  We report a framework that enables the wide adoption of authentic research
educational methodology at various schools by addressing common barriers. The
guiding principles we present were applied to implement a program in which
teams of students with complementary skills develop useful artificial
intelligence (AI) solutions for researchers in natural sciences. To accomplish
this, we work with research laboratories that reveal/specify their needs, and
then our student teams work on the discovery, design, and development of an AI
solution for unique problems using a consulting-like arrangement. To date, our
group has been operating at New York University (NYU) for seven consecutive
semesters, has engaged more than a hundred students, ranging from first-year
college students to master's candidates, and has worked with more than twenty
projects and collaborators. While creating education benefits for students, our
approach also directly benefits scientists, who get an opportunity to evaluate
the usefulness of machine learning for their specific needs.
