Caibin Sheng
Senior Data Scientist Clinical Trial Manager
Basel, Basel-City, Switzerland
Summary
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Rockstar🎓
Top SchoolCaibin Sheng is a Senior Data Scientist and Clinical Trial Manager based in Basel with six years of experience bridging computational biology and oncology drug development. He leads biomarker discovery and Bayesian trial design efforts for a first-in-class antibody program, combining single-cell multi-omics, digital pathology, and genomics to prioritize indications and elucidate mechanism of action. His background spans postdoctoral work at NIBR and academic labs where he developed probabilistic deep learning tools to denoise single-cell data and analysis pipelines for CRISPR screens. Caibin has hands-on wet-lab experience in CRISPR editing and live-cell imaging, giving him rare fluency across experiment and computational analysis. He is building AI agents and internal data platforms to streamline global clinical trial operations, reflecting a strong focus on automation and regulatory-ready data infrastructure. Colleagues rely on him for turning complex multi-modal datasets into actionable clinical decisions.
6 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Single Cell Biology Computational Biology Genome Editing, Doctor of Philosophy - PhD Single Cell Biology Computational Biology Genome Editing at Humboldt-Universität zu BerlinBachelor's degree Pharmacy, Bachelor's degree Pharmacy at Huazhong University of Science and TechnologyMaster's degree Molecular Biology, Master's degree Molecular Biology at Shanghai Jiao Tong University
Chinese, English, German
Stackoverflow
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Github Skills (50)
single-cell-genomics10
hierarchical10
package-management10
variational-autoencoder10
conda10
removal10
temporal-data10
topological-data-analysis10
autoencoder10
tsne10
density-estimation10
droplet10
transcriptomics10
single-cell-analysis10
probabilistic10
Programming languages (6)
Github contributions (5)
CaibinSh/scAR
Jan 2022 - Jan 2023
scAR (single-cell Ambient Remover) is a package for data denoising in single-cell omics.
Contributions:8 releases, 1 review, 77 commits in 1 year
ambientremovermachine-learning-algorithmsomicsprobabilistic-programming
Novartis/scar
May 2022 - May 2022
scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics
Contributions:13 releases, 17 reviews, 1 commit in 1 day
single-cell-rna-seqsingle-celldropletcite-seqprobabilistic-graphical-models
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