We report a methodology in which students gain experience in authentic research by developing artificial intelligence (AI) solutions for researchers in natural sciences. 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. In order to accomplish this, we work with research laboratories that reveal/specify the needs they have, and then our student teams work on the discovery, design, and development of an AI solution for unique problems using a consulting-like arrangement. Our design addresses common barriers which appear in most existing authentic research education approaches and thus is suitable for wide adoption at various schools. To date, our group has been operating at New York University (NYU) for five consecutive semesters and has engaged more than seventy students, ranging from first-year college students to master's candidates, and worked on more than 15 projects with 14 collaborators.

翻译：我们报告了一种方法论，学生通过为自然科学研究者开发人工智能（AI）解决方案，获得真实研究的经验。该方法在为学生创造教育益处的同时，也直接惠及科学家，使他们能够评估机器学习对其特定需求的实用性。为实现这一目标，我们与研究实验室合作，这些实验室揭示/明确其需求，随后我们的学生团队采用类似咨询的方式，针对独特问题发现、设计和开发AI解决方案。我们的设计克服了大多数现有真实研究教育方法中常见的障碍，因此适合在各类学校广泛推广。迄今为止，我们的团队已在纽约大学（NYU）连续运行五个学期，吸引了超过70名学生（涵盖大一新生至硕士研究生），并与14位合作者共同完成了15个以上的项目。