PROJECT SUMMARY
The proposed training program aims to address the lack of specialized training in Artificial Intelligence (AI) and
Machine Learning (ML) methods for addiction research in Mississippi’s major universities. The program is
featured by its evidence-based multimodalities and extensive interdisciplinary collaboration across three
campuses (University of Mississippi at Oxford, University of Mississippi Medical Center at Jackson, and the
historically black university Jackson State University). The program emphasizes fostering a diverse data
science workforce by collaborating with Jackson State University and making concerted recruitment efforts to
engage underrepresented students at other participating campuses. The program encompasses five integrated
components that create a progressive learning pathway while ensuring sustainability, including webinars (W),
summer academies (A), symposiums (S), a research lab (R), and an e-learning platform (E) branded as
WAS_RE. The novel creation of a progressive learning pathway facilitates underrepresented students' access
to studying AI/ML for addiction research and their engagement throughout the learning process. The WAS_RE
program begins with a series of webinars to raise campus-wide awareness and interest in applying AI/ML for
addiction research. It then progresses to the recruitment of dedicated undergraduate and graduate students (n
= 20 annually) and provides them with expert-led hands-on training during a four-week summer academy,
including a symposium day at the end to further enrich the learning experience. The program will then further
establish a dedicated research lab as a central hub for collaborative mentoring, providing mentored research
experiences to motivated undergraduate and graduate students (n = 6 annually) who have participated in the
summer academy or have equivalent capacities in applying AI/ML for addiction research. Furthermore, the
program will create an e-learning platform to expand the program’s reach by distributing webinar recordings
and to ensure sustainability through offering a self-paced course adapted from the summer academy
curriculum. The successful implementation of this training program is expected to produce a well-trained,
diverse workforce proficient in data science methods for addiction research, inspire students to pursue
advanced degrees in this field, foster enduring collaborations across disciplines and institutions, and advance
the field’s ability to tackle intricate addiction challenges.
