SUMMARY
Nasibeh Zanjirani Farahani, Ph.D., M.S., is a systems engineer and translational artificial intelligence (AI) researcher dedicated to advancing the integration of AI into clinical practice. She is a technical success manager with the Mayo Clinic Platform Accelerate program, where she focuses on developing, evaluating and implementing clinically integrated AI and machine learning (ML) solutions. As a certified Google Cloud digital leader and scrum master, Dr. Zanjirani Farahani bridges the gap between advanced AI technologies and clinical impact. Her work focuses on high-acuity domains such as cardiovascular and emergency medicine, where she designs decision support systems to improve diagnostic precision, streamline care delivery and enhance operational performance in complex healthcare settings.
Dr. Zanjirani Farahani's academic background in industrial engineering, operations research and systems optimization informs her unique approach to AI in healthcare. This approach is also grounded in data architecture, decision science and health systems engineering. Her technical expertise spans a wide range of methodologies, including generative AI, predictive modeling, natural language processing (NLP), simulation modeling and ethical AI governance.
Dr. Zanjirani Farahani plays a key role in shaping AI policies through her involvement with the Coalition for Health AI (CHAI) and Mayo Clinic Platform's Artificial Intelligence Steering Committee. She also strongly advocates for inclusive innovation, leading a Mayo Employee Resource Group while focusing on AI fairness and gender bias projects, mentoring women founders, and serving as a reviewer for top-tier AI and healthcare journals. Her work continues to shape the future of responsible, equitable and systems-driven AI in medicine.
Focus areas
- Artificial intelligence-driven clinical decision support systems. Dr. Zanjirani Farahani designs and deploys AI-powered tools to support real-time decision-making in clinical settings, focusing on cardiovascular and emergency medicine. Her work includes risk stratification models, ML-based ECG and echo tools for hypertrophic cardiomyopathy and AI-enabled diagnostics integrated into Mayo Clinic workflows.
- Generative AI and NLP. She leads strategic initiatives in generative AI adoption, including the development of NLP models for unstructured clinical data and internal governance frameworks. Her contributions include large language model evaluation, annotation strategies and AI guideline creation within the Mayo Clinic Platform Accelerate program.
- Ethical and trustworthy AI governance. Dr. Zanjirani Farahani shapes national and institutional policies on fairness, bias mitigation and responsible AI deployment. She has authored AI evaluation guardrails and advised on startup regulatory alignment.
- Systems engineering and healthcare optimization. She has roots in industrial engineering and operations research and applies systems thinking to complex healthcare challenges. Her work includes simulation modeling, discrete event analysis, supply chain and emergency department optimization, and predictive planning for trauma responsiveness, staffing and patient flow.
- Startup accelerate program and ecosystem evaluation. Dr. Zanjirani Farahani has evaluated over 650 AI and ML startup and solution developer proposals and mentored more than 50 early-stage companies. She has developed scalable frameworks for technical feasibility, clinical alignment, data integration and workflow adoption — advancing AI product-market fit across healthcare systems.
- Health equity, inclusion and women's health artificial intelligence. A champion of inclusive innovation, she leads gender-focused initiatives such as Femtech solution evaluation, bias mitigation in AI systems and advocacy for women in AI leadership. Her projects address equity in care delivery and representation in digital health research.
Significance to patient care
Dr. Zanjirani Farahani's research turns advanced AI technologies into tools that directly improve how healthcare professionals diagnose and treat patients. Her ML models help spot life-threatening heart conditions such as hypertrophic cardiomyopathy earlier, letting doctors treat patients sooner and more accurately.
In emergency rooms, Dr. Zanjirani Farahani's predictive tools and planning models have lessened patient wait times and improved how teams respond to trauma, making hospitals run more smoothly. She helps patients get the right care faster when every second counts.
Dr. Zanjirani Farahani also uses new types of AI, such as generative AI and NLP, to pull helpful insights from medical records into clinical workflows. She helps unlock insights from unstructured medical data, making diagnoses clearer and lessening paperwork for healthcare workers. She is committed to making sure that AI is used in a safe, fair and responsible way, putting trust and equity first for every patient.
Dr. Zanjirani Farahani leads efforts to make healthcare more equal. She works to reduce gender bias in AI, researching how social factors affect health and driving innovation in women's health. She aims to bring AI out of the lab and into real-world settings in hospitals and clinics, helping healthcare professionals make better decisions, closing health gaps and improving care for everyone.
Professional highlights
- Mayo Clinic:
- Member, Generative Artificial Intelligence Steering Committee, Mayo Clinic Platform, 2024-present.
- Co-investigator, Artificial Intelligence-Enabled Hypertrophic Cardiomyopathy Risk Stratification, Mayo Clinic Cardiovascular Grant, 2022-2024.
- Artificial Intelligence and Innovation Award, 2023.
- Member, Coalition for Health Artificial Intelligence, 2024-present.
- Mentor, National Institutes of Health Mentoring Fellowship, Harvard Medical School, 2024-present.
- Winner, University of Missouri Health Research and Creative Activities Forum Competition, 2018, 2019.
- Outstanding Doctoral Student Award, University of Missouri-Columbia, 2018.