University of Rochester Goergen Institute for Data Science

Overview

NSF NRT: Graduate Training in Data-Enabled Research into Human Behavior and its Cognitive and Neural Mechanisms

Welcome to the University of Rochester’s new interdisciplinary graduate education program sponsored by the National Science Foundation. This program will help PhD and Masters students learn how to harness the burgeoning power of data science to understanding the neural foundations of human behavior, and how to apply these skills in industrial and academic settings. The NSF Research Traineeship (NRT) program is a new graduate education initiative focused on Data-Enabled Science and Engineering (DESE) research.

All graduate students from all disciplines at the university are welcome to participate in NRT activities. In addition, each year a group of PhD students from Brain & Cognitive Science and Computer Science will be selected to receive a one-year BCS/CS NRT fellowship to support their graduate work.

Motivation

Understanding the cognitive and neural basis of human behavior is one of the most fundamental areas of scientific inquiry for the 21st century. It will impact almost every facet of human existence, including commerce, education, healthcare, and national security, as well as basic science. Major advances will be made by a new generation of scientists and engineers who are cross-trained to blend expertise in data science and computer science with a deep understanding of experimental approaches to collecting and analyzing neural and behavioral data. We propose a novel graduate training program at the interface of data science, artificial intelligence, cognitive science, and neuroscience.

At least four properties distinguish our proposal from existing programs. First, by focusing on understanding the nature of intelligence, both artificial and biological, our program will provide students with an integrated, multidisciplinary training experience encompassing computer science, brain and cognitive sciences, and as related disciplines. Second, our program will use theories and methods from data science (including machine learning and statistics) to provide students with a foundation for theory development, computational modeling, and data analysis. This foundation will serve as a conceptual and methodological framework unifying their studies of artificial and biological intelligence. Third, by emphasizing both practical applications and basic science, our program will train students to design research solutions relevant to today's societal needs as well as develop research approaches of critical importance to future needs. Finally, the hands-on, project-oriented nature of our program will provide students with the capabilities needed to conceptualize, design, and implement large-scale research projects from beginning to end.