Doris Jung-Lin Lee is a Ph.D. student at UC Berkeley, working with Aditya Parameswaran. Her research interests lie in interactive data analytics, visualization, and human-computer interaction. She received her bachelor’s degree in physics and astrophysics from UC Berkeley in 2016.
Doris’s research aims to design systems that improve the productivity of data scientists by providing automated guidance in visual data exploration and machine learning development. Often, analysts may not know which visualization or machine learning model decisions would lead to desired insights or performance, leading to wasted efforts in manual searching. Analysts can also be overwhelmed or lose track of where to look across a large potential space of visualizations, model, and parameter configurations, leading to suboptimal or even potentially erroneous selections.
To accelerate data exploration, Doris has developed several visualization recommendation systems that guide users to their high-level discovery goals, while eliminating the manual and tedious parts of the data exploration process. For assisting with machine learning development, her research contributes to the design of a human-in-the-loop machine learning platform that enables users to work collaboratively with machines in search of an optimal workflow.
For more information about Doris’s research and publications, please visit her website.