Agenda
We are interested in developing machine learning methods and systems using heterogeneous real-world data for applications in health. This includes electronic health records data and medical imaging for medical diagnostics and prognostics. Methodologies of interest pertain to multi-modal fusion, representation learning, and augmenting machine and human decision-making, to achieve high performance and utility in clinical practice.
Our research agenda consists of two interrelated tracks:
Projects that we lead
Privacy-preserving Intra-City Collaborative Learning for Health Screening Applications
Grant period: 2022-2024
Sponsor: NYUAD Center for Interacting Urban Networks & Center for Cybersecurity
Collaborators: Michail Maniatakos (NYUAD Engineering) & Mariam Al Harbi (Abu Dhabi Health Services)
EyeScore: Leveraging Cross-modal Associations between Clinical Data and Optical Imaging for Stroke Recurrence Risk Prediction
Grant period: 2022-2024
Sponsor: NYUAD Research Enhancement Fund
Collaborators: Bartlomiej Piechowski (Cleveland Clinic Abu Dhabi) & Farokh Atashzar (NYU Tandon School of Engineering)
Abu Dhabi Precision Medicine Virtual Research Institute
Grant period: 2022-2026
Sponsor: ASPIRE
Collaborators: Coming soon!
Projects that we collaborate on
Tailoring Breast Cancer Diagnosis Workflow with Deep Neural Networks
Grant period: 2020-2022
Sponsor: Gordon and Betty Moore Foundation
Collaborators: Krzysztof Geras (NYU Grossman School of Medicine)
Deep Learning for Robotic Human Augmentation
Grant period: 2022-2027
Sponsor: NYUAD Center for Artificial Intelligence & Robotics
Collaborators: Farokh Atashzar (NYU Tandon School of Engineering) & Tuka Al Hanai (NYUAD Engineering)
Enhancing the Conservation of Coral Reefs through Vision-based Health Monitoring
Grant period: 2022-2027
Sponsor: NYUAD Arabian Center for Climate and Environmental Sciences
Collaborators: John Burt (NYUAD Biology), Shady Amin (NYUAD Biology), & Anthony Tzes (NYUAD Engineering)