Tianyu Cui
Scientist at Johnson & Johnson Innovative Medicine
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolTianyu Cui is a scientist and machine learning researcher with a decade of experience applying probabilistic and deep learning methods to biomedical and drug discovery problems. Currently at Johnson & Johnson Innovative Medicine, he focuses on causal discovery, deep latent variable models, and foundation models for AI-driven drug design. His trajectory spans top research environments—Imperial College, Aalto University (PhD in probabilistic ML), UCL, and industry stints at Silo AI and Invenia—bridging rigorous Bayesian deep learning with practical, interpretable generative techniques. Tianyu’s work emphasizes interpretable priors, interaction detection in genetics, and decision-making under uncertainty, translating academic advances into life-saving applications. Based in London, he combines strong statistical foundations with hands-on model development for high-impact biomedical projects.
10 years of coding experience
5 years of employment as a software developer
Bachelor of Science- BS Statistics and Economics, Bachelor of Science- BS Statistics and Economics at Xi'an Jiaotong UniversityUniversity College London
Github Skills (20)
python9
google9
automation8
certificate7
prediction4
bootstrapping3
statistical-inference3
datasets2
benchmarking2
toolbox2
benchmark2
machine-learning1
drug-discovery1
docking1
clinical-trials1
Programming languages (1)
Github contributions (5)
tycui/GWAS_NN
Jan 2021 - Oct 2022
Contributions:2 releases, 21 commits, 20 pushes in 1 year 9 months
tycui/tycui.github.io
Sep 2018 - Mar 2025
Contributions:168 pushes, 1 branch in 6 years 7 months
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