Stanford University
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Arash Keshavarzi
Postdoctoral Scholar, Cardiovascular Medicine
BioArash has a background in molecular biology and chemistry, and earned his PhD in AI-driven drug discovery, where his work led to the identification of three candidate drugs for breast cancer, validated both in vitro and in vivo. Following this, he joined a lab at UCSF for his first postdoctoral position which led to a patent for AI drug discovery applications which led to multiple patents and articles. Throughout his career, Arash has also been involved in multiple ventures. He served as the Chief Scientific Officer at Nucleus Genomics with $17 million seed funding, and co-founded Lumos Bio, a stealth focused on RNA-targeted drug discovery. Currently, Arash is a NIH T32 fellow postdoc in the Ashley Lab and an investment fellow in Mubadala Capital
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Pik Fang Kho
Postdoctoral Scholar, Cardiovascular Medicine
BioI obtained my PhD in genetic epidemiology at Queensland University of Technology (Australia), where my research was focused on using genetic and genomic approaches to identify risk factors for endometrial cancer. During my graduate studies, I gained experience in large-scale genetic association studies and leveraging the correlation between diseases in genetic studies to identify novel genetic variants associated with endometrial cancer. I also developed expertise in various statistical genetic approaches in multi-omics data, including fine-mapping and colocalization analyses, to prioritize candidate causal variants and genes. I also gained extensive experience in genetic causal inference analysis to infer causality between risk factors and health outcomes.
My research focus since moving to Stanford has been the identification of genetic and non-genetic determinants of cardiometabolic diseases. I am currently involved in projects including large-scale genetic association studies, multi-trait analysis with correlated traits, development and validation of polygenic risk scores, integrative analyses with multi-omics data, as well as Mendelian randomization analyses to advance our understanding of the genetic and environmental factors that contribute to cardiometabolic diseases.
