Mostafizur Rahman
University of Missouri-Kansas City, MO·Computer Science
Alcohol and drug abuse are rising worldwide. They contribute to accidents, violence, suicide, anxiety, and depression.
- Fields
Computer Science
Engineering
Public Health & Epidemiology
- Topics
artificial intelligence
machine learning
networked sensing
- Grants
- 1 known grant, through Jun 2027
What they work on
- Develop non-invasive sensing approaches, which avoid penetrating the skin or collecting bodily fluids, for gathering data on alcohol and drug use as a more reliable alternative to self-reports.
- Develop secure, privacy-aware AI analytics that pull actionable information from diverse alcohol and drug data while accounting for context such as health history and criminal record.
- Train up to 120 master's and doctoral students in AI, networking, cybersecurity, and sensors through project-based learning with healthcare and legal partners, including ethics and leadership training.
More about the research
Yet the data used to guide treatment come mostly from unreliable self-reports, invasive tests of blood, breath, or sweat, or indirect interviews. Non-invasive sensors combined with artificial intelligence (AI) could collect and analyze this data far better. Doing so raises hard technical and ethical questions, especially about keeping personal health and legal information secure and private.
Why it matters
Better, non-invasive ways to measure alcohol and drug use could give clinicians more reliable data than self-reports. This could help improve treatment for people struggling with substance abuse. Privacy-aware AI analysis could also make it possible to use sensitive health and legal data responsibly. The program also aims to build a workforce trained to apply AI and secure sensing to this crisis and to other social problems.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Briget Eastep
Western Colorado University, CO·Ecology & Evolution
Develop, implement and assess adaptive management strategies for public lands, designing interventions as experiments to measure their effects on species and ecosystems.
Tahir Ekin
Texas State University, TX·Computer Science
Develop an Applied AI Summer School and new course modules in data analytics, Python, deep learning, natural language processing and computer vision for students in non-AI disciplines, using inclusive and contextualized teaching methods.
Margaret SobkowiczKline
University of Massachusetts-Lowell, MA·Materials Science
Train 60 master's and Ph.D. students from engineering, chemistry, earth science, biology, public health and economics in interdisciplinary research on materials that protect water resources.
The school
University of Missouri-Kansas City: 7 labs on PI Pages, $57M a year on research, 94 research doctorates a year.
Reach out
A start for your email. Fill in the brackets.