Rate My Professor Arjun Krishnan

Arjun Krishnan, PhD, is an Associate Professor in the Department of Biomedical Informatics at the University of Colorado Anschutz Medical Campus, School of Medicine. He concurrently holds an appointment in the Department of Biostatistics and Informatics and is affiliated with the Center for Health AI and the Colorado Center for Personalized Medicine. Krishnan serves as Co-Director of the Human Medical Genetics and Genomics Program and Co-Director of the Computational Biosciences Program. He is also a Training Program Investigator for the T15 Colorado Biomedical Informatics Training Program and training faculty for graduate programs in Computational Biosciences, Human Medical Genetics and Genomics, Biostatistics and Informatics, Pharmacology, Pharmaceutical Sciences, and Quantitative Biology at CU Boulder. He earned his PhD in Computational Biology from Virginia Polytechnic Institute and State University in 2010, followed by postdoctoral research as a Research Associate at the Lewis-Sigler Institute for Integrative Genomics at Princeton University from 2011 to 2013.

Krishnan leads the Krishnan Lab, which develops machine learning and artificial intelligence methods to harness massive public biomedical data collections, enabling predictive and interpretable models of genes, molecular networks, tissues, and mechanisms driving complex disease heterogeneity. His research spans computational biology, biomedical data science, network biology, and natural language processing applications in biomedicine. Notable contributions include PyGenePlexus, a Python package for network-based gene discovery and classification (Bioinformatics, 2023); PecanPy, a fast Python implementation for random walk-based network embedding (Bioinformatics, 2021); and CONE, for context-specific network embedding (Proceedings of Machine Learning Research). Key recent publications are 'Computational strategies for cross-species knowledge transfer' (Nature Methods, 2025), 'Annotating publicly-available samples and studies using interpretable modeling of unstructured metadata' (Briefings in Bioinformatics, 2024), 'Examining the genetic links between clusters of immune-mediated diseases and psychiatric disorders' (Translational Psychiatry, 2025), and 'Integration of 168,000 samples reveals global patterns of the human gut microbiome' (Cell, 2025). With 6,895 citations and expertise recognized on Google Scholar, his work advances data reuse and discovery in genomics and omics. In 2023, he led a team awarded the $12,500 FASEB DataWorks! Prize for Removing Metadata Barriers to Promote Data Reuse. Krishnan champions open science, research training, and inclusive environments.