j.rpsm.2021.12.002

Matúš Falis, Dong, H., Birch, A., & Alex, B. (Accepted/In press). CoPHE: A Count-Preserving Hierarchical Evaluation Metric in Large-Scale Multi-Label Text Classification. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021)

Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort, Arno Onken (2021)  Neuronal Learning Analysis using Cycle-Consistent Adversarial Networks (Preprint). https://arxiv.org/abs/2111.13073

(Preprint) Super-Resolution of Magnetic Resonance Images Acquired Under Clinical Protocols using Deep Attention-based Method. Bryan Li, Leonardo Castorina, Maria del C. Valdés-Hernández, Una Clancy, Stewart J. Wiseman, Eleni Sakka, Amos J. Storkey, Daniela Jaime Garcia, Yajun Cheng, Fergus Doubal, Michael T. Thrippleton, Michael Stringer, Joanna M. Wardlaw medRxiv 2022.01.24.22269144; doi: https://doi.org/10.1101/2022.01.24.22269144

(Preprint) Designing human Sphingosine-1-phosphate lyases using a temporal Dirichlet variational autoencoder. Evgenii Lobzaev, Michael A. Herrera, Dominic J. Campopiano, Giovanni Stracquadanio bioRxiv 2022.02.14.480330; doi: https://doi.org/10.1101/2022.02.14.480330

Michael Stam, Wood C W, DE-STRESS: a user-friendly web application for the evaluation of protein designs, Protein Engineering, Design and Selection, Volume 34, 2021, gzab029, https://doi.org/10.1093/protein/gzab029

(Preprint) DNA Methylation scores augment 10-year risk prediction of diabetes. Yipeng Cheng, Danni A Gadd, Christian Gieger, Karla Monterrubio-Gómez, Yufei Zhang, Imrich Berta, Michael Stam, Natalia Szlachetka, Evgenii Lobzaev, Archie Campbell, Cliff Nangle, Rosie M Walker, Chloe Fawns-Ritchie, Annette Peters, Wolfgang Rathmann, David J Porteous, Kathryn L Evans, Andrew M McIntosh, Timothy I Cannings, Melanie Waldenberger, Andrea Ganna, Daniel L McCartney, Catalina A Vallejos, Riccardo E Marioni medRxiv 2021.11.19.21266469; doi: https://doi.org/10.1101/2021.11.19.21266469

2020

Andreeva, Rayna, Fontanella, Alessandro, Giarratano Y., Bernabeu M.O. (2020) DR Detection Using Optical Coherence Tomography Angiography (OCTA): A Transfer Learning Approach with Robustness Analysis. In: Fu H., Garvin M.K., MacGillivray T., Xu Y., Zheng Y. (eds) Ophthalmic Medical Image Analysis. OMIA 2020. Lecture Notes in Computer Science, vol 12069. Springer, Cham. https://doi.org/10.1007/978-3-030-63419-3_2

Giarratano, Y., Pavel, A., Lian, J., Andreeva, Rayna, Fontanella, Alessandro, Sarkar, R., Reid, L., Forbes, S., Pugh, D., Farrah, T., Dhaun, N., Dhillon, B., MacGillivray, T. and Bernabeu, M., 2020. A Framework for the Discovery of Retinal Biomarkers in Optical Coherence Tomography Angiography (OCTA). Ophthalmic Medical Image Analysis, pp.155-164.OMIA 2020. Lecture Notes in Computer Science, vol 12069. Springer, Cham. https://doi.org/10.1007/978-3-030-63419-3_16

Fontanella, Alessandro, Pead, E.,Macgillivray, T., Bernabeu, M., & Storkey, A. (2020). Classification with a domain shift in medical imaging. Med-NeurIPS 2020: Medical Imaging meets NeurIPS Workshop http://www.cse.cuhk.edu.hk/~qdou/public/medneurips2020/43_Classification_with_a_domain_shift_in_medical_imaging.pdf

Talks

2024

Raman Dutt: 'Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity', Microsoft Research Biomedical Imaging Group, 2023 Barry Ryan: 'Multi-Omic Analysis with Networks'. CGEM Work in Progress Talks, 2024

2023

Rayna Andreeva: 'Magnitude as a novel metric for measuring embedding quality'. EpiCrossBorders symposium, Munich 2023

Leonardo Castorina: 'How to Solve the Protein Folding Problem: AlphaFold2' Toward Data Science Blog Post 2023

Filippo Corponi: 'Challenges and opportunities in personal sensing for mood disorders'. ecnp Neuroscience Applied digital online series 2023

Justin Engelmann: 'Exclusion of poor quality fundus images biases health research linking retinal traits and systemic health', ARVO annual meeting 2023

Justin Engelmann: 'Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation', UK Biobank Eye & Vision Consortium meeting 2023

