Community
Working Groups
Small groups of researchers and engineers who own a specific area of MONAI: ultrasound, federated learning, ophthalmology, deploy, human-AI interaction. Each group meets regularly, ships code and publications, and reports to the Advisory Board.
Each working group is led by chairs who serve as members of the MONAI Advisory Board, which keeps each group aligned with MONAI's overall mission.
Navigate
Find Your Group
Jump directly to a working group or browse through all groups below to learn about their missions and leadership.
Our Teams
All Working Groups
From technical implementation to clinical applications, our working groups ensure that MONAI remains at the forefront of healthcare AI innovation.
Deploy Working Group
This working group aims to define how to close the existing gap from research and development to clinical production environments by bringing AI models into medical applications and clinical workflows with the end goal of helping improve patient care. The focus includes defining the open high-level functional architecture and determining which components and standard APIs are required. By collaborating with the MONAI developers, the group will move from requirements to implemented solutions.
Group Leads
Barbaros Selnur Erdal
Mayo Clinic
David Bericat
NVIDIA
Haris Shuaib
Guy's and St Thomas' NHS Foundation Trust
Developers Committee Working Group
This working group aims to establish and maintain technical excellence in MONAI Core by coordinating development efforts and ensuring high code quality standards. The focus includes overseeing architectural decisions, establishing development guidelines, and maintaining technical documentation with the end goal of creating a sustainable framework for medical imaging AI research and development. By fostering collaboration between contributors, the group ensures consistent implementation of best practices across the codebase.
Group Leads
Nic Ma
NVIDIA
Eric Kerfoot
King's College London
Yun Liu
NVIDIA
Education Working Group
This working group aims to accelerate the adoption of AI in medical imaging through comprehensive educational resources and training materials. The focus includes developing structured learning paths, hands-on tutorials, and practical exercises with the end goal of enabling researchers and clinicians to effectively utilize MONAI in their work. By creating accessible content for various skill levels, the group helps bridge the knowledge gap in medical imaging AI.
Group Leads
Eric Kerfoot
King's College London
Marc Modat
King's College London
Evaluation and Benchmarking Working Group
The Evaluation and Benchmarking MONAI working group aims at providing guidelines, infrastructure, and practical tools for evaluation and benchmarking of medical image analysis methods. It focuses on leading the community towards the identification and adoption of best practices for evaluation and benchmarking and on identifying practical solutions to improve reproducibility.
Group Leads
Annika Reinke
DKFZ
Carole Sudre
UCL
Data Quality and Federated Learning Working Group
This working group aims to advance collaborative medical AI research through secure and efficient federated learning implementations. The focus includes developing standardized workflows, ensuring data compatibility, and creating modular components with the end goal of enabling distributed learning across institutions while preserving data privacy. By establishing best practices for federated learning, the group facilitates multi-institutional collaboration in medical AI research.
Group Leads
Holger Roth
NVIDIA
Sai Praneeth Karimireddy
USC
Human-AI Interaction Working Group
This working group aims to advance, standardize, and support human-AI interaction cycles through well-defined interfaces and community-driven development. The focus includes developing standardized APIs for AI prompting, uncertainty communication, and annotation feedback processes with the end goal of creating reusable interactive AI workflows. By fostering community-driven specification and implementation across diverse domains including radiology, pathology, and surgery, the group enables efficient AI deployment across cloud, local, and HPC environments.
Group Leads
Dr. Ralf Floca
DKFZ
Dr. Saad Nadeem
Memorial Sloan Kettering Cancer Center
Bruce Hashemian
NVIDIA
Ophthalmology Working Group
This working group aims to advance the application of AI in ophthalmology through specialized tools and algorithms. The focus includes developing analysis methods for various ophthalmic imaging modalities, creating annotation tools, and building predictive models with the end goal of improving diagnosis and treatment of eye diseases. By leveraging MONAI's capabilities, the group accelerates innovation in ophthalmic image analysis.
Group Leads
Jayashree Kalpathy-Cramer
University of Colorado
Aaron Lee
University of Washington
Outreach and Adoption Working Group
This working group aims to expand MONAI's reach and impact across the medical imaging community. The focus includes organizing technical training, fostering community engagement, and developing infrastructure with the end goal of establishing MONAI as the leading open-source platform for medical imaging AI. By building an inclusive and transparent community, the group ensures sustainable growth and adoption of MONAI.
Group Leads
Michael Zephyr
NVIDIA
Ultrasound Working Group
This working group will focus on enabling reproducible, scalable AI development for ultrasound within the MONAI ecosystem. Key priorities include harmonizing data formats (e.g., DICOM for B-mode); supporting data streaming (e.g., for RF signals); standardizing annotation formats and labeling protocols for common ultrasound tasks; and defining reusable pipelines for training, inference, evaluation, and deployment. Short-term and long-term priorities and focal clinical applications will be determined by participants of the group. By collaborating with the MONAI developers, the group will move from requirements to implemented solutions.
Group Leads
Tina Kapur
Brigham and Women's Hospital, Harvard Medical School
Stephen Aylward
NVIDIA
Get Involved
Join a Working Group
Working group members collaborate regularly through meetings, workshops, and joint projects, fostering knowledge exchange and driving continuous improvement in their specialized areas. Get started by exploring the groups above or reaching out to the community.