REU Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach

This Research Experiences for Undergraduates (REU) Site Program at the University of North Texas will enhance the knowledge and research skills of a diverse cohort of undergraduate students through empowering, innovative, and interdisciplinary research experiences in developing Deep Learning applications and systems. The program aims to 1) expose undergraduate students to real-world and cutting-edge research focused on accelerated deep learning through combined hardware and software development; 2) encourage more undergraduate students to continue their academic careers and seek graduate degrees in computer science, computer engineering, and related disciplines; 3) develop research skills and improve communication and collaborative skills in undergraduate students.

The emphasis of this program is on the interdisciplinary research experience for the REU students to gain hardware-software codesign skills. REU students will be mentored by experienced researchers in the area of AI/machine learning algorithms, computer system and architecture, biomedical informatics and computational life science.

Ten students will be hosted on the University of North Texas campus each summer where they closely collaborate with faculty and graduate students in performing innovative research that will address the timely and critical problems in developing Deep Learning systems and algorithms. Through their projects, the students will be able to observe the connections and interactions between different disciplines involving hardware and software.

The REU students will also be formally trained in the process of collaborative and responsible research including ethics, teamwork and leadership. The program will also help the students to improve their communication abilities and writing skills through activities such as oral presentations and technical reports. Through this program, the students will be empowered with research skills and experience to empower their journey to become successful researchers.

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.