Masoud Rouhizadeh, PhD, FAMIA
Assistant Professor; Lead, Intelligent Critical Care Center (IC3)
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About Masoud Rouhizadeh
Dr. Masoud Rouhizadeh is a computer scientist by training with nearly two decades of experience building AI and machine learning systems for healthcare. At the University of Florida, he directs the Medical AI Research (MAIR) Lab, leads the AI Collaboration Hub at the Intelligent Critical Care Center (IC3), and is part of UF’s AI in the Health Sciences Initiative. He was elected a Fellow of the American Medical Informatics Association (FAMIA) in 2025.
Before joining UF, he was a faculty member at Johns Hopkins Medicine, where he co-founded the Center for Clinical Natural Language Processing (C2NLP) and led NLP at the Institute for Clinical and Translational Research; he holds an adjunct appointment in the Johns Hopkins Division of Biomedical Informatics and Data Science. He completed postdoctoral training at the University of Pennsylvania and earned a PhD and MS in Computer Science and Engineering from Oregon Health & Science University, a Professional Master’s in Human Language Technology from the University of Trento, and an MA in Linguistics. His research has been funded by the CDC, NIA, NIMH, NIMHD, FDA, NIDA, and PCORI.
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Lead
2024 – Current · AI Collaboration Hub, Intelligent Critical Care Center (IC3)
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Core Member
2023 – Current · AI Task Force, UF College of Pharmacy
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Adjunct Assistant Professor
2021 – Current · Johns Hopkins University
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Co-Founder
2018 – 2021 · Johns Hopkins Center for Clinical NLP (C2NLP)
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Faculty Instructor
2017 – 2021 · Biomedical Informatics and Data Science, Johns Hopkins Medicine
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NLP Lead
2017 – 2021 · Institute for Clinical and Translational Research, Johns Hopkins Medicine
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NLP Specialist
2017 – 2021 · Center for Language and Speech Processing (CLSP), Johns Hopkins School of Engineering
Teaching Profile
Courses Taught
Teaching Philosophy
Dr. Rouhizadeh’s teaching centers on hands-on experience with applied AI, preparing students for an increasingly data-driven healthcare landscape. He has developed and coordinated graduate courses in biomedical informatics and clinical natural language processing, led AI training for clinical faculty and staff, and was nominated for the College of Pharmacy’s 2024 Teaching Team Award.At UF, he is helping shape how the next generation of pharmacists and researchers learns to work with AI: developing an AI integration roadmap for the PharmD curriculum, a college-wide AI certificate, and a graduate course on practical AI methods for pharmacy research, and contributing to UF’s MS in AI in Biomedical and Health Sciences. He has mentored graduate students, clinicians, and faculty into leading roles across industry, academia, and government.
Research Profile
Dr. Rouhizadeh builds resource-efficient, auditable large language model (LLM) systems that turn unstructured EHR notes into computable phenotypes, risk prediction, and clinical decision support at health-system scale. His signature Screen-and-Reason framework separates finding from interpreting: a high-recall screen reads under 5% of the record while recovering over 99% of relevant mentions, and an auditable clinical reasoning cascade interprets what survives, cutting computational and annotation costs by 90–95% and capturing confirmed negatives, a category structured data cannot represent.
These methods identify 20 to 25 times more cases of substance use, suicide risk, and social needs than diagnosis codes, and they run in production rather than in demonstration: HIPAA-compliant pipelines process more than 70,000 clinical notes daily at UF Health, within multi-institutional networks spanning 700M+ notes and 26M+ patients (OneFlorida+, PCORnet, N3C, OHDSI). As Segment PI in the NIH/NIA-funded 1Florida Alzheimer’s Disease Research Center, he extends this work to aging safety and early detection, and pairs record-derived signal with molecular data for precision medicine in cardiology and oncology.
0000-0002-9006-6112
Areas of Interest
- Behavioral health, substance use, aging safety, and social determinants of health
- Clinical natural language processing (NLP) and large language models (LLMs)
- Computable phenotyping, risk prediction, and clinical decision support
- Multimodal AI for precision medicine
- Privacy-preserving clinical AI infrastructure and federated research
Publications
Academic Articles
Presentations
Grants
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Assessing Barriers and Facilitators for Participating Structured Lifestyle Intervention
- Role:
- Co-Investigator
- Funding:
- EMORY UNIV via CTRS FOR DISEASE CONTROL AND PREVENTION
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Assessing Barriers and Facilitators for Participating Structured Lifestyle Intervention and Its Real-world Effectiveness and Cost-effectiveness among US Veterans
- Role:
- Co-Investigator
- Funding:
- CTRS FOR DISEASE CONTROL AND PREVENTION
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1Florida Alzheimer’s Disease Research Center
- Role:
- Project Manager
- Funding:
- NATL INST OF HLTH NIA
Education
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Postdoctoral Training in Biomedical Informatics and Data Science
University of Pennsylvania
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Ph.D. in Computer Science and Engineering
Oregon Health and Science University
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M.Sc. in Computer Science and Engineering
Oregon Health and Science University
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Professional Master’s in Human Language Technology and Interfaces
University of Trento
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M.A. in Linguistics
Allameh Tabatabai University
Contact Details
- Business:
- (352) 273-9397
- Business:
- mrouhizadeh@ufl.edu
- Business Mailing:
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PO Box 100496
GAINESVILLE FL 32610 - Business Street:
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1889 Museum Rd.
Room 6012
Malachowsky Hall for Data Science and IT
Gainesville FL 32611