Multi-disciplinary research


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: Terrence Lee St John (Cleveland Clinic Abu Dhabi), Bartlomiej Piechowski (Canberra Hospital), and Artie Shen (NYU CDS)

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)