Design and implementation of a scalable authentic-research education program for Artificial Intelligence and Science
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We report a program designed to bring authentic research experience to machine learning and science students at scale. Our design addresses common barriers to such efforts and should allow students and faculty from other universities to implement similar programs with ease. With support from a faculty member, students form a group. The group contains several teams working on independent projects in a consulting type of arrangement with research labs in natural sciences. Each team comprises students with complementary skills (in AI, science, and leadership). Labs provide the data, and the teams work on the discovery, design, and development of an AI solution. A student leadership team manages the student group. This team interviews applicants, forms other teams, sets up standards for operations, fosters collaborations, and ensures the continuity of multi-semester projects. To date, this group has run for three consecutive semesters and has engaged more than forty students, ranging from first-year college students to master's candidates. This effort has resulted in over a dozen successful collaborations with academic and industry partners.
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