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Committee
Symposium Chairs
Dr. 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.
Alvitta Ottley (Vice-Chair)
Alvitta Ottley is an Associate Professor in the Department of Computer Science & Engineering at Washington University in St. Louis. She also holds a courtesy appointment in the Department of Psychological and Brain Sciences. Her research uses interdisciplinary approaches to solve problems such as how best to display information for effective decision-making and how we can design human-in-the-loop visual analytics interfaces that are more attuned to how people think.
Paper Chairs
Dr. Anamaria Crisan is an Assistant Professor of Computer Science at the University of Waterloo. She conducts interdisciplinary research that integrates techniques and methods from machine learning, human-computer interaction, and data visualization. Her research focuses on the intersection of Data Science and Data Visualization, especially toward the way humans can collaboratively work together with ML/AI systems through visual interfaces. Before joining the University of Waterloo, she was a Lead Research Scientist at Tableau.
Dr. Dylan Cashman is an assistant professor in the Michtom School of Computer Science at Brandeis University, where he teaches classes on data visualization as well as core computer science courses. He previously worked in the Data and AI division at Novartis, in Cambridge MA. As a senior expert in data science and advanced visual analytics, he had an impact on many projects through all phases of the drug development process. He received his PhD in Computer Science at Tufts University. Focusing on Data Visualization and Machine Learning, he has built libraries for visualization, data science, and artificial intelligence.
Web/Tech Chair
Saugat Pandey is a Ph.D. candidate in the Visual Interface and Behavior Exploration Lab at Washington University St. Louis. His research investigates visualization literacy and employs state-of-the-art computer vision techniques to understand the perceived beauty of the visualizations in the wild.
Steering Committee
Liang Gou is a Director of AI at Splunk. His research interests lie in the fields of visual analytics, deep learning and human-computer interaction. Before joining Splunk, Liang was a Principal Research Scientist at Bosch Research and Visa Research and a Research Staff Member at IBM Almaden Research Center.
Adam Perer is an Assistant Research Professor at Carnegie Mellon University, where he is a member of the Human-Computer Interaction Institute. His research integrates data visualization and machine learning techniques to create visual interactive systems to help users make sense out of big data. Lately, his research focuses on human-centered data science and extracting insights from clinical data to support data-driven medicine. This work has been published at premier venues in visualization, human-computer interaction, and medical informatics. He was previously a Research Scientist at IBM Research. He holds a Ph.D. in Computer Science from the University of Maryland, College Park.