Leonardo Castorina
Senior Research Scientist at AstraZeneca
Cambridge, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolLeonardo Castorina is a Senior Research Scientist based in Cambridge with a decade of experience at the intersection of machine learning and molecular biology, now working at AstraZeneca. He brings hands-on ML research experience from industry leaders including Microsoft and NEC, plus entrepreneurial perspective as a former CEO and co-founder. Trained at the University of Edinburgh through BSc, MSc and PhD studies, he focuses on protein science and computational methods—aptly self-described as a "protein dreamer." His track record includes short-term consulting and internships that bridge applied ML and biotech R&D, demonstrating an ability to translate research prototypes into industry-relevant solutions. Colleagues can expect a researcher who blends rigorous academic training with product-minded experimentation and a knack for concise science communication (he also blogs about his work).
10 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at The University of EdinburghLa Grande Boissière - International Baccalaurate Diploma, La Grande Boissière - International Baccalaurate Diploma at International School of Geneva
Italian, English, French, sicilian
Stackoverflow
423reputation
38kreached
5answers
4questions
Github Skills (189)
python10
menubar10
protein-design10
economics10
cryptocurrency10
genomics10
backlight10
swiftui10
crypto10
protein-sequences10
sec10
brightness10
sampling10
autoencoder10
keyboard10
Programming languages (15)
Github contributions (5)
universvm/BacXeption
Dec 2018 - Oct 2020
Deep Learning Template for bacterial image classification in Keras.
Contributions:59 commits, 7 PRs, 14 pushes in 1 year 10 months
biotechnologydeep-learningbioinformaticsneural-networkimage-classification
wells-wood-research/timed-design
Nov 2021 - Jan 2023
Protein Sequence Design with Deep Learning and Tooling like Monte Carlo Sampling and Analysis
Contributions:5 releases, 22 reviews, 239 commits in 1 year 1 month
toolingsequenceprotein-sequencesautoencoderdeep-learning
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