Xiaoyu Lu

• Developed machine learning and statistical inference approaches to identify critical regulators of transcriptional patient states from multi-modal real-world patient molecular profiles, which contributing to patient selection and clinical strategy for BMS on-going programs. • Contributed to the initiation of 5+ data driven novel targets in selected oncology indications, driving the computational strategy and analysis in cross-functional teams. • Designed genetic validation experiments in relevant patient derived models, integrated orthogonal lines of evidence, utilized computational innovations to accelerate target prioritization 5-fold and delivered 3+ target validation data packages for discovery programs.

• Advanced machine learning and statistical model development in bioinformatics • Multi-omics data investigation and inference • User friendly R Shiny interface development. • Work as a reviewer for multiple journal and conferences, e.g. Bioinformatics, PLOS ONE, KDD, RECOMB and BIBM.

• Hands-on analysis of internal single cell sequencing and spatial transcriptomics datasets. • Develop new computational methods and pipelines for spatial transcriptomics data. • Discussing results with diverse groups to pursue data driven characterization for pathogenesis and MoA in Oncology and CNS diseases.

• Identified gene signatures which are highly correlated in tumor microenvironment and correspond to glycolysis levels in vitro and in vivo. • Estimate glycolysis levels in the TME using transcriptomic data.

Statistical learning development in high dimension data. Transcriptomic and medical data analysis.

Golden Award in China Undergraduate Mathematical Contest in Modeling. 10/2015 Excellent Student Scholarship, Shandong University. 2015-2017