August 6–7, 2026
August 6–7, 2026
hosted at FLAME University, Pune, India
hosted at FLAME University, Pune, India
hosted at FLAME University, Pune, India
Artificial Intelligence for Monitoring Malnutrition (AIMM) is developing and validating an AI-powered smartphone application that uses photographs to support accurate, accessible, and scalable child nutrition screening in rural and resource-constrained settings. Funded by the Swiss National Science Foundation and Innosuisse BRIDGE Discovery programme, the four-year project has completed development of its initial pipeline and preliminary field testing and is preparing to collect standardized images and reference measurements from approximately 6,000 children across Maharashtra. These data will support model refinement, independent evaluation, subgroup performance assessment, and subsequent household and institutional testing.
Artificial Intelligence for Monitoring Malnutrition (AIMM) is developing and validating an AI-powered smartphone application that uses photographs to support accurate, accessible, and scalable child nutrition screening in rural and resource-constrained settings. Funded by the Swiss National Science Foundation and Innosuisse BRIDGE Discovery programme, the four-year project has completed development of its initial pipeline and preliminary field testing and is preparing to collect standardized images and reference measurements from approximately 6,000 children across Maharashtra. These data will support model refinement, independent evaluation, subgroup performance assessment, and subsequent household and institutional testing.
The 2026 Technical Advisory Group (TAG) online meeting brings together experts in AI, nutrition, public health, humanitarian response, implementation, and institutional uptake to critically review the project’s technical, methodological, ethical, and operational decisions. This website contains all meeting materials, including agendas, guiding questions, background documents, and access links. Kindly register for the webinar sessions by 31 July 2026 and review the background information in advance.
The 2026 Technical Advisory Group (TAG) online meeting brings together experts in AI, nutrition, public health, humanitarian response, implementation, and institutional uptake to critically review the project’s technical, methodological, ethical, and operational decisions. This website contains all meeting materials, including agendas, guiding questions, background documents, and access links. Kindly register for the webinar sessions by 31 July 2026 and review the background information in advance.
About AIMM
About AIMM
Register
Register
Tell us your questions and suggestions:
Tell us your questions and suggestions:
Webinar Sessions
Webinar Sessions
FAQ
What problem does AIMM address?
AIMM addresses the need for faster, lower-cost, and more accurate child nutrition screening, particularly in hard-to-reach, crisis-affected, or otherwise resource-constrained settings. Current nutrition assessments often require trained personnel, physical measurement tools, and repeated field visits, which can limit coverage during emergencies, displacement, or pandemic-related restrictions. AIMM explores whether smartphone-based images can help estimate key indicators of child undernutrition and support low-cost, near-real-time identification of children at risk.
In which contexts is AIMM most useful?
AIMM is designed for settings where reliable nutrition data are urgently needed but difficult to collect. This includes conflict-affected areas, remote communities, humanitarian emergencies, public health crises, and other situations where access to children and households is limited. By enabling smartphone-based, community-level monitoring, AIMM can help generate timely information when standard measurement systems are disrupted, overstretched, or unavailable.
Who is AIMM designed for?
The app is being developed so that caregivers and families can monitor child nutrition using a standard smartphone, with minimal equipment and guidance. Drawing on prior experience with emoji-based questionnaires and culturally appropriate interface designs in Kenya, AIMM will place strong emphasis on intuitive, low-literacy, and locally appropriate user interaction. The app interface will be refined together with rural households and caregivers to ensure that it is easy to understand and use in everyday settings.
Where is AIMM developed and tested?
AIMM is being developed and tested in Maharashtra, India. In the first phase, the study will sample approximately 7,000 children across five districts — Dhule, Chandrapur, Nagpur, Jalgaon, and Beed — to train and validate the app. In a second phase, AIMM will be tested in Pune district with 150 households over a period of 12 months.
When will the beta version of AIMM be launched?
We will launch a beta version of AIMM for pilot testing by 2028. This beta version will be developed and refined through field validation in Maharashtra, India, using smartphone-based image capture, anthropometric measurements, and user feedback from households and frontline implementation settings. The first beta will be intended for research and pilot use, not yet for routine clinical or diagnostic deployment.
What is your licensing strategy?
