University of Wisconsin–Madison, US

Daifeng Wang is an Assistant Professor in Department of Biostatistics and Medical Informatics and an Investigator in Waisman Center at University of Wisconsin–Madison. His research focuses on developing interpretable machine learning approaches and bioinformatics tools to analyze multi-omics data for understanding functional genomics and gene regulation in the human brain; e.g., he recently developed interpretable deep neural network modeling for single-cell deconvolution and genotype-phenotype prediction to reveal the molecular mechanisms and functional pathways in human brain disorders. He is currently working on deciphering single-cell functional genomics for deep phenotypes across brain diseases such as neuropsychiatric and neurodegenerative diseases, aiming to discover the regulatory mechanisms and genomic engineering principles for precision medicine.

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Speaker at
13-14 February 2020, Leuven Belgium