WIP: Building a Research Experience for Undergraduates in Quantum Machine Learning

This work in progress research-to-practice study describes the development of a new undergraduate research training site on Quantum Machine Learning (QML), hosted at Arizona State University, a large Hispanic-Serving Institution. The objectives of this project are to a) recruit and prepare students from diverse pathways to increase representation of those traditionally underrepresented in QML research, b) increase awareness of career opportunities in the QML field, c) engage students in theoretical and experimental quantum information processing and machine learning (ML), d) motivate students to continue QML research into graduate school, and e) provide professional development training including presenting to stakeholders, developing publications/patents, and building an awareness on social implications, ethics, and privacy. The project adopts an integrative theory, application, and hands-on training approach by immersing undergraduate students in ML algorithm and quantum computing studies with hands-on quantum circuit design tasks. Participants are embedded in research labs, guided by graduate students and faculty mentors on quantum computing research studies. The program is evaluated by both the Center for Evaluating the Research Pipeline (CERP) and an independent evaluator. Formative and summative assessments include pre- and post-surveys, a mid-point check-in survey, and a document review of program deliverables. Findings are described in a final evaluation report. This paper describes the importance of introducing QML research at the undergraduate level, methods for recruiting a diverse group of participants, program format, research projects, and preliminary program evaluation results.