Date and Time: Friday 30th January 2026 at 3.30pm.
Place: School of Computing Science, Sir Alwyn Williams Building, Room 423/424.
Talk 1: Multi-agent AI enables evidence-based cell annotation in single-cell transcriptomics
Dr Parashar Dhapola, Co-founder and CEO of Nygen Analytics, Lund, Sweden. https://www.nygen.io/
Associated research papers: [1] Gautam Ahuja, Alex Antill, Yi Su, Giovanni Marco Dall’Olio, Sukhitha Basnayake, Göran Karlsson, Parashar Dhapola (2025) Multi-agent AI enables evidence-based cell annotation in single-cell transcriptomics, bioRxiv 2025.11.06.686964 https://doi.org/10.1101/2025.11.06.686964
Talk 2: Deciphering complex biological systems using AI - from generative models to language models
Dr Cen Wan (Senior Lecturer in Bioinformatics, School of Computing and Mathematical Sciences, Birkbeck College, University of London)
Associated research papers: [1] Alsaggaf, I., Buchan, D. and Wan, C. (2025) Less is more: Improving cell-type identification with augmentation-free single-cell RNA-Seq contrastive learning, Bioinformatics, btaf437. https://doi.org/10.1093/bioinformatics/btaf437
[2] Alsaggaf, I., Buchan, D. and Wan, C. (2025) An extensive evaluation of single-cell RNA-Seq contrastive learning generative networks for intrinsic cell-types distribution estimation, bioRxiv. DOI: 10.1101/2025.09.15.675691. https://www.biorxiv.org/content/10.1101/2025.09.15.675691v1
[3] Rafi, A., et al. (2024) A community effort to optimize sequence-based deep learning models of gene regulation, Nature Biotechnology. https://doi.org/10.1038/s41587-024-02414-w