A problem amongst many institutions is the lack of resources to create meaningful interdisciplinary partnerships together. Working with those from various disciplines will result in better projects and research opportunities for faculty. Students involved in these opportunities gain a deeper understanding of how their field can be implemented in another field. Application X is a novel web application developed to expand resources for Institution X to break the boundaries of student and faculty specializations to create more collaborative learning opportunities across disciplines. Within this application, faculty can find, reach out, and connect with faculty in other disciplines, based on their common interests. These faculty can create collaborations across their courses and inspire projects that bring together students from different backgrounds such as STEM and humanities to work with one another to benefit a community partner in terms of social good. Once projects have been completed, faculty members can upload information about completed projects, which can then be reviewed by other users of Application X, and potentially inspire them to develop their own collaborations. Application X implements principles of human computation and collective intelligence; reviews can help Application X become self-sustaining and maintain the reliability of the information. This poster will discuss the design of an algorithm that recommends faculty for potential course collaborations. The unique challenge encountered in this research was how to develop an algorithm that matches faculty from dissimilar disciplines but who have similar interests outside of their own disciplines.