John Wenskovitch, a visual analytics researcher at Pacific Northwest National Lab, is an adjunct professor in the Department of Computer Science. He received a Ph.D. in computer science from Virginia Tech in 2019 and was a student at the Discovery Analytics Center, advised by Chris North.
His current work focuses on the interconnecting roles of visualization and machine learning in visual analytics systems and primarily addresses the question, “How can machine learning support visualization?” In contrast to recent work in Explainable AI, which explores methods by which visualization can support machine learning, Wenskovitch explores techniques to enable systems to infer the interests and intentions of the interacting user, thereby adapting and personalizing the visualization and underlying models.
Wenskovitch has also engaged in interdisciplinary research with colleagues in architecture, astronomy, computational and molecular biology, electronic art, medicine and nursing, and statistics.
He received a master’s degree in computer science from the University of Pittsburgh in 2011. He was a research intern at FXPAL and previously taught in the Mathematics Department at Chatham University and in the Computer Science Department at Allegheny College.