Amaya Gallagher-syed
Honorary Research Fellow at Imperial College London
London, England, United Kingdom
Summary
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Senior🎓
Top SchoolAmaya Gallagher-Syed is an interdisciplinary AI-for-biology researcher with nine years’ experience developing interpretable deep learning methods for histopathology and transcriptomics, focused on biomarker discovery and patient stratification in immunology. Currently an Honorary Research Fellow at Imperial College London and affiliated with DERI, she combines a PhD in AI for Biomedicine and an MSc in Data Analytics to bridge computational rigor with biological insight. Her recent work pivots to modelling cell–cell interactions, biology foundation models, and information propagation—areas that require both theoretical innovation and practical multimodal data integration. Known for explainable algorithms in multi-stain and multimodal pathology, she brings a rare blend of wet-lab biological training and advanced machine learning expertise to translational problems.
9 years of coding experience
Doctor of Philosophy - PhD AI for Biomedicine, Doctor of Philosophy - PhD AI for Biomedicine at Queen Mary University of LondonLicentiate degree in Biological Sciences Computational Biology, Licentiate degree in Biological Sciences Computational Biology at University of Buenos Aires
English, French, Spanish
Github Skills (8)
self-attention9
histopathology8
gnn8
transcriptomics6
benchmark4
immunology4
xai3
foundation-models2
Programming languages (2)
Github contributions (5)
AmayaGS/WSI_Multiple_Instance_Learning
Jan 2023 - Mar 2023
Contributions:46 commits, 46 pushes, 1 branch in 1 month
AmayaGS/MUSTANG
Mar 2023 - Feb 2025
Multi-stain graph self attention multiple instance learning for histopathology Whole Slide Images - BMVC 2023
Contributions:2 PRs, 46 pushes in 1 year 11 months
gnngraph-attentionhistopathologymultiple-instance-learningself-attention
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