Date: March 26, 2018
Time: 10:40 AM - 12:00 PM
Location: Room E404, CSE Building
Host: UF CISE Department
Admission: This event is free and open to the public.
Theory-guided Data Science: A New Paradigm for Scientific Discovery From Data
Abstract: This talk will introduce theory-guided data science, a novel paradigm of scientific discovery that leverages the unique ability of data science methods to automatically extract patterns and models from data, but without ignoring the treasure of knowledge accumulated in scientific theories.
Theory-guided data science aims to fully capitalize the power of machine learning and data mining methods in scientific disciplines by deeply coupling them with models based on scientific theories. This talk will describe several ways in which scientific knowledge can be combined with data science methods in various scientific disciplines such as hydrology, climate science, aerospace and chemistry.
To demonstrate the value in combining physics with data science, the talk will also introduce a novel framework for combining deep learning methods with physics-based models, termed as physics-guided neural networks, and present some preliminary results of this framework for an application in lake temperature modeling.
The talk will conclude with a discussion of future prospects in exploiting latest advances in deep learning for building the next generation of scientific models for dynamical systems, where theory-based and data science methods are used at an equal footing.
Biography: Anuj Karpatne is a Postdoctoral Associate at the University of Minnesota, where he develops data mining methods for solving scientific and socially relevant problems in Professor Vipin Kumar’s research group. Karpatne has published more than 25 peer-reviewed articles at toptier conferences and journals (e.g., KDD, ICDM, SDM, TKDE, and ACM Computing Surveys), given multiple invited talks, and served on panels at leading venues (e.g., SDM and SSDBM). Karpatne’s research has resulted in a system to monitor the dynamics of surface water bodies on a global scale, which was featured in an NSF news story. He is also a co-author of the second edition of the textbook Introduction to Data Mining. He received his Ph.D. in September 2017 from the University of Minnesota. Before joining the University of Minnesota, Anuj received his bachelor’s and master’s degrees from the Indian Institute of Technology Delhi.