Pejman Mohammadi is an Associate Professor at the University of Washington and a Principal Investigator at Seattle Children's, focusing on the development of machine learning methods that integrate biological principles for enhanced decision-making from limited data. Expertise includes quantitative analysis of regulatory variation in the human genome through large-scale omics data for precision medicine applications. Previous roles include Associate Professor at Scripps Research, Postdoctoral Researcher at New York Genome Center, and Postdoctoral Fellow at Columbia University, with a foundational background in Computational Biology and Bioinformatics obtained through a PhD from ETH Zürich and a Master’s from Aalto University. Additional research experience spans various institutions, emphasizing Bayesian machine learning, structural bioinformatics, and algorithmic data mining.
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