Celebrating Achievements Across AIM-AHEAD’s Collaborative Training Programs
From January through September 2025, AIM-AHEAD’s Collaborative Training Programs supported researchers, clinicians, and data scientists pursuing practical training in artificial intelligence and machine learning to advance health research outcomes and promote AI workforce development initiatives across the nation.
Survey responses from participants across the four training programs showed strong progress in technical skill-building, research readiness, and career advancement. These End of Program surveys were developed and disseminated by Research Scientists and Lead Evaluators with the AIM-AHEAD Coordinating Center’s Program Evaluation Office (PEO), in collaboration with each program leadership team. Completed surveys were anonymously submitted, analyzed, and compiled into summarized reports.
AIM-AHEAD All of Us Training Program (Cohort 2)
Trainees in the AIM-AHEAD All of Us Training Program reported high satisfaction with the coursework and mentoring support. Of the 24 trainees, 21 completed the End of Program survey. Based on their responses, mentors received an average rating of 6.67 out of 7 for meeting program expectations, and the program’s impact on professional development was rated 8.67 out of 10. Additionally, 95% of responding trainees indicated that program courses and data use cases helped them complete their research projects.
Trainees cited a range of career milestones as a result of their participation in the training program. Six trainees reported achieving new roles or promotions, such as Postdoctoral Researcher, Postdoctoral Fellow, PhD Intern, and Predoctoral Fellow. Four trainees presented at AI/ML-focused scientific conferences, and five prepared or submitted publications in the field.
Trainees emphasized the guidance of program coaches as being a highlight of their experience in the training program. Eight of the 13 mentors (62%) responded to the survey. The majority reported regularly scheduled meetings with their mentees, including 75% who reported meeting every two weeks. Mentors also rated their effectiveness in supporting professional development highly, averaging 6.12 out of 7.
"I have been able to grow as a mentor from the training provided and especially from the mentee meetings and activities...The experiences navigating the needs, strengths, and support for my mentees who were at very different stages of their career were incredibly valuable."
"The RTI Coaches were extremely knowledgeable with code and the Researcher Workbench. This process could not have been possible without their help."
AIM-AHEAD Bridge2AI AI-READI Training Program (Cohort 1)
Trainees in the AIM-AHEAD Bridge2AI AI-READI Training Program demonstrated strong gains in applying AI/ML to health data. Of the 22 trainee respondents to the Bridge2AI AI-READI Cohort 1 End of Program Evaluation Report, 91% reported they could describe key applications and levels of data risk. Mentoring was highly regarded, with all respondents rating their mentors as good or excellent listeners, and 82% feeling mostly or completely confident presenting AI/ML concepts to colleagues or community members.
Career and research progress included five trainees joining residency programs, taking on academic or governance roles, or receiving promotions. Nine trainees prepared or submitted manuscripts to journals such as Diabetes Technology & Therapeutics and Neurocritical Care.
Among the 13 program mentors, 11 (85%) responded to the survey. All 11 respondents reported having productive meetings with their mentees, and 91% confirmed having effective communication with program staff and sufficient mentoring time.
A strength of the AI-READI traineeship was the specialized training in AI/ML at the intersection of health and biomedical sciences, which is a rapidly growing career and research space that requires extensive knowledge and experience.
The program fosters meaningful partnerships across domains including computer science, biomedical research, and community engagement. This creates a rich environment for developing AI tools that are both scientifically rigorous and socially responsible.
AIM-AHEAD Bridge2AI for Clinical Care Training Program (Cohort 1)
Trainees in the AIM-AHEAD Bridge2AI for Clinical Care Training Program reported high satisfaction with coursework and mentoring. Of the 29 trainees, 23 completed the Bridge2AI Clinical Care Cohort 1 End of Program Evaluation Report, along with all 16 program mentors. Nearly all responding trainees (87%) found the training useful for their projects, with eight strongly agreeing. Confidence was high, with 91% of responding trainees reporting they felt confident or mostly confident in core skills such as formulating hypotheses, presenting AI/ML concepts, and developing analysis plans.
Career and research milestones included three career promotions, two new grant awards, and four conference presentations at meetings such as the Texas Neurological Society and UT Systems AI Symposium. Nine trainees reported multiple publications in progress or accepted and hands-on experience with real-world datasets was consistently highlighted.
All 16 mentor respondents indicated productive meetings with their mentees, and 94% agreed or strongly agreed that communication with program staff was effective and mentoring time sufficient.
One strength of the Bridge2AI Clinical Care Program is the collaborative, data-driven infrastructure,…standardized workflows, and responsible AI development that can be translated into meaningful improvements in patient care.
It gave the trainee a great opportunity to work in a multi-disciplinary team with professionals from all over the nation, strengthened their AI and research skills using clinical data and working on a cloud-based portal.
AIM-AHEAD & NCATS Training Program (Cohort 2)
The AIM-AHEAD & NCATS Training Program earned some of the highest overall ratings of the year. Of 49 trainees, 47 (96%) completed the AIM-AHEAD & NCATS Health Data Science Training Program End of Program Comprehensive Evaluation Report, along with 19 out of 25 mentors (76%) and all eight (100%) of the program’s clinical advisors. Trainees gave an average score of 9.23 out of 10 for professional development and reported high confidence using AI/ML tools, forming hypotheses, and working with real-world health datasets. Mentorship was also rated highly, with an average score of 8.26 out of 10 for overall guidance.
Career and research milestones included six trainees advancing in their careers, four securing grant funding—including the ASRA Early-Stage Investigator Award and 2025 Yale AI Seed Grant—and seven publications in progress. Trainees consistently cited hands-on experience with real-world datasets as a highlight of the program.
Among 19 mentor respondents, 95% agreed that communication with program administrators was effective, and 17 (90%) indicated sufficient time spent with mentees. Most notably, all responding mentors expressed willingness to participate in future cohorts.
Among 19 mentor respondents, 95% agreed that communication with program administrators was effective, and 17 (90%) indicated sufficient time spent with mentees. Most notably, all responding mentors expressed willingness to participate in future cohorts.
It has been both rewarding and transformative. Serving as a mentor sharpened my own communication and leadership skills, while allowing me to reflect on how best to translate complex ideas into actionable insights.
One key strength of the program is its interdisciplinary training approach, which combines technical data science and machine learning research in a cohesive curriculum. The use of real-world datasets like N3C allows trainees to gain hands-on experience applying advanced analytic methods to relevant public health questions.
Note: The AIM-AHEAD ScHARe Training Program (Cohort 1) outcomes are not included in this article, as the End of Program Evaluation Report was still being finalized at the time of publication.