About

I’m a 4th year PhD student in Mechanical Engineering at the University of Illinois Urbana-Champaign, where I conduct research in the Tissue Biomechanics Laboratory. My work has two complementary focuses: developing accessible measurement tools and applying them to evaluate exercise interventions for manual wheelchair users.

Research Focus

I develop and apply accessible technologies to solve real-world problems in wheelchair mobility:

• Evaluating adapted exercise modes like handcycling and suspended-wheel wheelchair attachments
• Quantifying musculoskeletal safety during exercise to balance cardiovascular benefits with injury risk
• Developing monitoring tools that enable personalized exercise prescription and long-term safety tracking

What I Develop

I build open-source, low-cost systems to support this research:

• Machine learning algorithms that predict external loading during physical activity
• Flexible markerless motion capture pipelines with multi-camera calibration, pose estimation, and 3D triangulation

What I Use

I leverage existing tools and technologies to conduct my research:

• Machine Learning: PyTorch, TensorFlow, scikit-learn for model development
• Computer Vision: OpenCV, DeepLabCut for pose estimation, camera calibration, and 3-D reconstruction
• Biomechanics Analysis: OpenSim for musculoskeletal modeling and simulation
• Wearable Sensors: Smartwatches and IMUs for field-based data collection

My Approach

My work focuses on creating practical measurement tools that bring biomechanics monitoring out of the lab and into real-world settings. By developing accessible systems to study exercise safety and effectiveness, I aim to support the development of better physical activity guidance for manual wheelchair users and the clinicians who work with them.