Our licensing strategy is to keep AIMM accessible for public-interest use, especially by researchers, public health institutions, and implementation partners working on child nutrition. The exact licensing model will be finalized after validation and IP review. Our current approach is to: enable non-commercial research and public health use under clear access conditions; protect sensitive components such as child image data, trained models, and validation datasets; allow controlled collaboration with academic, government, and implementation partners; prevent misuse, unvalidated clinical deployment, or commercial use without permission; support future scale-up in India and other low-resource settings through responsible licensing agreements. AIMM is being developed as a research-based digital public health tool. Any licensing decision will prioritize ethical use, data protection, scientific transparency, and broad public health benefit.
Do you develop in-house?
Yes. AIMM is developed in-house by the project team, with technical and research support from partner institutions. The AI model, app design, validation strategy, and research workflow are led by the AIMM team at the Geneva Graduate Institute, in collaboration with FLAME University and technical partners in India. We also work with field teams and users during pilot testing to refine the app for real-world use. This allows us to keep close control over the scientific methods, data protection standards, and public health objectives of the tool.
FAQ
What problem does AIMM address?
AIMM addresses the need for faster, lower-cost, and more accurate child nutrition screening, particularly in hard-to-reach, crisis-affected, or otherwise resource-constrained settings. Current nutrition assessments often require trained personnel, physical measurement tools, and repeated field visits, which can limit coverage during emergencies, displacement, or pandemic-related restrictions. AIMM explores whether smartphone-based images can help estimate key indicators of child undernutrition and support low-cost, near-real-time identification of children at risk.
In which contexts is AIMM most useful?
AIMM is designed for settings where reliable nutrition data are urgently needed but difficult to collect. This includes conflict-affected areas, remote communities, humanitarian emergencies, public health crises, and other situations where access to children and households is limited. By enabling smartphone-based, community-level monitoring, AIMM can help generate timely information when standard measurement systems are disrupted, overstretched, or unavailable.
Who is AIMM designed for?
The app is being developed so that caregivers and families can monitor child nutrition using a standard smartphone, with minimal equipment and guidance. Drawing on prior experience with emoji-based questionnaires and culturally appropriate interface designs in Kenya, AIMM will place strong emphasis on intuitive, low-literacy, and locally appropriate user interaction. The app interface will be refined together with rural households and caregivers to ensure that it is easy to understand and use in everyday settings.
Where is AIMM developed and tested?
AIMM is being developed and tested in Maharashtra, India. In the first phase, the study will sample approximately 7,000 children across five districts — Dhule, Chandrapur, Nagpur, Jalgaon, and Beed — to train and validate the app. In a second phase, AIMM will be tested in Pune district with 150 households over a period of 12 months.
When will the beta version of AIMM be launched?
We will launch a beta version of AIMM for pilot testing by 2028. This beta version will be developed and refined through field validation in Maharashtra, India, using smartphone-based image capture, anthropometric measurements, and user feedback from households and frontline implementation settings. The first beta will be intended for research and pilot use, not yet for routine clinical or diagnostic deployment.
What is your licensing strategy?
Our licensing strategy is to keep AIMM accessible for public-interest use, especially by researchers, public health institutions, and implementation partners working on child nutrition. The exact licensing model will be finalized after validation and IP review. Our current approach is to: enable non-commercial research and public health use under clear access conditions; protect sensitive components such as child image data, trained models, and validation datasets; allow controlled collaboration with academic, government, and implementation partners; prevent misuse, unvalidated clinical deployment, or commercial use without permission; support future scale-up in India and other low-resource settings through responsible licensing agreements. AIMM is being developed as a research-based digital public health tool. Any licensing decision will prioritize ethical use, data protection, scientific transparency, and broad public health benefit.
Do you develop in-house?
Yes. AIMM is developed in-house by the project team, with technical and research support from partner institutions. The AI model, app design, validation strategy, and research workflow are led by the AIMM team at the Geneva Graduate Institute, in collaboration with FLAME University and technical partners in India. We also work with field teams and users during pilot testing to refine the app for real-world use. This allows us to keep close control over the scientific methods, data protection standards, and public health objectives of the tool.
FAQ
What problem does AIMM address?
AIMM addresses the need for faster, lower-cost, and more accurate child nutrition screening, particularly in hard-to-reach, crisis-affected, or otherwise resource-constrained settings. Current nutrition assessments often require trained personnel, physical measurement tools, and repeated field visits, which can limit coverage during emergencies, displacement, or pandemic-related restrictions. AIMM explores whether smartphone-based images can help estimate key indicators of child undernutrition and support low-cost, near-real-time identification of children at risk.
