Visual Pattern Exploration At and Across Scales

Explore cutting-edge visualization systems and interaction techniques for efficient pattern discovery in large-scale scientific datasets. Delve into a 55-minute colloquium presentation by Fritz Lekschas, a Ph.D. candidate from Harvard University, as he discusses visual pattern exploration at various scales. Learn about a web platform for browsing multi-modal and multi-scale datasets, a framework for interactively arranging and aggregating pattern instances, and the integration of interactive visual machine learning to enhance pattern finding. Gain insights into how these innovative approaches can be applied to genomic, geospatial, and time-series data, ensuring effective human-in-the-loop data analysis for increasingly complex scientific datasets. Discover how Lekschas's research combines visualization and human-centered machine learning to address challenges in exploring sparsely-distributed patterns and uncertain data.

Allen School Colloquium: Fritz Lekschas (Harvard University)