Afrida Alam is a software engineer and physicist with eight years of experience applying machine learning to terabyte-scale scientific datasets, most recently developing CNN and self-organising map pipelines during a PhD at the University of Hull. She builds reproducible, scalable data workflows in Python and TensorFlow, with strong skills in preprocessing, augmentation, hyperparameter optimisation and SQL-backed data integration. Her work bridges research and practical engineering—publishing peer-reviewed results and presenting at conferences while productionising models with checkpointing and evaluation infrastructure. Comfortable mentoring MSc students, she also brings consultancy experience in financial data governance, giving her a pragmatic approach to data quality and compliance. Notably, she pairs deep-domain astronomy knowledge with engineering rigor to tackle complex image classification challenges ahead of the SKA era.
8 years of coding experience
5 years of employment as a software developer
PhD Physics, PhD Physics at University of Hull
International Baccalaureate, International Baccalaureate at UWC Atlantic College
International Summer Semester, International Summer Semester at Sungkyunkwan University
Masters Degree Physics, Masters Degree Physics at University of Leicester
Contributions:5 PRs, 2 pushes, 7 branches in 3 years 4 months
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