In which contexts is AIMM most useful?
AIMM is designed for settings where reliable nutrition data are urgently needed but difficult to collect. This includes conflict-affected areas, remote communities, humanitarian emergencies, public health crises, and other situations where access to children and households is limited. By enabling smartphone-based, community-level monitoring, AIMM can help generate timely information when standard measurement systems are disrupted, overstretched, or unavailable.
Who is AIMM designed for?
The app is being developed so that caregivers and families can monitor child nutrition using a standard smartphone, with minimal equipment and guidance. Drawing on prior experience with emoji-based questionnaires and culturally appropriate interface designs in Kenya, AIMM will place strong emphasis on intuitive, low-literacy, and locally appropriate user interaction. The app interface will be refined together with rural households and caregivers to ensure that it is easy to understand and use in everyday settings.
Where is AIMM developed and tested?
AIMM is being developed and tested in Maharashtra, India. In the first phase, the study will sample approximately 7,000 children across five districts — Dhule, Chandrapur, Nagpur, Jalgaon, and Beed — to train and validate the app. In a second phase, AIMM will be tested in Pune district with 150 households over a period of 12 months.
When will the beta version of AIMM be launched?
We will launch a beta version of AIMM for pilot testing by 2028. This beta version will be developed and refined through field validation in Maharashtra, India, using smartphone-based image capture, anthropometric measurements, and user feedback from households and frontline implementation settings. The first beta will be intended for research and pilot use, not yet for routine clinical or diagnostic deployment.
What is your licensing strategy?
Our licensing strategy is to keep AIMM accessible for public-interest use, especially by researchers, public health institutions, and implementation partners working on child nutrition. The exact licensing model will be finalized after validation and IP review. Our current approach is to: enable non-commercial research and public health use under clear access conditions; protect sensitive components such as child image data, trained models, and validation datasets; allow controlled collaboration with academic, government, and implementation partners; prevent misuse, unvalidated clinical deployment, or commercial use without permission; support future scale-up in India and other low-resource settings through responsible licensing agreements. AIMM is being developed as a research-based digital public health tool. Any licensing decision will prioritize ethical use, data protection, scientific transparency, and broad public health benefit.
Do you develop in-house?
Yes. AIMM is developed in-house by the project team, with technical and research support from partner institutions. The AI model, app design, validation strategy, and research workflow are led by the AIMM team at the Geneva Graduate Institute, in collaboration with FLAME University and technical partners in India. We also work with field teams and users during pilot testing to refine the app for real-world use. This allows us to keep close control over the scientific methods, data protection standards, and public health objectives of the tool.
Contact us
Get in touch with any questions.
Nina Link
Contact us
Get in touch with any questions.
Nina Link
Contact us
Get in touch with any questions.
Nina Link
August 6–7, 2026
August 6–7, 2026
hosted at FLAME University, Pune, India
hosted at FLAME University, Pune, India
hosted at FLAME University, Pune, India
Artificial Intelligence for Monitoring Malnutrition (AIMM) is developing and validating an AI-powered smartphone application that uses photographs to support accurate, accessible, and scalable child nutrition screening in rural and resource-constrained settings. Funded by the Swiss National Science Foundation and Innosuisse BRIDGE Discovery programme, the four-year project has completed development of its initial pipeline and preliminary field testing and is preparing to collect standardized images and reference measurements from approximately 6,000 children across Maharashtra. These data will support model refinement, independent evaluation, subgroup performance assessment, and subsequent household and institutional testing.
Artificial Intelligence for Monitoring Malnutrition (AIMM) is developing and validating an AI-powered smartphone application that uses photographs to support accurate, accessible, and scalable child nutrition screening in rural and resource-constrained settings. Funded by the Swiss National Science Foundation and Innosuisse BRIDGE Discovery programme, the four-year project has completed development of its initial pipeline and preliminary field testing and is preparing to collect standardized images and reference measurements from approximately 6,000 children across Maharashtra. These data will support model refinement, independent evaluation, subgroup performance assessment, and subsequent household and institutional testing.
