REU Site: Intelligent and Scalable Systems

Lehigh University, Bethlehem PA

Investigators

Abstract

The Intelligent and Scalable Systems Research Experiences for Undergraduates (REU) site provides an inspirational and successful research experience for 10 undergraduate students over a 10 week period at Lehigh University. Over the summer, participants learn how to harness the incredible potential of machine learning, and the unprecedented power of modern parallel compute resources, to invent new systems and algorithms that are infused with intelligence and hence capable of solving pressing societal problems. The proposed REU Site employs a multifaceted recruiting strategy, with a focus on encouraging women, underrepresented, and minority students to participate; a special focus will be placed on recruiting from institutions that lack undergraduate research opportunities. Students will also benefit from a program of seminars and tutorials designed to ensure that they are ready to collaborate, knowledgeable about the key concepts and technologies in modern intelligent and scalable systems, and inspired to pursue both further education and life-long careers in Computer Science. The objective of this ten-week summer research experience is to increase the number and diversity of students pursuing graduate degrees in computer science, around the timely theme of intelligent and scalable systems. This REU Site will facilitate research into fundamental topics in both machine learning and scalable computer systems, such as new algorithms for machine learning, new approaches to privacy preservation, and new techniques for increasing the performance of parallel programs. It will also support application-focused research, with an emphasis on creating solutions to hard problems in both research and society. Through seminars and faculty-supervised collaborative projects, participants will learn about the research process, hone their software development skills, improve their comfort with technical communication, become knowledgeable about graduate school and its application process, and ultimately develop greater confidence in their ability to succeed in a Science/Technology/Engineering/Math career. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.