Wearable Sensing for Remote Health Monitoring

My PhD research at Georgia Tech focuses on wearable and ubiquitous sensing systems for remote health monitoring and diagnostics, with a particular emphasis on contexts where conventional medical infrastructure is absent or unreliable.

The core problem

Most medical sensing technology is designed around access: access to power grids, to trained technicians, to hospital-grade calibration. That design assumption quietly excludes the populations who need monitoring most. Remote and underserved communities face a compounding disadvantage: higher burden of chronic disease, less access to routine care, and diagnostic tools that weren’t built for their environment.

Wearable and ambient sensing offers a different path: continuous, low-friction data collection that can operate at the point of need rather than the point of care. But getting there requires solving problems at multiple levels: hardware that is durable, low-power, and manufacturable at scale; signal processing pipelines that work with noisy, intermittent data; and interfaces designed for users who are not clinicians.

Research direction

Working with my advisor Dr. Alexander T Adams, my research targets the full stack from sensor design through clinical deployment, with sustainability as a core design constraint rather than an afterthought. This means:

• Sensing systems that function in low-resource and off-grid environments
• Diagnostic pipelines that can operate on-device, without cloud dependency
• Evaluation grounded in fieldwork and active clinical partnerships, not just lab benchmarks

Why this matters

There is a gap between what sensor technology can do in a controlled lab and what it actually does in a patient’s home, a rural clinic, or a community health setting. Closing that gap is both a human-centered design problem and a technical one. That’s why it belongs in an HCI program.

Status

Incoming PhD student, fall 2026.