Scholar
Tianyu Cui
Google Scholar ID: zz_l_pYAAAAJ
Research Scientist, Johnson and Johnson
Citations & Impact
Citations
206
H-index
6
i10-index
6
Publications
20
Co-authors
4
list available
Publications
Resume
Academic Achievements
- Published several papers including 'BioBO: Biology-informed Bayesian Optimization for Perturbation Design', 'InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network Inference', and more, covering areas such as gene regulatory network inference and large-scale equivariant learning.
Research Experience
- Worked as a Research Associate at Imperial College London.
Education
- PhD from Aalto University under the supervision of Prof. Samuel Kaski and Prof. Pekka Marttinen, focusing on Bayesian deep learning; MSc degree from University College London on computational statistics and machine learning.
Background
- I'm Tianyu, a Senior Research Scientist at Johnson & Johnson in London, working on AI for drug discovery. My research spans Bayesian modeling to modern deep learning, with a particular focus on developing principled probabilistic methods that leverage foundation models to enhance prediction and discovery.
Miscellany
- Contact: Email | LinkedIn | GitHub | Google Scholar
