Research

My primary research interests lie in applied AI and data science, particularly AI-powered descriptive and predictive models in healthcare. I am interested in advanced AI mechanisms to automatically and objectively analyze diverse range of health data (e.g., medical images, clinical notes, patient-provided information, and EHRs) to precisely tackle clinical prediction and description mainly focusing on musculoskeletal diseases and disorders. The interdisciplinary nature of my research has been helping me to foster further collaborations with physicians, orthopedic surgeons, informaticians, and also software engineers to implement computational methods for modeling real-world healthcare problems. My main technical and clinical interests are as follows:

• Technical: Explainable, Interpretable, and Accountable AI and Machine Learning
• Clinical: Musculoskeletal Diseases and Disorders

My current computational/technical research focus spans the following agendas:

• Multimodal Clinical Data Analysis
• Fused AI and Machine Learning Models
• Few-Shot Learning

Further information about my research agendas could be found via my research laboratory, the Pitt HexAI Research Laboratory!