Publications

DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform, Alexander Denker, Francisco Vargas, Shreyas Padhy, Kieran Didi, Simon Mathis, Vincent Dutordoir, Riccardo Barbano, Emile Mathieu, Urszula Julia Komorowska, Pietro Lio, arxiv, 06/2024
BioModelsML: Building a FAIR and reproducible collection of machine learning models in life sciences and medicine for easy reuse, Divyang Deep Tiwari, Nils Hoffmann, Kieran Didi, Sumukh Deshpande, Sucheta Ghosh, Tung V. N. Nguyen, Karthik Raman, Henning Hermjakob, Rahuman S Malik Sheriff, biorxviv, 05/2023

Structure-based Drug Design with Equivariant Diffusion Models, Arne Schneuing, Yuanqi Du, Charles Harris, Kieran Didi, Arian Jamasb, Ilia Igashov, weitao Du, Tom Blundell, Pietro Liò, Carla Gomes, Max Welling, Michael Bronstein, Bruno Correia

MISATO: machine learning dataset of protein–ligand complexes for structure-based drug discovery, Till Siebenmorgen, Filipe Menezes, Sabrina Benassou, Erinc Merdivan, Kieran Didi, André Santos Dias Mourão, Radosław Kitel, Pietro Liò, Stefan Kesselheim, Marie Piraud, Fabian J. Theis, Michael Sattler & Grzegorz M. Popowicz, Nature Computational Science, 05/2024
[Synsor: a tool for alignment-free detection of engineered DNA sequences], Aidan P Tay, Kieran Didi, Anuradha Wickramarachchi, Denis Bauer, Laurence Wilson and Maciej Maselko, Frontiers in Bioengineering and Biotechnology, 04/2024
AbNatiV: VQ-VAE-based assessment of antibody and nanobody nativeness for hit selection, humanisation, and engineering, Aubin Ramon, Montader Ali, Misha Atkinson, Alessio Saturnino, Kieran Didi, Cristina Visentin, Stefano Ricagno, Xing Xu, Matthew Greenig, Pietro Sormanni, Nature Machine Intelligence, 04/2023
Biomolecular condensate phase diagrams with a combinatorial microdroplet platform, William E. Arter, Runzhang Qi, Nadia A. Erkamp, Georg Krainer, Kieran Didi, Timothy J. Welsh, Julia Acker, Jonathan Nixon-Abell, Seema Qamar, Jordina Guillén-Boixet, Titus M. Franzmann, David Kuster, Anthony A. Hyman, Alexander Borodavka, Peter St George-Hyslop, Simon Alberti & Tuomas P. J. Knowles, Nature Communications, 12/2022

RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design,
Dynamics-Informed Protein Design with Structure Conditioning, Urszula Julia Komorowska, Simon V Mathis, Kieran Didi, Francisco Vargas, Pietro Lio, Mateja Jamnik , ICML ML4LMS 2024 (Oral Presentation), 01/2024
Evaluating Representation Learning on the Protein Structure Universe, Arian Rokkum Jamasb, Alex Morehead, Zuobai Zhang, Chaitanya Joshi, Kieran Didi, Simon Mathis, Charles Harris, Jian Tang, Jianlin Cheng, Pietro Liò, Tom Blundell, ICLR,01/2024
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design, Kieran Didi, Francisco Vargas, Simon Mathis, Vincent Dutordoir, Emile Mathieu, Urszula Julia Komorowska, Pietro Lio, NeurIPS AI4D3 2023 (Oral Presentation), 11/2023
Benchmarking Generated Poses: How Rational is Structure-based Drug Design with Generative Models?, Charles Harris, Kieran Didi, Arian Jamasb, Chaitanya Joshi, Simon Mathis, Pietro Lio, Tom Blundell, NeurIPS MLSB 2023 (Oral Presentation), 11/2023
Modelling biology in novel ways - an AI-first course in Structural Bioinformatics, Kieran Didi, Charles Harris, Pietro Liò, Rainer Beck, NeurIPS AI4Science 2023, 10/2023
Flexible Small-Molecule Design and Optimization with Equivariant Diffusion Models, Charles Harris, Kieran Didi, Arne Schneuing, Yuanqi Du, Arian Jamasb, Michael Bronstein, Bruno Correia, Pietro Liò, Tom Blundell, ICLR MLDD 2023, 03/2023

Generative Models in Bioinformatics, invited book chapter in Encyclopedia of Bioinformatics and Computational Biology, under review, 01/2023

Conference Presentations

Conditioning generative models for proteins, images and more (oral presentation), AI and Biology Conference, EMBL Heidelberg (Germany), 03/2024
Where do we stand in protein and ligand design? (oral presentation), Computational Structural Biology Conference, EMBL Heidelberg (Germany), 12/2023
Conditional Diffusion Models for Protein Design via Doob’s h-transform (poster), MoML Conference, MIT (US), 11/2023
Reality Check - Evaluating Generative Models for Protein and Ligand Design (poster), Machine Learning in Drug Discovery Symposium, Broad Institute (US), 10/2023
Accessible AMR-detection tools for clinicians via cloud-based bioinformatics (oral presentation), Clinical Informatics Symposium, Melbourne (Australia), 12/2022
sINSIDER: a cloud-native modular platform for kmer-based genomic analysis (oral presentation), ABACBS Conference, Melbourne (Australia), 11/2022
Moving bioinformatics to the cloud (keynote presentation), eSCAMPS Symposium, Cambridge (UK), 09/2022
Detecting DNA integration via HPC bioinformatics pipeline (poster),R&I Conference, Sydney (Australia), 08/2022

ICML CompBio 2023, NeurIPS AI4Science 2023, NeurIPS GenBio 2023, MoML@MIT 2023, ICLR GEM 2024

Deep Learning in Structure-Based Drug Design, tutorial, Spring School Structure-based Computer-aided Drug Design, Swiss Institute of Bioinformatics (SIB), 06/2024
SDEs and Diffusion Processes, lecture, Cambridge University (MPhil Advanced Computer Science), 01/2024
Structural Bioinformatics, lecture, Heidelberg University (BSc Biochemistry), 10/2023
Graph Modelling with Applications to Structural Biology, presentation, CCAIM AI and Machine Learning Summer School, 09/2023
Advanced Python for Scientists, lecture, Heidelberg University, 06/2023
Algorithms II, supervising course on data structures and graph algorithms, Cambridge University, 03-05/2023
Algorithms I, Cambridge University, 01-03/2023
MLOps with PyTorch Lightning and W&B, workshop, ML Forum CSIRO Australia, 01/2023
Python for Scientists, lecture, Heidelberg University, 11/2022
Python Best Practices, workshop (co-host), Scientific Software Center Heidelberg, 11/2022
Deep Learning with PyTorch, Lunch Time Python workshop, Scientific Software Center Heidelberg, 10/2022
Python for Biochemists, lecture, Heidelberg University, 03/2022