Postdoctoral Researcher · NIH Clinical Center · NeuroRobotics Research Group
The research program treats movement as an integrated loop spanning neural command, muscle activation and deformation, joint motion, sensory feedback, and interaction with assistive technologies. By measuring and perturbing multiple points across this pathway, the goal is to determine how these components couple to produce movement, how those relationships break down in neuromotor disorders, and how rehabilitation can restore them.
Three stages build from foundational research thrusts to cross-signal coupling metrics and, ultimately, predictive and intervention tools.
Stage 1 is divided into four research thrusts. Thrusts 1–3 are active areas of current work; Thrust 4 captures the sensory-feedback foundation that informs the broader program.
Develop cortico-muscular, electro-mechanical, musculo-kinematic, musculo-sensory, and kinematic-sensory metrics that quantify cross-signal relationships across the full chain and localize impairment.
Use validated metrics to forecast response and support clinician-in-the-loop therapy decisions.
All Stage 1 thrusts and projects remain visible. Select a project to bring its related publications alongside it; publication-to-project filtering remains available as well.
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Demonstrates real-time ultrasound-based closed-loop FES control for acquiring kinematic targets.
Presents preliminary feasibility of ultrasound-guided closed-loop FES in individuals with cerebral palsy.
Shows that muscle deformation and limb kinematics share conserved trajectory features consistent with minimum-jerk control.
Validates sonomyography for estimating joint kinematics during voluntary and FES-evoked motion, including in cerebral palsy.
Shows that distributed wearable ultrasound measurements can predict isometric ground-reaction force.
Develops a low-voltage, four-channel wearable ultrasound system for safe, real-time dynamic imaging of deep muscle tissue.
Demonstrates a sonomyography-based muscle–computer interface for proportional control in people with spinal cord injury.
Applies motor-control principles to quantify and compare human–machine interface performance beyond endpoint accuracy alone.
Examines how training-load surrogates relate to patellar-tendon adaptations and neuromuscular performance in collegiate volleyball athletes.
Demonstrates intuitive, proportional, multi-degree-of-freedom control from residual muscle deformation in people with upper-limb loss.
Characterizes how stimulus timing and temperature shape the thermal grill illusion and dynamic thermal perception.
Shows that ultrasound can track joint movement during FES despite electrical-stimulation artifacts.
Demonstrates shared proportional position control of a prosthetic hand using sonomyographic signals.
Establishes the feasibility of quantifying joint movement directly from ultrasound-measured muscle deformation.
Demonstrates volitional target-position control using sonomyographic muscle signals.
Shows that vibrotactile feedback supports accurate sonomyographic target acquisition without visual feedback.
Tests how proprioception contributes to proportional sonomyographic position control for prosthetic applications.
Examines how the timing of thermal stimulation shapes the thermal grill illusion and dynamic thermal perception.
Integrates multisensory feedback with sonomyographic control to study and improve prosthetic-device operation.
Develops a thermoelectric display for controlled assessment of touch sensory deficits.
Invited seminars, conference presentations, thesis talks, workshops, and professional panels.
Teaching, mentorship, scholarly review, workshop leadership, and service to the research community.
Open to collaborations, questions, and conversations about movement science, neuromuscular sensing, and rehabilitation technology.