The 2026 Technical Advisory Group (TAG) online meeting brings together experts in AI, nutrition, public health, humanitarian response, implementation, and institutional uptake to critically review the project’s technical, methodological, ethical, and operational decisions. This website contains all meeting materials, including agendas, guiding questions, background documents, and access links. Kindly register for the webinar sessions by 31 July 2026 and review the background information in advance.
The 2026 Technical Advisory Group (TAG) online meeting brings together experts in AI, nutrition, public health, humanitarian response, implementation, and institutional uptake to critically review the project’s technical, methodological, ethical, and operational decisions. This website contains all meeting materials, including agendas, guiding questions, background documents, and access links. Kindly register for the webinar sessions by 31 July 2026 and review the background information in advance.
About AIMM
About AIMM
Register
Register
Tell us your questions and suggestions:
Tell us your questions and suggestions:
Webinar Sessions
Webinar Sessions
FAQ
What problem does AIMM address?
AIMM addresses the need for faster, lower-cost, and more accurate child nutrition screening, particularly in hard-to-reach, crisis-affected, or otherwise resource-constrained settings. Current nutrition assessments often require trained personnel, physical measurement tools, and repeated field visits, which can limit coverage during emergencies, displacement, or pandemic-related restrictions. AIMM explores whether smartphone-based images can help estimate key indicators of child undernutrition and support low-cost, near-real-time identification of children at risk.
In which contexts is AIMM most useful?
AIMM is designed for settings where reliable nutrition data are urgently needed but difficult to collect. This includes conflict-affected areas, remote communities, humanitarian emergencies, public health crises, and other situations where access to children and households is limited. By enabling smartphone-based, community-level monitoring, AIMM can help generate timely information when standard measurement systems are disrupted, overstretched, or unavailable.
Who is AIMM designed for?
The app is being developed so that caregivers and families can monitor child nutrition using a standard smartphone, with minimal equipment and guidance. Drawing on prior experience with emoji-based questionnaires and culturally appropriate interface designs in Kenya, AIMM will place strong emphasis on intuitive, low-literacy, and locally appropriate user interaction. The app interface will be refined together with rural households and caregivers to ensure that it is easy to understand and use in everyday settings.
Where is AIMM developed and tested?
AIMM is being developed and tested in Maharashtra, India. In the first phase, the study will sample approximately 7,000 children across five districts — Dhule, Chandrapur, Nagpur, Jalgaon, and Beed — to train and validate the app. In a second phase, AIMM will be tested in Pune district with 150 households over a period of 12 months.
When will the beta version of AIMM be launched?
We will launch a beta version of AIMM for pilot testing by 2028. This beta version will be developed and refined through field validation in Maharashtra, India, using smartphone-based image capture, anthropometric measurements, and user feedback from households and frontline implementation settings. The first beta will be intended for research and pilot use, not yet for routine clinical or diagnostic deployment.
What is your licensing strategy?
Our licensing strategy is to keep AIMM accessible for public-interest use, especially by researchers, public health institutions, and implementation partners working on child nutrition. The exact licensing model will be finalized after validation and IP review. Our current approach is to: enable non-commercial research and public health use under clear access conditions; protect sensitive components such as child image data, trained models, and validation datasets; allow controlled collaboration with academic, government, and implementation partners; prevent misuse, unvalidated clinical deployment, or commercial use without permission; support future scale-up in India and other low-resource settings through responsible licensing agreements. AIMM is being developed as a research-based digital public health tool. Any licensing decision will prioritize ethical use, data protection, scientific transparency, and broad public health benefit.
Do you develop in-house?
Yes. AIMM is developed in-house by the project team, with technical and research support from partner institutions. The AI model, app design, validation strategy, and research workflow are led by the AIMM team at the Geneva Graduate Institute, in collaboration with FLAME University and technical partners in India. We also work with field teams and users during pilot testing to refine the app for real-world use. This allows us to keep close control over the scientific methods, data protection standards, and public health objectives of the tool.
FAQ
What problem does AIMM address?
AIMM addresses the need for faster, lower-cost, and more accurate child nutrition screening, particularly in hard-to-reach, crisis-affected, or otherwise resource-constrained settings. Current nutrition assessments often require trained personnel, physical measurement tools, and repeated field visits, which can limit coverage during emergencies, displacement, or pandemic-related restrictions. AIMM explores whether smartphone-based images can help estimate key indicators of child undernutrition and support low-cost, near-real-time identification of children at risk.
