Mark Craven

Mark Craven is a Professor at the University of Wisconsin-Madison, holding dual appointments in the Department of Biostatistics and Medical Informatics and the Department of Computer Sciences. He leads the NIH-funded Computation and Informatics in Biology and Medicine (CIBM) Training Program and is affiliated with the Carbone Cancer Center and the Center for Genomic Science Innovation. His research focuses on machine learning applications in biological networks, clinical data analysis, and biomedical text mining.

Craven’s work emphasizes interpretable machine learning, active learning, and weak supervision techniques. Key projects include modeling host-virus interactions, gene regulatory networks, and clinical risk prediction from electronic health records. He has contributed to tools like the EDGE platform for toxicogenomic analysis and developed methods for extracting insights from biomedical literature.

Publications highlight advancements in viral replication networks, temporal data modeling, and multi-omics profiling. His team’s work spans bioinformatics, computational biology, and healthcare informatics, with applications in asthma, surgical outcomes, and genetic risk assessment. Craven teaches machine learning courses and mentors a vibrant research group, fostering interdisciplinary collaborations across computer science and life sciences.

Affiliations include the NIH’s Center for Predictive Computational Phenotyping and the Center for Genomic Science Innovation. His research integrates computational methods with biological and clinical data to address complex problems in health and disease.