Swati Kaushik
Senior Scientist II at Tempus AI
San Francisco, California, United States
Summary
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Senior🎓
Top SchoolSwati Kaushik is a computational scientist with over a decade of experience applying machine learning and systems biology to cancer genomics and proteomics, currently advancing translational efforts as Senior Scientist II at Tempus AI. She has a strong track record at Gilead and UCSF developing single-cell and bulk RNA-seq pipelines, integrating proteomics and network-based pan-omics biomarkers to improve patient stratification and predict drug response. Her work spans algorithm development (e.g., C-HMM for remote homolog detection) to production-ready visualization tools and ML models for target discovery and clinical decision support. Proficient in Python, R and Perl, she routinely combines high-throughput omics, mass-spec proteomics and WES analyses to uncover mechanisms of drug resistance and rational combination strategies. Colleagues describe her as both a hands-on developer and a strategic collaborator who bridges academic and industry partnerships to accelerate biomarker-driven therapies. Based in San Francisco, she brings an uncommon blend of computational rigor and practical implementation experience in translational oncology.
11 years of coding experience
10 years of employment as a software developer
Doctore of Philosophy (PhD) Computational Biology, Doctore of Philosophy (PhD) Computational Biology at National Center for Biological SciencesMaster of Science (MS) in Bioinformatics, Master of Science (MS) in Bioinformatics at Savitribai Phule Pune University
English, HindiGithub contributions (5)
SwatiKaushik/C-HMM
Jan 2015 - Jan 2015
Contributions:1 release, 41 commits, 40 pushes in 1 day
SwatiKaushik/Correlation-analyses
Oct 2016 - Mar 2017
Contributions:33 pushes, 1 branch in 5 months
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