In which contexts is AIMM most useful?
AIMM is designed for settings where reliable nutrition data are urgently needed but difficult to collect. This includes conflict-affected areas, remote communities, humanitarian emergencies, public health crises, and other situations where access to children and households is limited. By enabling smartphone-based, community-level monitoring, AIMM can help generate timely information when standard measurement systems are disrupted, overstretched, or unavailable.
Who is AIMM designed for?
The app is being developed so that caregivers and families can monitor child nutrition using a standard smartphone, with minimal equipment and guidance. Drawing on prior experience with emoji-based questionnaires and culturally appropriate interface designs in Kenya, AIMM will place strong emphasis on intuitive, low-literacy, and locally appropriate user interaction. The app interface will be refined together with rural households and caregivers to ensure that it is easy to understand and use in everyday settings.
Where is AIMM developed and tested?
AIMM is being developed and tested in Maharashtra, India. In the first phase, the study will sample approximately 7,000 children across five districts — Dhule, Chandrapur, Nagpur, Jalgaon, and Beed — to train and validate the app. In a second phase, AIMM will be tested in Pune district with 150 households over a period of 12 months.
When will the beta version of AIMM be launched?
We will launch a beta version of AIMM for pilot testing by 2028. This beta version will be developed and refined through field validation in Maharashtra, India, using smartphone-based image capture, anthropometric measurements, and user feedback from households and frontline implementation settings. The first beta will be intended for research and pilot use, not yet for routine clinical or diagnostic deployment.
What is your licensing strategy?
Our licensing strategy is to keep AIMM accessible for public-interest use, especially by researchers, public health institutions, and implementation partners working on child nutrition. The exact licensing model will be finalized after validation and IP review. Our current approach is to: enable non-commercial research and public health use under clear access conditions; protect sensitive components such as child image data, trained models, and validation datasets; allow controlled collaboration with academic, government, and implementation partners; prevent misuse, unvalidated clinical deployment, or commercial use without permission; support future scale-up in India and other low-resource settings through responsible licensing agreements. AIMM is being developed as a research-based digital public health tool. Any licensing decision will prioritize ethical use, data protection, scientific transparency, and broad public health benefit.
Do you develop in-house?
Yes. AIMM is developed in-house by the project team, with technical and research support from partner institutions. The AI model, app design, validation strategy, and research workflow are led by the AIMM team at the Geneva Graduate Institute, in collaboration with FLAME University and technical partners in India. We also work with field teams and users during pilot testing to refine the app for real-world use. This allows us to keep close control over the scientific methods, data protection standards, and public health objectives of the tool.
FAQ
What problem does AIMM address?
AIMM addresses the need for faster, lower-cost, and more accurate child nutrition screening, particularly in hard-to-reach, crisis-affected, or otherwise resource-constrained settings. Current nutrition assessments often require trained personnel, physical measurement tools, and repeated field visits, which can limit coverage during emergencies, displacement, or pandemic-related restrictions. AIMM explores whether smartphone-based images can help estimate key indicators of child undernutrition and support low-cost, near-real-time identification of children at risk.
In which contexts is AIMM most useful?
AIMM is designed for settings where reliable nutrition data are urgently needed but difficult to collect. This includes conflict-affected areas, remote communities, humanitarian emergencies, public health crises, and other situations where access to children and households is limited. By enabling smartphone-based, community-level monitoring, AIMM can help generate timely information when standard measurement systems are disrupted, overstretched, or unavailable.
Who is AIMM designed for?
The app is being developed so that caregivers and families can monitor child nutrition using a standard smartphone, with minimal equipment and guidance. Drawing on prior experience with emoji-based questionnaires and culturally appropriate interface designs in Kenya, AIMM will place strong emphasis on intuitive, low-literacy, and locally appropriate user interaction. The app interface will be refined together with rural households and caregivers to ensure that it is easy to understand and use in everyday settings.
Where is AIMM developed and tested?
AIMM is being developed and tested in Maharashtra, India. In the first phase, the study will sample approximately 7,000 children across five districts — Dhule, Chandrapur, Nagpur, Jalgaon, and Beed — to train and validate the app. In a second phase, AIMM will be tested in Pune district with 150 households over a period of 12 months.
When will the beta version of AIMM be launched?
