I am interested in using high-dimensional data to construct causal networks of interconnected molecular and phenotypic features and understanding how perturbations propagate across these networks causing diseases and aging. I also help to develop Calico’s capabilities for computational mass spectrometry, both to cast a wide net in search of biomarkers, but also so we can build principled integrative-omic models.
I spent my PhD developing methods for understanding metabolism at the interface of fluxes, metabolites and enzymes using high-dimensional data. I devoted my PostDoc to developing techniques for extracting additional information from such data modalities.
Publications
Time-resolved genome-scale profiling reveals a causal expression network
Systems-level analysis of mechanisms regulating yeast metabolic flux
Genetic basis of metabolome variation in yeast
Education
Princeton University, Ph.D. in Quantitative and Computational Biology
Cornell University, B.S. in Biological Sciences (Genetics & Development)
Honors and Awards
MIT Sloan Sports Analytics Conference Research Paper Finalist - 2017
Department of Energy Office of Science Graduate Fellow - 2012
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