HCII Seminar Series - Leilani Battle
Speaker
Leilani Battle
Assistant Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington and co-director of the UW Interactive Data Lab
When
-
Where
Newell-Simon Hall 1305
Video
Panopto
Description
"Behavior-Driven Optimization for Interactive Data Exploration"
Analysts need the ability to intuitively explore their data before deciding how to clean it, model it, and present it to key decision makers. With the abundance of massive datasets in industry and science, analysts also need exploration systems that can process data quickly and efficiently, otherwise these systems will fail to keep pace with a user’s analytic flow. Addressing these challenges requires a deeper understanding of not only how system behavior influences user performance, but also how user behavior influences system performance. In this talk, I will discuss a range of performance problems observed when designing systems to support interactive analytics over large datasets. Then, I will present a set of complementary techniques for modeling human analysis behavior and discuss how these models can be leveraged to test as well as enhance data science system and user interface design.
Speaker's Bio
Leilani Battle is an Assistant Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington and co-director of the UW Interactive Data Lab. Her research spans the areas of data management, HCI, and data visualization. Her research interests focus on developing interactive data-intensive systems that can aid analysts in performing complex data exploration and analysis. Prof. Battle has received early career awards from both the database (2022 TCDE Rising Star Award) and visualization (2023 IEEE VGTC Significant New Researcher Award) research communities. She was named one of the 35 Innovators Under 35 by the MIT Technology Review in 2020 and was selected as a Sloan Fellow in 2023. Her research has been supported by several organizations, including Adobe, VMWare, Google, the ORAU, and the National Science Foundation (via the GRF, CISE CRII and CISE CAREER programs). In 2017, she completed a postdoc in the UW Interactive Data Lab. She holds an MS (2013) and PhD (2017) in Computer Science from MIT, where she was a member of the MIT Database Group, and a BS in Computer Engineering from UW (2011) as part of the UW database group.