Majid Jaberi-Douraki
Kansas State University, KS·Computer Science
Antibiotic resistance is a growing threat to both people and animals. Fighting it requires knowing how antibiotics are actually used.
- Fields
Computer Science
Public Health & Epidemiology
Medicine & Clinical Research
- Topics
antimicrobial resistance
antibiotic resistance
antimicrobial stewardship
- Grants
- 1 known grant, through Aug 2029
What they work on
- Extract antimicrobial use data for major livestock and poultry species by building the LAMU-AI web-crawler, which applies machine learning and a large language model to FARAD records and regulatory data.
- Extend antimicrobial use data collection to minor species and companion animals, drawing on veterinary teaching hospitals and online repositories.
- Develop a secure Big Data dashboard and visualization system that combines FARAD databases and regulatory testing data to show antibiotic use trends in real time.
More about the research
In veterinary medicine, however, data on antibiotic use in farm animals and pets are scattered and incomplete. This project aims to fill those gaps by gathering antimicrobial use data automatically, combining sources into one system and updating it in real time.
Why it matters
Real-time data on antibiotic use in livestock, poultry and pets could help veterinarians, food producers and regulators make better decisions about when and how to use antimicrobials. That evidence could support efforts to slow antibiotic resistance, a public-health problem shared by animals and humans.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Renata Ivanek Miojevic
Cornell University, NY·Public Health & Epidemiology
Collect detailed, complete and validated multi-year records of antimicrobial use at the individual animal level on dairy farms.
Bradford Becken
University of Nebraska Medical Center, NE·Medicine & Clinical Research
Assess the translation potential of an automated dynamic antibiogram through experiential learning and first-hand interviews across the healthcare industry ecosystem.
Dongxiao Zhu
Wayne State University, MI·Computer Science
Develop optimization algorithms that make large language model unlearning, removing specific data influences without retraining, more effective, robust and efficient.
The school
Kansas State University: 7 labs on PI Pages, $265M a year on research, 201 research doctorates a year.
Reach out
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