SUMMARY
Moein Enayati, Ph.D., leads the development of advanced computational tools, infrastructure, and artificial intelligence (AI) and machine learning (ML) platforms to accelerate innovation in patient care and research. His work centers on translational research at the intersection of computational science and clinical practice.
Dr. Enayati's research focuses on ML and signal processing for noninvasive remote vital sign monitoring. Before joining Mayo Clinic, he spent seven years in industry, contributing to large-scale software engineering, algorithm optimization, and end-to-end solution architecture across both enterprise and startup environments. Dr. Enayati also has led and contributed to multiple externally funded research initiatives in collaboration with clinical and research groups at Mayo Clinic.
Focus areas
- Platform technologies. Dr. Enayati's work focuses on enterprise-scale infrastructure to support seamless remote care delivery, enabling secure integration of data from remote patient monitoring devices, third-party applications and partner platforms.
- Early disease diagnosis. Dr. Enayati advances AI- and ML-powered predictive analytics to identify disease risks earlier and improve diagnostic precision. He integrates multimodal clinical and sensor data for timely interventions.
- Noninvasive sensors. Dr. Enayati has extensive experience in the design and development of noninvasive health monitoring tools for cardio-respiratory function, daily activity tracking and fall risk assessment. His work enables clinicians to monitor patients remotely and support early interventions.
- Large language model-based patient safety analytics. In collaboration with Mayo Clinic's patient safety team, Dr. Enayati leverages advanced natural language processing and machine learning to develop and deploy large language models that identify, analyze and mitigate patient safety risks, supporting real-time root-cause analysis and improved care.
- AI- and machine learning-based phenotyping of rare genetic diseases. In collaboration with Mayo Clinic's Center for Individualized Medicine and Department of Clinical Genomics, Dr. Enayati integrates multimodal clinical data to improve early disease diagnosis and personalize patient care.
- Predictive models and decision-support systems for cardiovascular risk assessment. Together with Mayo's Department of Cardiovascular Medicine, Dr. Enayati uses advanced computational tools to enhance clinical decision-making for hypertrophic cardiomyopathy.
- Machine learning-driven analysis of diagnostic errors in emergency care. In collaboration with the Department of Emergency Medicine, Dr. Enayati applies advanced AI and data fusion techniques to identify, characterize and reduce diagnostic errors, supporting improved clinical decision-making and patient safety in the emergency department.
Significance to patient care
Dr. Enayati's work helps patients get care quickly and accurately. He builds remote care tools that let medical teams help patients outside the hospital — in their homes and communities. These tools safely share information from wearable devices and other health tools, keeping care teams updated. This helps patients get care sooner, stay connected and have better access to medical care no matter where they live or what resources they have.
Dr. Enayati also studies how to find diseases earlier using computer technology, such as AI. His research helps healthcare teams spot health risks early to treat patients sooner. By bringing together medical data and smart computer tools, Dr. Enayati's work helps cut diagnosis delays, personalize care for each patient, and improve health and safety.
Professional highlights
- Institute of Electrical and Electronics Engineers:
- Member, Future Directions Committee, Computational Intelligence Society, 2025-present.
- Associate editor, Engineering in Medicine and Biology Society, 2021-present.
- Technology director, Beyond Walls, Mayo Clinic Platform, Mayo Clinic, 2025-present.
- Editorial board, Frontiers in Bioengineering and Biotechnology, 2022-present.
- Editorial board, Frontiers in Physiology, 2022-present.
- University of Minnesota:
- Chair, Digital Health and Devices Track, Design of Medical Devices Conference, 2024-2025.
- Nominee, 3-in-5 Competition award, Design of Medical Devices Conference, 2020.
- Awardee, Translational Artificial Intelligence in Healthcare grant, Society to Improve Diagnosis in Medicine, 2021-2022.
- RoboCup 2002, The Robot World Cup Soccer Games and Conferences:
- Semifinalist, Simulated Soccer League, 2002.
- Member, National Team, Simulated Soccer League, 2002.