Dr. Prasad's research focuses on improving outcomes for patients with osteoarthritis and lower-limb degenerative joint disease through a combination of biomechanics, gait analysis, and technology-enabled musculoskeletal care. He is particularly interested in understanding the mechanical and biological drivers of pain, function and disease progression in hip and knee osteoarthritis, with the aim of informing more personalized, mechanism-based interventions.

A key theme of his work is the integration of quantitative gait and biomechanical assessment with clinical, imaging, and biological data. He is interested in identifying how abnormal joint loading, impact, and movement patterns relate to pain generation, structural disease, and patient-reported outcomes, both before and after intervention. This includes work in pre-arthritic and early osteoarthritis populations, as well as patients undergoing joint-preserving or joint-replacement surgery.

He also has a strong interest in the role of tissue and fluid biomarkers in osteoarthritis, including synovial fluid and periprosthetic tissue analysis, and how these may correlate with biomechanical stress, inflammation, pain phenotypes and surgical outcomes. Access to a large, well-characterized clinical cohorts has enabled translational studies linking biomechanics, biomarkers and outcomes at scale.

Methodologically, Dr. Prasad's work spans prospective clinical studies, gait and wearable-based assessment, and collaboration with engineers and data scientists to develop scalable tools for objective outcome measurement. A longer-term goal is to support the development of technology-enabled care pathways that improve patient stratification, optimize timing and selection of interventions, and enhance recovery following surgery.

Dr. Prasad has an interest in collaboration across disciplines, particularly with investigators in rheumatology, biomechanics, bioengineering and population health, to address clinically meaningful questions in osteoarthritis and musculoskeletal disease.