Skip to main content Skip to main menu
UF Health University of Florida
Winterstein Research Group College of Pharmacy
Masoud Rouhizadeh

Masoud Rouhizadeh, PhD, FAMIA

Assistant Professor; Lead, Intelligent Critical Care Center (IC3)

Department: Pharmaceutical Outcomes & Policy
Business Phone: (352) 273-9397
Business Email: mrouhizadeh@ufl.edu

On This Page

About Masoud Rouhizadeh

Dr. Masoud Rouhizadeh is a computer scientist and engineer by training with nearly two decades of hands-on experience building AI and machine learning systems for healthcare.

At the University of Florida, he leads the AI Collaboration Hub at the Intelligent Critical Care Center (IC3) and is part of UF’s AI in Health Sciences initiative. His work centers on clinical natural language processing (NLP), developing large language model (LLM), transformer, and deep learning systems that turn unstructured healthcare data into reliable, clinically meaningful evidence. 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 co-led AI and NLP initiatives at the Institute for Clinical and Translational Research. He now holds an Adjunct Assistant Professor appointment in the at Johns Hopkins Division of Biomedical Informatics and Data Science.

He completed his postdoctoral training at the University of Pennsylvania’s Institute for Biomedical Informatics and holds a PhD and MS in Computer Science and Engineering from Oregon Health & Science University, along with a Professional Master’s in Human Language Technology from the University of Trento, Italy. His research focuses on translational work that develops machine learning and LLM pipelines to identify social, behavioral, and mental health outcomes, substance use patterns, and Alzheimer’s disease risk factors, together with the informatics infrastructure that scales these methods across multi-site research networks. This work is supported by funders including the CDC, NIA, NIMHD, FDA, NIDA, and PCORI. A consistent theme of his work is moving AI from prototype to practice, generating real-world evidence that clinicians and health systems can act on.

Additional Positions:

  1. Lead

    2024 – Current · AI Collaboration Hub, Intelligent Critical Care Center (IC3)

  2. Core Member

    2023 – Current · AI Task Force, UF College of Pharmacy

  3. Adjunct Assistant Professor

    2021 – Current · Johns Hopkins University

  4. Co-Founder

    2018 – 2021 · Johns Hopkins Center for Clinical NLP (C2NLP)

  5. Faculty Instructor

    2017 – 2021 · Biomedical Informatics and Data Science, Johns Hopkins Medicine

  6. NLP Lead

    2017 – 2021 · Institute for Clinical and Translational Research, Johns Hopkins Medicine

  7. NLP Specialist

    2017 – 2021 · Center for Language and Speech Processing (CLSP), Johns Hopkins School of Engineering

Related Links:
Google Scholar

Teaching Profile

Courses Taught

Teaching Philosophy

Dr. Rouhizadeh teaches at the intersection of AI and healthcare, drawing on interdisciplinary training in computer science and biomedical informatics. He has developed and coordinated graduate courses in biomedical informatics and natural language processing for the health sciences and has led AI training for clinical faculty and staff. His teaching centers on hands-on experience with applied AI, preparing students for an increasingly data-driven healthcare landscape, an approach recognized with a nomination for the College of Pharmacy’s 2024 Teaching Team Award. At the University of Florida, he is helping define how the next generation of pharmacists and researchers learns to work with AI. He leads the reactivation of the College of Pharmacy’s AI Taskforce and is developing an AI integration roadmap for the PharmD curriculum, a college-wide AI certificate program, and a new graduate course on practical AI methods for pharmacy research, while also contributing to UF’s MS program in AI in Biomedical and Health Sciences. Beyond the classroom, he is a committed mentor, having guided graduate students, staff, clinicians, and faculty into leading roles across industry, academia, and government.

Research Profile

Dr. Rouhizadeh builds artificial intelligence for one of healthcare’s hardest problems: the richest information about patients is often locked in unstructured text, the clinical notes and narratives that conventional data systems cannot read. Using natural language processing (NLP), large language models (LLMs), and deep learning, he turns that text into evidence clinicians and health systems can act on.

His signature approach, which he calls Retrieve → Reason → Phenotype, lets AI work through millions of records efficiently: it finds the small slice of text that matters, reasons over it with an LLM, and turns the result into computable phenotypes, structured profiles of a patient or population. A document-level take on retrieval-augmented generation (RAG), it makes population-scale analysis practical without overlooking the rare cases that often matter most.

He has applied these methods across a wide range of health problems, from substance use and cardiovascular risk to social and behavioral determinants of health and mental health conditions such as depression, anxiety, and suicidal behavior. As a Segment PI for the 1Florida Alzheimer’s Disease Research Center, he develops models that detect subtle cognitive and linguistic change years before a formal diagnosis, and his statewide mental health surveillance system analyzes data for more than five million Floridians to help public health agencies see where needs are emerging.

Underlying all of this is production-grade, HIPAA-compliant infrastructure that processes tens of thousands of clinical notes a day across Johns Hopkins and UF Health and supports secure collaboration through national research networks such as N3C and PCORnet. Across every project, Dr. Rouhizadeh prioritizes explainable, interpretable AI, so that what his models conclude stays transparent to clinicians and ready to use in real decisions.

Areas of Interest

  • AI-driven extraction and analysis of mental health outcomes, including suicidal behavior, anxiety, and depression.
  • Analyzing substance use patterns and their impact on vulnerable populations.
  • Developing AI tools for early risk assessment in Alzheimer’s Disease and Related Disorders (ADRD).
  • Investigating linguistic markers for early detection of neurological conditions.
  • Large Language Models (LLms) and Natural Language Processing (NLP)
  • Studying population health, focusing on social and behavioral determinants of health.

Publications

Academic Articles

Presentations

Grants

  1. Assessing Barriers and Facilitators for Participating Structured Lifestyle Intervention

    Active

    Role:
    Co-Investigator
    Funding:
    EMORY UNIV via CTRS FOR DISEASE CONTROL AND PREVENTION

  2. 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

  3. 1Florida Alzheimer’s Disease Research Center

    Active

    Role:
    Project Manager
    Funding:
    NATL INST OF HLTH NIA

Education

  1. Postdoctoral Training in Biomedical Informatics and Data Science

    University of Pennsylvania

  2. Ph.D. in Computer Science and Engineering

    Oregon Health and Science University

  3. M.Sc. in Computer Science and Engineering

    Oregon Health and Science University

  4. Professional Master’s in Human Language Technology and Interfaces

    University of Trento

  5. M.A. in Linguistics

    Allameh Tabatabai University

Contact Details

Phones:
Business:
(352) 273-9397
Emails:
Business:
mrouhizadeh@ufl.edu
Addresses:
Business Mailing:
PO Box 100496
 GAINESVILLE FL 32610
Business Street:
1889 Museum Rd.
Room 6012
Malachowsky Hall for Data Science and IT
 Gainesville FL 32611