Bryan Li: 'Dynamic V1 response prediction with a video Transformer', NeurIPS 2023 Dynamic Sensorium workshop 2023

Charlotte Merzbacher: 'Bridging the gap between genome-scale and kinetic models' SynBioUK Conference 2023

Charlotte Merzbacher: 'Machine learning for complex biological circuit design' AI for Healthcare CDT conference 2023

Charlotte Merzbacher: 'Awarded SFI working group for project “Uncertainty and Representation" Talk and award, SFI Complexity-GAINS Summer School 2023

Dominic Phillips: 'Numerical Methods with Coordinate Transforms for Efficient Brownian Dynamics Simulations' Numerical Methods Reading Group (University of Geneva) 2023

Dominic Phillips: 'Numerical Methods with Coordinate Transforms for Efficient Brownian Dynamics Simulations' Machine Learning and Simulation of Stochastic Dynamics with applications in materials science (University of Birmingham) 2023

Dominic Phillips: 'Numerical Methods with Coordinate Transforms for Efficient Brownian Dynamics Simulations' The 14th International Conference in Monte Carlo Methods and Applications (Paris) 2023

Barry Ryan: 'Multi-Omic Graph Diagnosis (MOGDx) : A data integration tool to perform classification tasks for heterogenous diseases', ENGoGS 2023

Xiao Yang: 'How the different diagnostic AI get embedded into healthcare' Conference 4S, Honolulu 2023

2022

Rayna Andreeva: 'Topological data analysis for papillae classification', CAI4H 2022

Leonardo Castorina: 'Latent Diffusion Explained Simply (with Pokémon)' Towards AI Blog Post 2022

Leonardo Castorina: 'Obsidian Tutorial for Academic Writing' Better Humans Blog Post 2022

Justin Engelmann: 'Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation', AI and Machine Learning in Healthcare Summer School at the Cambridge Centre for AI in Medicine 2022

Justin Engelmann: 'Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation', Plenary of the VAMPIRE research group 2022

Alessandro Fontanella: 'ACAT: Adversarial counterfactual attention for classification and detection in medical imaging', CAI4H - Joint AI Health meeting 2022

Alessandro Fontanella: 'The Challenges and Applications of Deep Learning Methods on Medical Imaging for Acute Ischemic Stroke', Edinburgh Imaging Academy - NIS meeting 2022

Alessandro Fontanella: 'The Challenges and Applications of Deep Learning Methods on Medical Imaging for Acute Ischemic Stroke', HDR UK - Applied Analytics seminar 2022

Aryo Pradipta Gema: 'Knowledge-Augmented Clinical Language Models', Guest Lecturer at Bina Nusantara University 2023

Aryo Pradipta Gema: 'Knowledge Graph Embeddings in the Biomedical Domain',  Guest Lecturer at Bina Nusantara University 2023

Bryan Li: 'Identifying digital biomarkers of illness activity and treatment response in bipolar disorder', UKRI AI CDTs in Healthcare Conference 2022

Domas Linkevicius: 'Linking models of biochemical dynamics via mass-constrained neural ordinary differential equations', 21st International Conference for Systems Biology 2022Charlotte Merzbacher: 'Machine learning approaches for dynamic metabolic engineering', International Conference on Systems Biology 2022

Charlotte Merzbacher: 'Synthetic biology in the age of machine learning', International Conference on Systems Biology organised workshop 2022

Angeletos Chrysaitis Nikitas: 'First impression bias in the development of perceptual priors', TEX2022: Bringing together Predictive Processes and Statistical Learning 2022

Xiao Yang: 'Beyond image: How Brain Legions are Automatically Recognised' Conference EASST, Madrid 2022

2021

Rayna Andreeva: 'Automatic papillae identification using discrete curvature analysis', Food Oral Processing, Early Career Researcher session 2021

Rayna Andreeva: A Geometric Approach to Papillae Identification in 3D Meshes, Young Researchers Forum, 37th Symposium on Computational Geometry 2021 https://cse.buffalo.edu/socg21/program.html

Matúš Falis: 'Towards Better Use of Ontological Structure in the Evaluation of Automated ICD Coding', HealTAC Healthcare Text Analytics Conference 2021

Alessandro Fontanella: 'Deep learning methods to identify ischemic stroke lesions from CT scans of the brain', SICSA Conference 2021

Evgenii Lobzaev: 'Primer on Variational Inference and its application to Deep Learning', 6th Winter School on Data Analytics DA 2021

Evgenii Lobzaev: 'AI-driven design of enzyme replacement therapies', SICSA Conference 2021

2020

Rayna Andreeva: 'DR Detection Using Optical Coherence Tomography Angiography (OCTA): A Transfer Learning Approach with Robustness Analysis', 7th MICCAI Workshop on Ophthalmic Medical Image Analysis (OMIA7)

