Research Groups
NAAMII's autonomous research groups drive cutting-edge innovation across diverse domains of AI
and its applications
TOGAI (Transforming Global Health with AI)
TOGAI builds intelligent health technologies for low-resource settings. In a world where over 4.5 billion people lack access to essential healthcare, TOGAI tackles critical gaps in diagnostics, specialist access, and information equity to harness the transformative potential of AI to improve people’s lives. Through AI-powered task-shifting systems, low-cost diagnostic tools, and accessible health information, TOGAI transforms healthcare delivery in the Global South, making quality care more affordable and widely available.
BBMMLL (B Bhattarai Multi-Modal Learning Lab)
The B Bhattarai MultiModal Learning Lab is at the forefront of developing robust and interpretable machine learning algorithms. Our mission is to pioneer algorithms that can reason across complex, heterogeneous data to address some of the most critical challenges in healthcare, energy, and global agriculture. We are dedicated to building a global research pipeline that fosters talent and innovation guided by the philosophy: to build AI that is not only powerful but also trustworthy and explainable.
MAPMED (Multimodal Medical Data Analysis for Precision Medicine Lab)
MAPMED focuses on multimodal medical data analysis for decision support systems in radiomics and precision medicine. We specialize in analyzing multimodal medical imaging data, including PET, CT, MRI, and microscopic tissue (histopathology) images and develop deep learning models for tasks such as segmentation, detection prognostication, prediction, and classification.
PUSHVIC (Providential Use of Spatial and Human Visual Computing)
PUSHVIC is at the forefront of research in Augmented Reality (AR), Robotics, and Computer Vision. We explore spatial computing and human visual perception to bridge the fundamental research to real-world deployment. Our work advances AR, robotics, and vision-based systems to enhance human interaction, perception, and decision-making. Through interdisciplinary research and industry collaboration, we develop technologies that expand the frontiers of visual and spatial computing.
CGL (Computational Genomics Lab)
CGL applies bioinformatics and machine learning to tackle pressing challenges in disease biology. Our research focuses on understanding the genomics of communicable and non-communicable diseases, with a particular emphasis on treatment resistance and disease progression. By developing efficient computational methods, we aim to transform global health, with a focus on diseases prevalent in low- and middle-income countries like Nepal.
Agri AI (A²) Innovation Lab (AI for Conscious Living and Sustainable Agriculture)
A² Innovation Lab integrates cutting-edge technology with traditional farming wisdom to develop resilient, sustainable agricultural systems. Our mission centers on three foundational pillars: Climate-Smart Agriculture: Leveraging AI, IoT, and satellite technologies to optimize resource management, predict climate risks, and enhance crop resilience. Regenerative Agriculture: Using AI-driven analytics to promote soil health, biodiversity, and long-term farm sustainability. Permaculture & Traditional Knowledge Integration: Preserving ancestral farming practices while enriching AI models with culturally appropriate insights. Our approach creates practical, scalable technologies that empower farmers, researchers, and communities to protect crops, enhance productivity, and maintain ecological balance.
CESP (Computational Endoscopy, Surgery & Pathology)
Research at CESP focuses on integrating computational techniques into medical practices to enhance the accuracy and effectiveness of endoscopic computer vision, surgical data science, and computational pathology. Our goal is to improve healthcare outcomes by conducting high throughput imaging and medical image analyses for better diagnostic and surgical interventions.
RAIN (Research using Artificial Intelligence in Neuroscience)
The RAIN lab explores the intersection of AI and neuroscience, with emphasis on different neurological conditions and disorders.
AI & Society (Governance Lab)
The AI and Society group is committed to ensuring the responsible and ethical integration of AI into society. We develop tools and methods to enhance the public’s understanding of AI and promote discussions about its impact on human life and social structures. Our work aims to better understand the potential negative impacts of AI, such as bias and exclusion, fostering transparency of AI applications for the collective good.
TrAI (Translating Advances In Artificial Intelligence Into Health Services)
Our work translates the advances in artificial intelligence and digital health and the tools that it develops into health services, with a special focus on meeting the health needs of resource limited settings. We see the implementation of AI tools into health services as a sequential two step process:Translation Research: Transforming theoretical and scientific breakthroughs in AI and related disciplines into applied solutions and usable tools that can support, augment, audit, and strengthen health services.Implementation Science: Deploying, integrating, and rigorously evaluating AI-driven tools and technologies within clinical and public health environments to ensure safety, effectiveness, and scalability.We hope to create and evaluate health services, ancillary tools and technologies that can be deployed readily in clinical and public health settings.