III: Medium: Collaborative Research: Towards Effective Interpretation of Deep Learning: Prediction, Representation, Modeling and Utilization

Principal Investigator: Eric Ragan

Sponsor: National Science Foundation

Start Date: August 15, 2019

End Date: July 31, 2023

Amount: $118,562


While deep learning has achieved unprecedented prediction capabilities, it is often criticized as a black box because of lacking interpretability, which is very important in real-world applications such as healthcare and cybersecurity. For example, healthcare professionals would appropriately trust and effectively manage prediction results only if they can understand why and how a patient is diagnosed with prediabetes. The project is to investigate the interpretability of deep learning by following the fundamental elements in a data mining practice from representation, modeling to prediction. The results of the project are expected to improve the usability of deep learning in important applications, positively boosting the overall value of the deep learning based information systems. The education program that integrates data science, industrial engineering, and visualization is to train students with data analytics technologies in industrial systems, to attract and mentor members of underrepresented groups pursuing careers in STEM.

More Information: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1900767&HistoricalAwards=false