Rayna Andreeva, Alessandro Fontanella: 'Identifying patient status using optical coherence tomography angiography (OCTA): A transfer learning approach', 12th SINAPSE Annual Scientific Meeting

Alessandro Fontanella: 'Classification with a domain shift in medical imaging', NEURIPS- Medical imaging meets NEURIPS workshop

Posters

2024

Justin Engelmann: 'Effective Artificial Intelligence (AI)-based identification of Geographic Atrophy (GA) in ultra-widefield (UWF) imaging in mixed and age-related macular degeneration (AMD) populations' ARVO Imaging in the Eye conference, 2024

Justin Engelmann: 'Repeatability and measurement noise of retinal Fractal Dimension using Deep Approximation of Retinal Traits (DART) and their relationship with image quality' The Association for Research in Vision and Ophthalmology (ARVO) annual meeting, 2024

Domas Linkevicius: 'Fitting, comparison and selection of different Calmodulin kinetic schemes on a single data set using non-linear mixed effects modelling', FENS Forum 2024

2023

Rayna Andreeva: 'Metric Space Magnitude and Generalisation in Neural Networks', ICML, TAG-DS, Honolulu, Hawaii and TDA week, Kyoto, Japan, as part of ICIAM 2023

Justin Engelmann: 'Deep learning identifies age as a key axis of perceptual variation in fundus images – without training on fundus images', ARVO imaging in the eye pre-conference 2023

Achille Fraisse: 'Predicting perivascular space severity scores from MRI scans using deep learning' CDT Biomedical AI Research Poster Showcase 2023

Hans-Christof Gasser: 'Utility of language model and physics-based approaches in modifying MHC Class-I immune-visibility for the design of vaccines and therapeutics'. Vaccine, ISMB 2023

Dominic Phillips: 'Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical Models', Thirty-Seventh AAAI Conference on Artificial Intelligence (Washington DC) 2023

Aleksandra Sobieska, Chris Brackley, Kartic Subr: 'Modelling large-scale 3D genome organisation using ML-informed polymer simulations', CDT Biomedical AI Showcase, Informatics Forum, University of Edinburgh 2023

Lars Werne: 'Evaluating factors that drive information decoding from EEG data'. CuttingEEG Conference Dundee 2023

2022

Rayna Andreeva: 'Topological data analysis for papillae classification', Autumn poster session, online, AATRN 2022

Rayna Andreeva: 'Topological data analysis for papillae classification', Provost’s visit to the School of Informatics 2022

Rayna Andreeva: 'Topological data analysis for papillae classification', Biomedical AI Research Poster Showcase 2022

Rayna Andreeva: 'Applications of magnitude to neural networks', Topology of Data in Rome

Rayna Andreeva: 'Topological data analysis for papillae classification', SINAPSE Annual Scientific Meeting

Rayna Andreeva: 'Topological data analysis for papillae classification',  Applied Topology in Będlewo 2022

Rayna Andreeva: 'Topological data analysis for papillae classification', CAI4H 2022

Leonardo Castorina: 'Machine Learning for Protein Design', APFED22

Justin Engelmann: 'Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning', Biomedical AI Research Poster Showcase, 2022

Justin Engelmann: 'Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation', Ophthalmic Medical Image Analysis workshop at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention 2022

Justin Engelmann: 'Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning' Provost’s visit to the School of Informatics 2022

Justin Engelmann: 'Parity in predictive performance is neither necessary nor sufficient for fairness', Algorithmic Fairness through the Lens of Causality and Privacy at the NeurIPS conference 2022

Matúš Falis: 'Horses to Zebras: Ontology-Guided Data Augmentation and Synthesis for ICD-9 Coding', ACL 2022

Alessandro Fontanella: 'ACAT: Adversarial counterfactual attention for classification and detection in medical imaging', CAI4H 2022

Olivier Labayle Pabet: 'Let’s remove unnecessary assumptions from population genetics studies', EMGM 2022

Bryan Li: 'Inferring mood disorder symptoms from multivariate time-series sensory data', NeurIPS Workshop on Learning from Time Series for Health 2022

Domas Linkevicius: 'Linking models of biochemical dynamics via mass-constrained neural ordinary differential equations', 21st International Conference for Systems Biology 2022

Domas Linkevicius: 'Modeling the dynamics of arbitrary partially known biochemical systems via mass constrained neural ODEs' Scottish Neuroscience Group Meeting 2022

Evgenii Lobzaev: 'Designing Human Sphingosine-1-phosphate Lyases Using Generative Deep Learning', Glycolipid and Sphingolipid Biology GRC 2022

Charlotte Merzbacher: 'Fast and Scalable machine learning for dynamic metabolic engineering', SynBioUK Conference 2022

