Masoud Rouhizadeh, Ph.D., M.Sc., M.A.

Dr. Masoud Rouhizadeh holds an Assistant Professor position in the Department of Pharmaceutical Outcomes and Policy at the University of Florida. He plays key leadership roles in the University’s AI in the Health Sciences Initiative, serving as a core member of the College of Pharmacy’s AI Task Force and as the Lead for the AI Collaboration Hub at the Intelligent Critical Care Center. Dr. Rouhizadeh also holds an Adjunct Assistant Professor appointment in the Division of Biomedical Informatics and Data Science at the Johns Hopkins School of Medicine.

Dr. Rouhizadeh’s career has spanned several prestigious institutions. Prior to joining UF, he served on the faculty within Biomedical Informatics and Data Science and as the NLP Lead at the Institute for Clinical and Translational Research at Johns Hopkins University School of Medicine, where he also co-founded the Center for Clinical NLP (C2NLP). Before Johns Hopkins, he was a postdoctoral fellow at the Institute for Biomedical Informatics at the University of Pennsylvania. Dr. Rouhizadeh obtained his Master’s and Ph.D. degrees in Computer Science and Engineering from Oregon Health and Science University, and earlier in his career, he earned a Master’s degree in Human Language Technology from the University of Trento in Italy.

Supported by federal grants and contracts from agencies including the CDC, NIA, NIMHD, FDA, NIDA, and PCORI, Dr. Rouhizadeh’s research integrates cutting-edge artificial intelligence (AI)—particularly natural language processing (NLP) and large language models (LLMs)—to enhance health outcomes through real-world data analysis.

With extensive training in biomedical informatics, computer science, linguistics, and machine learning, combined with leadership experience, Dr. Rouhizadeh is uniquely positioned to lead innovative research in this field. As a faculty member in the University of Florida’s AI in Health Sciences initiative and a core member of the College of Pharmacy’s AI Task Force, he develops large-scale AI solutions for healthcare. This builds upon his experience at Johns Hopkins University, where he co-founded the Center for Clinical NLP and led NLP efforts at the Institute for Clinical and Translational Research, creating pioneering AI solutions with significant clinical impact.

Dr. Rouhizadeh’s research applies AI and LLMs to extract valuable insights from diverse healthcare data sources, including unstructured electronic health records, patient-reported outcomes, lab tests, and claims data. He focuses on extracting key details, developing computable phenotypes for individuals and populations, and creating precise, data-driven health condition profiles. These phenotypes support predictive modeling, risk assessment, personalized treatment planning, and population health management. A key emphasis of his research is explainability; he prioritizes interpretable AI methods to ensure that generated insights are transparent and clinically relevant, enhancing their utility in healthcare decision-making.

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• 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.