We will launch a beta version of AIMM for pilot testing by 2028. This beta version will be developed and refined through field validation in Maharashtra, India, using smartphone-based image capture, anthropometric measurements, and user feedback from households and frontline implementation settings. The first beta will be intended for research and pilot use, not yet for routine clinical or diagnostic deployment.
What is your licensing strategy?
Our licensing strategy is to keep AIMM accessible for public-interest use, especially by researchers, public health institutions, and implementation partners working on child nutrition. The exact licensing model will be finalized after validation and IP review. Our current approach is to: enable non-commercial research and public health use under clear access conditions; protect sensitive components such as child image data, trained models, and validation datasets; allow controlled collaboration with academic, government, and implementation partners; prevent misuse, unvalidated clinical deployment, or commercial use without permission; support future scale-up in India and other low-resource settings through responsible licensing agreements. AIMM is being developed as a research-based digital public health tool. Any licensing decision will prioritize ethical use, data protection, scientific transparency, and broad public health benefit.
Do you develop in-house?
Yes. AIMM is developed in-house by the project team, with technical and research support from partner institutions. The AI model, app design, validation strategy, and research workflow are led by the AIMM team at the Geneva Graduate Institute, in collaboration with FLAME University and technical partners in India. We also work with field teams and users during pilot testing to refine the app for real-world use. This allows us to keep close control over the scientific methods, data protection standards, and public health objectives of the tool.
Contact us
Get in touch with any questions.
Nina Link
Contact us
Get in touch with any questions.
Nina Link
Contact us
Get in touch with any questions.
Nina Link
August 6–7, 2026
August 6–7, 2026
hosted at FLAME University, Pune, India
hosted at FLAME University, Pune, India
hosted at FLAME University, Pune, India
Artificial Intelligence for Monitoring Malnutrition (AIMM) is developing and validating an AI-powered smartphone application that uses photographs to support accurate, accessible, and scalable child nutrition screening in rural and resource-constrained settings. Funded by the Swiss National Science Foundation and Innosuisse BRIDGE Discovery programme, the four-year project has completed development of its initial pipeline and preliminary field testing and is preparing to collect standardized images and reference measurements from approximately 6,000 children across Maharashtra. These data will support model refinement, independent evaluation, subgroup performance assessment, and subsequent household and institutional testing.
Artificial Intelligence for Monitoring Malnutrition (AIMM) is developing and validating an AI-powered smartphone application that uses photographs to support accurate, accessible, and scalable child nutrition screening in rural and resource-constrained settings. Funded by the Swiss National Science Foundation and Innosuisse BRIDGE Discovery programme, the four-year project has completed development of its initial pipeline and preliminary field testing and is preparing to collect standardized images and reference measurements from approximately 6,000 children across Maharashtra. These data will support model refinement, independent evaluation, subgroup performance assessment, and subsequent household and institutional testing.
The 2026 Technical Advisory Group (TAG) online meeting brings together experts in AI, nutrition, public health, humanitarian response, implementation, and institutional uptake to critically review the project’s technical, methodological, ethical, and operational decisions. This website contains all meeting materials, including agendas, guiding questions, background documents, and access links. Kindly register for the webinar sessions by 31 July 2026 and review the background information in advance.
The 2026 Technical Advisory Group (TAG) online meeting brings together experts in AI, nutrition, public health, humanitarian response, implementation, and institutional uptake to critically review the project’s technical, methodological, ethical, and operational decisions. This website contains all meeting materials, including agendas, guiding questions, background documents, and access links. Kindly register for the webinar sessions by 31 July 2026 and review the background information in advance.
About AIMM
About AIMM
Register
Register
Tell us your questions and suggestions:
Tell us your questions and suggestions:
Webinar Sessions
Webinar Sessions
FAQ
What problem does AIMM address?
AIMM addresses the need for faster, lower-cost, and more accurate child nutrition screening, particularly in hard-to-reach, crisis-affected, or otherwise resource-constrained settings. Current nutrition assessments often require trained personnel, physical measurement tools, and repeated field visits, which can limit coverage during emergencies, displacement, or pandemic-related restrictions. AIMM explores whether smartphone-based images can help estimate key indicators of child undernutrition and support low-cost, near-real-time identification of children at risk.
In which contexts is AIMM most useful?
