Soroush Dianaty

Soroush Dianaty

PhD Student, Biomedical Informatics & Data Science

Arizona State University

Biography & Clinical-to-Informatics Journey

Physician-scientist and PhD student, focused on the evaluation and real-world implementation of clinical AI systems. My research centers on trustworthy clinical LLMs, including hallucination detection, evidence grounding, contextual reliability, and AI safety in healthcare settings. I develop evaluation frameworks and computational methods to determine whether clinical AI systems are scientifically grounded, clinically reliable, and suitable for deployment in real-world practice.
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Education & Academic Background

PhD, Biomedical Informatics and Data Science

Aug 2025 – Present

Arizona State University

Doctor of Medicine (M.D.)

Sep 2016 – Jun 2024

Tehran Medical Sciences Branch, Islamic Azad University (IAUTMU)

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Research Focus Areas

Health Informatics Digital Health Clinical LLMs Trustworthy Clinical AI
From Bedside to Benchmarks

I trained and practiced as a Family Physician (M.D.)—treating over 7,500 patients across 17 rural and urban communities—before transitioning into computer science and biomedical informatics research.

During my clinical practice, I experienced firsthand how traditional clinical decision support tools fall short when handling real-world ambiguity, non-standardized EHR notes, and dynamic patient trajectories. As Large Language Models began entering healthcare discussions, it became clear that evaluation metrics borrowed from general NLP (like exam accuracy on multiple-choice questions) fail to capture the asymmetric risk of clinical hallucinations.

Now as a Biomedical Informatics PhD Researcher at Arizona State University, my work focuses on building the mathematical, computational, and standards-compliant frameworks necessary to evaluate generative clinical AI before it touches patient care.