Rate My Professor William Majoros

Majoros's research interests encompass probabilistic machine learning, Bayesian graphical models, structured prediction, interpretation and prioritization of genetic variants in disease, RNA splicing, and gene regulation. He also investigates computational linguistics topics, including formal grammars and parsing, syntactic structure, and memetic evolution in complex bird song. Majoros is affiliated with the Center for Advanced Genomic Technologies in Duke's Pratt School of Engineering and the Duke Center for Statistical Genetics and Genomics. He serves as principal investigator on the National Institute of General Medical Sciences grant "Computational Methods for Investigating the Genetics of Gene Regulation" (2023–2028). Additionally, he is a research investigator on the National Institute of Mental Health grant "Beyond GWAS: High Throughput Functional Genomics & Epigenome Editing to Elucidate the Effects of Genetic Associations for Schizophrenia" (2021–2027) and co-principal investigator on the National Human Genome Research Institute grant "Design, prediction, and prioritization of systematic perturbations of the human genome" (2021–2026). His recent publications include "Structured Pooling Improves Detection of Rare Regulatory Mutations in Population-Scale Reporter Assays" (2026), "Identifying Inheritance Patterns of Allelic Imbalance, using Integrative Modeling and Bayesian Inference" (2026), "The IGVF catalog—from genetic variation to function" (2026), "Bayesian estimation of allele-specific expression in the presence of reference bias" (2025), and "Characterization and bioinformatic filtering of ambient gRNAs in single-cell CRISPR screens" (2025). Earlier notable works feature contributions to gene prediction algorithms and studies on microRNA translocation in sickle cell erythrocytes and coordinated posttranscriptional mRNA dynamics.