AIMM is designed for settings where reliable nutrition data are urgently needed but difficult to collect. This includes conflict-affected areas, remote communities, humanitarian emergencies, public health crises, and other situations where access to children and households is limited. By enabling smartphone-based, community-level monitoring, AIMM can help generate timely information when standard measurement systems are disrupted, overstretched, or unavailable.
Who is AIMM designed for?
The app is being developed so that caregivers and families can monitor child nutrition using a standard smartphone, with minimal equipment and guidance. Drawing on prior experience with emoji-based questionnaires and culturally appropriate interface designs in Kenya, AIMM will place strong emphasis on intuitive, low-literacy, and locally appropriate user interaction. The app interface will be refined together with rural households and caregivers to ensure that it is easy to understand and use in everyday settings.
Where is AIMM developed and tested?
AIMM is being developed and tested in Maharashtra, India. In the first phase, the study will sample approximately 7,000 children across five districts — Dhule, Chandrapur, Nagpur, Jalgaon, and Beed — to train and validate the app. In a second phase, AIMM will be tested in Pune district with 150 households over a period of 12 months.
When will the beta version of AIMM be launched?
We will launch a beta version of AIMM for pilot testing by 2028. This beta version will be developed and refined through field validation in Maharashtra, India, using smartphone-based image capture, anthropometric measurements, and user feedback from households and frontline implementation settings. The first beta will be intended for research and pilot use, not yet for routine clinical or diagnostic deployment.
What is your licensing strategy?
Our licensing strategy is to keep AIMM accessible for public-interest use, especially by researchers, public health institutions, and implementation partners working on child nutrition. The exact licensing model will be finalized after validation and IP review. Our current approach is to: enable non-commercial research and public health use under clear access conditions; protect sensitive components such as child image data, trained models, and validation datasets; allow controlled collaboration with academic, government, and implementation partners; prevent misuse, unvalidated clinical deployment, or commercial use without permission; support future scale-up in India and other low-resource settings through responsible licensing agreements. AIMM is being developed as a research-based digital public health tool. Any licensing decision will prioritize ethical use, data protection, scientific transparency, and broad public health benefit.
Do you develop in-house?
Yes. AIMM is developed in-house by the project team, with technical and research support from partner institutions. The AI model, app design, validation strategy, and research workflow are led by the AIMM team at the Geneva Graduate Institute, in collaboration with FLAME University and technical partners in India. We also work with field teams and users during pilot testing to refine the app for real-world use. This allows us to keep close control over the scientific methods, data protection standards, and public health objectives of the tool.
FAQ
What problem does AIMM address?
AIMM addresses the need for faster, lower-cost, and more accurate child nutrition screening, particularly in hard-to-reach, crisis-affected, or otherwise resource-constrained settings. Current nutrition assessments often require trained personnel, physical measurement tools, and repeated field visits, which can limit coverage during emergencies, displacement, or pandemic-related restrictions. AIMM explores whether smartphone-based images can help estimate key indicators of child undernutrition and support low-cost, near-real-time identification of children at risk.
In which contexts is AIMM most useful?
AIMM is designed for settings where reliable nutrition data are urgently needed but difficult to collect. This includes conflict-affected areas, remote communities, humanitarian emergencies, public health crises, and other situations where access to children and households is limited. By enabling smartphone-based, community-level monitoring, AIMM can help generate timely information when standard measurement systems are disrupted, overstretched, or unavailable.
Who is AIMM designed for?
The app is being developed so that caregivers and families can monitor child nutrition using a standard smartphone, with minimal equipment and guidance. Drawing on prior experience with emoji-based questionnaires and culturally appropriate interface designs in Kenya, AIMM will place strong emphasis on intuitive, low-literacy, and locally appropriate user interaction. The app interface will be refined together with rural households and caregivers to ensure that it is easy to understand and use in everyday settings.
Where is AIMM developed and tested?
AIMM is being developed and tested in Maharashtra, India. In the first phase, the study will sample approximately 7,000 children across five districts — Dhule, Chandrapur, Nagpur, Jalgaon, and Beed — to train and validate the app. In a second phase, AIMM will be tested in Pune district with 150 households over a period of 12 months.
When will the beta version of AIMM be launched?
We will launch a beta version of AIMM for pilot testing by 2028. This beta version will be developed and refined through field validation in Maharashtra, India, using smartphone-based image capture, anthropometric measurements, and user feedback from households and frontline implementation settings. The first beta will be intended for research and pilot use, not yet for routine clinical or diagnostic deployment.
