معرفی
Eugene Lin is a Researcher in the Department of Biostatistics at the University of Washington. His work focuses on the intersection of artificial intelligence and medicine, particularly in computational biology, genomics, and pharmacogenomics. He holds a Ph.D. and M.S. in Biostatistics from the University of Washington.
Research interests include machine learning frameworks for single-cell RNA sequencing, drug discovery, and deep learning applications in neuroimaging. He develops algorithms in Python, R, and TensorFlow for analyzing multi-omics data and genetic associations.
Key contributions include a deep adversarial variational autoencoder for single-cell data analysis and ensemble learning approaches for predicting antidepressant responses. His work spans pharmacogenomic studies, genetic association analyses, and precision medicine applications in schizophrenia and depression.
