Lucas Seninge is a Machine Learning Scientist II based in California with 8 years of experience applying ML to genomics and single-cell biology. At NewLimit he builds scalable AI systems for in silico reprogramming and lab-in-the-loop workflows, having previously designed models for epigenetic reprogramming and pooled single-cell screens. His doctoral work fused prior biological knowledge with interpretable deep generative models for single-cell pathway activity and in-silico perturbation, and he has practical experience translating models across domains including drug response prediction with graph convolutional networks. Comfortable in both research and production settings, he has built scalable data formats and ML pipelines for petabyte-scale genomics and contributed to multi-institution projects funded by CIRM and the Chan-Zuckerberg Initiative. Notably, he combines hands-on lab protocol experience and single-cell sequencing know-how with strong computational skills, enabling tighter integration between experimental design and model-driven hypothesis testing.
8 years of coding experience
3 years of employment as a software developer
Master's degree, High-Throughput methods applied to Biology, Master's degree, High-Throughput methods applied to Biology at University of Strasbourg
Engineer's degree, Biotechnology, Engineer's degree, Biotechnology at ESBS
Biology, General, Biology, General at Clémenceau High School (REIMS)
Contributions:2 releases, 57 commits, 49 pushes in 1 year 4 months
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Lucas Seninge - Machine Learning Scientist II at NewLimit