What is your licensing strategy?
Our licensing strategy is to keep AIMM accessible for public-interest use, especially by researchers, public health institutions, and implementation partners working on child nutrition. The exact licensing model will be finalized after validation and IP review. Our current approach is to: enable non-commercial research and public health use under clear access conditions; protect sensitive components such as child image data, trained models, and validation datasets; allow controlled collaboration with academic, government, and implementation partners; prevent misuse, unvalidated clinical deployment, or commercial use without permission; support future scale-up in India and other low-resource settings through responsible licensing agreements. AIMM is being developed as a research-based digital public health tool. Any licensing decision will prioritize ethical use, data protection, scientific transparency, and broad public health benefit.
Do you develop in-house?
Yes. AIMM is developed in-house by the project team, with technical and research support from partner institutions. The AI model, app design, validation strategy, and research workflow are led by the AIMM team at the Geneva Graduate Institute, in collaboration with FLAME University and technical partners in India. We also work with field teams and users during pilot testing to refine the app for real-world use. This allows us to keep close control over the scientific methods, data protection standards, and public health objectives of the tool.
FAQ
What problem does AIMM address?
AIMM addresses the need for faster, lower-cost, and more accurate child nutrition screening, particularly in hard-to-reach, crisis-affected, or otherwise resource-constrained settings. Current nutrition assessments often require trained personnel, physical measurement tools, and repeated field visits, which can limit coverage during emergencies, displacement, or pandemic-related restrictions. AIMM explores whether smartphone-based images can help estimate key indicators of child undernutrition and support low-cost, near-real-time identification of children at risk.
In which contexts is AIMM most useful?
AIMM is designed for settings where reliable nutrition data are urgently needed but difficult to collect. This includes conflict-affected areas, remote communities, humanitarian emergencies, public health crises, and other situations where access to children and households is limited. By enabling smartphone-based, community-level monitoring, AIMM can help generate timely information when standard measurement systems are disrupted, overstretched, or unavailable.
Who is AIMM designed for?
The app is being developed so that caregivers and families can monitor child nutrition using a standard smartphone, with minimal equipment and guidance. Drawing on prior experience with emoji-based questionnaires and culturally appropriate interface designs in Kenya, AIMM will place strong emphasis on intuitive, low-literacy, and locally appropriate user interaction. The app interface will be refined together with rural households and caregivers to ensure that it is easy to understand and use in everyday settings.
Where is AIMM developed and tested?
AIMM is being developed and tested in Maharashtra, India. In the first phase, the study will sample approximately 7,000 children across five districts — Dhule, Chandrapur, Nagpur, Jalgaon, and Beed — to train and validate the app. In a second phase, AIMM will be tested in Pune district with 150 households over a period of 12 months.
When will the beta version of AIMM be launched?
We will launch a beta version of AIMM for pilot testing by 2028. This beta version will be developed and refined through field validation in Maharashtra, India, using smartphone-based image capture, anthropometric measurements, and user feedback from households and frontline implementation settings. The first beta will be intended for research and pilot use, not yet for routine clinical or diagnostic deployment.
What is your licensing strategy?
Our licensing strategy is to keep AIMM accessible for public-interest use, especially by researchers, public health institutions, and implementation partners working on child nutrition. The exact licensing model will be finalized after validation and IP review. Our current approach is to: enable non-commercial research and public health use under clear access conditions; protect sensitive components such as child image data, trained models, and validation datasets; allow controlled collaboration with academic, government, and implementation partners; prevent misuse, unvalidated clinical deployment, or commercial use without permission; support future scale-up in India and other low-resource settings through responsible licensing agreements. AIMM is being developed as a research-based digital public health tool. Any licensing decision will prioritize ethical use, data protection, scientific transparency, and broad public health benefit.
Do you develop in-house?
Yes. AIMM is developed in-house by the project team, with technical and research support from partner institutions. The AI model, app design, validation strategy, and research workflow are led by the AIMM team at the Geneva Graduate Institute, in collaboration with FLAME University and technical partners in India. We also work with field teams and users during pilot testing to refine the app for real-world use. This allows us to keep close control over the scientific methods, data protection standards, and public health objectives of the tool.
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Contact us
Get in touch with any questions.
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