Aleksandra Sobieska: 'Development of a machine learning-based approach for the analysis of DNA replication in primary mammalian cells', Biomedical AI Research Summer Social Poster Session 2022

Aleksandra Sobieska: 'Benchmarking of deconvolution algorithms for data-informed cell type composition of in vitro models for non-alcoholic fatty liver disease', Biomedical AI Research Poster Showcase 2022

Michael Stam: 'Data-driven prediction of antibody expression', APFED22

2021

Rayna Andreeva: 'Automatic papillae identification using discrete curvature analysis', Food Oral Processing 2021, Early Career Researcher session

Domas Linkevicius: 'Modeling the dynamics of partially known systems via the integration of a system of ordinary differential equations into a recurrent neural network', CNS*2021

Domas Linkevicius: 'Combining neural ODEs and incomplete ODE systems to model complex, under-parameterised synaptic biochemical networks', Neuroscience 2021

Filippo Corponi: 'Definition of early age at onset in bipolar disorder according to distinctive neurodevelopmental pathways: insights from the FACE-BD study', French Congress of Psychiatry

Li W, Fontanella Alessandro, Antoniou A, Platt E., Martin C., Mair G., Trucco E., Storkey A., Wardlaw J.: 'Acute ischaemic stroke (AIS) lesion detection with a convolutional deep learning model', 7th European Stroke Organisation Conference ESOC 2021

Mair G., Li W., Martin C., Fontanella, Alessandro, Trucco E., Storkey A., Wardlaw J.: 'Challenges of delivering medical image sets for development of deep learning software in stroke', Artificial intelligence in practice 2021

Public Engagement and EDI initiatives

Justin Engelmann: ML in the “real world” - Some insights from a PhD student in medical imaging.  Guest lecture for Dr Elliot Crowley’s course “Data Analysis and Machine Learning 4 (ELEE10031)” (2024)

Justin Engelmann: received £2,200 from the CMVM travel fund to visit Dr Daniel Ferraz and colleagues in Sao Paulo, Brazil, (May 2024)

Xiao Yang Presented and discussed PhD research related to AI ethics at the AIES 2024 Doctoral Colloquium (2024)

Fiona Smith 'Creator in Residence: an exploration of multimedia approaches for public engagement'  Panel Discussion on “Transformative Spaces: Science-Art Residencies” followed by the Exhibition Opening of “The BOX” as part of the 2024 Edinburgh Science Festival, investigates the theme ‘Shaping the Future’, which showcases some of the cutting-edge science that can help us create a future that is sustainable, accessible and equal for all.   Venue: Informatics Forum and Inspace Gallery in Edinburgh. (2024)

Charlotte Merzbacher: 'S6 students (ages 9-10) in 3 primary school classes interviewed me about what it is like to be an engineer.' Engineer Day at Burnbrae Primary School (2024)

Xiao Yang Coordinated and Facilitated the global participants of the Sketch group as the Society Liaison Representative, 4S (2023)

Leonardo Castorina: 'AI in Healthcare: The Next Frontier, a Biomedical Perspective' investigates the inner workings of ChatGPT and highlights issues related to its use in biomedical applications.  A series of TEDx talks on the theme of The Great UnknownTEDx ChatGPT   (2023)

Barry Ryan: 'Prize for ENGoGS presentation'  https://onehealthgenomics.ed.ac.uk/barry-ryan (2023)

Aryo Pradipta Gema: 'Large Language Models and its biomedical applications' with Sutton Trust Summer School at University of Edinburgh: a speaker to introduce Large Language Models and ChatGPT as well as the potential clinical use cases.

Aryo Pradipta Gema: 'ChatGPT: A Biomedical AI Perspective' at University of Edinburgh: a speaker to introduce Large Language Models and ChatGPT as well as the potential clinical use cases (2023)

Bryan Li: Alan Turing Institute 2023-2024 Enrichment Scheme Placement award (2023-2024)

Xiao Yang is an Academic Association Committee Member of AsSIST-UK, organising the bi-annual conference and ECR events (2022 to present)

Michael Stam, Leo Castorina, Natalia Szlachetka and Team: "Programming Proteins" pubic exhibition at the Royal Society Summer Science Exhibition (2022).

Katarzyna Szymaniak: Co-Creation Workshop with IntellSensing Lab at Newcastle University (2021)

Rayna Andreeva, Natalia Szlachetka, Katarzyna Szymaniak:  Panel participation: Women in AI event hosted by UCL (2020)

Rayna Andreeva: EDI in STEM: Race and Disability Workshop. Participation in an EDI workshop as part of the Women in STEM and CompSoc's equality, diversity, and inclusion (EDI) series with Dr Frantzana (2020)