福利片国产

School of Public Health

About AI for Health Research Lab

Header: AI for Health Research Lab

The UofM AI for Health Research Lab seeks to develop innovative, ethically grounded applications of artificial intelligence to improve public health outcomes. As part of the university鈥檚 broader investment in AI and health鈥攊ncluding the Center for Responsible Artificial Intelligence in Public Health and the 鈥淎I for All鈥 academic programs鈥攖he Lab addresses critical challenges across multiple domains.

AIM-AHEAD

The AIM-AHEAD Consortium is a National Institutes of Health (NIH) initiative designed to expand the use of artificial intelligence (AI) and machine learning (ML) in health research. It supports institutions in building AI/ML capacity through targeted resources, training and collaborative opportunities that advance research activities.

Application of Artificial Intelligence in Treatment
Development for Substance Use Disorders
AIM AHEAD: Application of Artificial Intelligence in Treatment

With support from the Program for Artificial Intelligence Readiness (PAIR), the 福利片国产 of Memphis has established the AI for Health Research Lab. While the Lab鈥檚 initial focus is on substance use disorder, its work extends to other pressing areas such as maternal and child health, food and nutrition, mental health and broader efforts in preventive health and disease prevention. The Lab also seeks to incorporate generative AI (GenAI) tools to enhance public health education and communication, encourage healthy behaviors and support student training and faculty development.

AIM-AHEAD - PAIR Cohort 2026


Bowie State 福利片国产
California State 福利片国产 - San Marcos
Georgia State 福利片国产
Illinois State 福利片国产
Penn State 福利片国产
Santa Clara 福利片国产
福利片国产 of Memphis
福利片国产 of Georgia
福利片国产 of Hawai鈥檌 - Manoa
福利片国产 of Massachusets - Lowell
福利片国产 of Nebraska - Lincoln
Universidad de Puerto Rico
福利片国产 of Texas - San Antonio


 

A key component of this initiative is the CRA, which provides structured support to institutions for establishing AI/ML health research laboratories. The PAIR program includes a two-phase funding model:

Phase 1: Provides up to $100,000 for institutional teaming and training, with an emphasis on forming multidisciplinary teams, refining research concepts, and engaging with AIM-AHEAD resources.

Phase 2: Provides up to $150,000 to launch research labs, conduct exploratory projects, and prepare for future NIH grant submissions such as R01 or R21.

This research is supported by the National Institutes of Health (NIH) under Agreement No. 1OT2OD032581.

Team

CRAIPH brings together a team of faculty, students and partners with expertise in AI, health research, systems science and applied analytics.

 
Headshot of Ricky Leung

Ricky Leung, PhD, MPhil, MS
Director and Principal Investigator, Professor of Social and Behavioral Sciences

Headshot of Dipankar Dasgupta

Dipankar Dasgupta, PhD
Co-Principal Investigator, Hill Professor in Cybersecurity

Headshot of Satish Kedia

Satish Kedia, PhD, MPH, MS
Associate Dean, Administration and Faculty Affairs, Professor

Headshot of Arunava Roy

Arunava Roy, PhD
Research Assistant Professor at the Center for Information Assurance (CfIA)

Headshot of Rameshwari Prasad

Rameshwari Prasad, MBBS, MPH
Public Health Scholar, PhD Candidate in Social and Behavioral Sciences

Joomi Kim, MS
First-year PhD student

Headshot of Sharon Griffin

Sharon Griffin, PhD, MBA, MPM
Senior Project Manager

Join the Lab

While initially focused on substance use disorder, its scope includes maternal and child health, aging, nutrition, mental health, food, disease prevention and preventive health. The Lab also utilizes generative AI tools to advance public health education and communication, promote healthy behaviors and support student training and faculty development. Through these efforts, the Lab aims to strengthen research capacity and cultivate a diverse, skilled workforce prepared to lead in AI-driven public health innovation. Join our team today by emailing aihr@memphis.edu or connecting with us on .

 

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Multimodal Data Sources
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Substance Use Disorder (SUDs)
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Early Intervention Strategies
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Behavioral Change
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Populations Affected by Addiction
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Mental Health Challenges
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Chronic Diseases