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MS, PhD

Northwestern University, Shirley Ryan AbilityLab

Biomedical Engineering

• GPA: 3.81; NSF Graduate Research Fellowship (2022); NIH T32 Training Grant (2024)

Rotation Student

Washington University in St. Louis

Biomedical Engineering

BS

University of Missouri

Biomedical Engineering

• GPA: 3.92; Emphasis: Bioinformatics; Minor: Mathematics
• Honors Scholar; Dean’s List (all semesters)

PhD Researcher

Center for Bionic Medicine, Shirley Ryan AbilityLab

• Led first-author research in computer vision, sensor fusion, and biomechanical modeling for clinical AI, taking models from concept through validated clinical deployment; 15+ publications, >170 citations in <4 years.
• Developed and released the Portable Biomechanics Laboratory — the first clinically validated single-camera smartphone gait analysis system, achieving <3° joint-angle error and ICC > 0.9 for derived gait biomarkers; first-author paper in npj Digital Medicine (Nature).
• Deployed PBL to 3 external clinical sites (Shriners Children’s, Lake Lucerne Institute), each of which published independent validation studies; demonstrated derived gait metrics detect surgical response in cervical myelopathy more sensitively than standard patient-reported outcomes.
• Designed a neural-network fusion of uncalibrated IMU and monocular smartphone video, cutting knee angle error 26% while maintaining accuracy through visual occlusions.
• Co-authored B3D, a feed-forward biomechanical prediction head on a frozen SAM-3D-Body foundation model, distilled label-free via differentiable MuJoCo physics; accepted to ECCV 2026 workshop.
• Built multi-camera calibration and SAM-based pseudo-labeling pipelines, generating pseudo-ground-truth annotations to train and benchmark monocular scene reconstruction models; curated a 10,000-video clinical movement dataset for scene understanding model development.
• Trained a contrastive learning + causal masking transformer on unannotated clinical gait data; demonstrated learned embeddings classify neurological diagnosis and track patient response to inpatient therapy.

Research Scientist Intern

Glove Sensing and Tracking Team, Meta Reality Labs

• Implemented a real-time hand pose estimation and inverse-kinematics pipeline achieving <5 mm fingertip tracking error at 60 Hz with occlusion robustness across a 22-DoF hand model.
• Trained a CNN+Transformer model on fiber-optic sensor data for direct hand pose regression, benchmarking learned pose estimation against an inverse-kinematics baseline.
• Collected a dexterous-manipulation benchmarking dataset with motion-capture ground truth and authored production evaluation pipeline; first-author paper accepted to IROS 2026.

Fulbright-Mitacs Globalink Intern

Neuromuscular Control & Biomechanics Laboratory, University of Alberta

• Computationally modeled seated human trunk biomechanics under Functional Electrical Stimulation (FES) and designed LQR and fuzzy inference (FIS) feedback controllers; validated closed-loop stability in simulation.

Undergraduate Researcher

Neural Engineering Laboratory, University of Missouri

• Developed and optimized a closed-loop gamma oscillation detection and modulation algorithm achieving <2 ms latency on embedded hardware; open-sourced on GitHub.

Undergraduate Researcher

Pulmonary Imaging Research Laboratory, University of Missouri

• Built a semi-automated image segmentation, registration, and quantification pipeline enabling large-cohort comparison of 129Xe MRI vs. 99mTc SPECT; first-author publication in Academic Radiology (2024).
• Won Audience Choice Award for oral presentation at International Workshop on Pulmonary Functional Imaging (2019).

Biomechanics-aware Multi-view Markerless Motion Capture of Dexterous Hand Movements

Biomechanical 3D Body: Self-Supervised Distillation of Biomechanical Pose from a 3D Body Foundation Model

Fiber Optic Sensing Glove for High Performance Dexterous Manipulation Capture

Portable biomechanics laboratory enables clinically accessible movement analysis from a handheld smartphone

Markerless Motion Capture for Biomechanical Whole-Body Kinematic Estimation in Infants

Monocular Markerless Motion Capture Enables Quantitative Assessment of Upper Extremity Reachable Workspace

Differentiable Biomechanics for Markerless Motion Capture in Upper Limb Stroke Rehabilitation: A Comparison With Optical Motion Capture

Synergy-based functional electrical stimulation for gait rehabilitation in chronic stroke: a pilot study

Fusing Uncalibrated IMUs and Handheld Smartphone Video to Reconstruct Knee Kinematics

Biomechanical Arm and Hand Tracking with Multiview Markerless Motion Capture

Hyperpolarized 129Xe MRI, 99mTc scintigraphy, and SPECT in lung ventilation imaging: a quantitative comparison

Optimizing Trajectories and Inverse Kinematics for Biomechanical Analysis of Markerless Motion Capture Data

Self-Supervised Learning of Gait-Based Biomarkers

Enhanced selectivity of transcutaneous spinal cord stimulation by multielectrode configuration

Teaching Assistant — Biomedical Applications of Machine Learning

Northwestern University

• Instructed graduate students in Python-based ML including data preprocessing, regression, tree-based methods, DNNs, and CNNs.

Teaching Assistant — Advanced Hydroinformatics

University of Missouri

• Created curriculum introducing graduate students to scientific data manipulation and parallel computation job submission on HPC clusters.

Ski Instructor

Vail Resorts

Speaker

National Biomechanics Day

Developed interactive sessions for high school students on biomechanics, prosthetics, computer vision, and AI for medical image analysis.

Peer Reviewer

BioRob, IROS, iScience, CMBBE — Imaging & Visualization

Site Leader

Mizzou Alternative Breaks

• Organized a week-long adaptive sports service trip (Ski Apache, NM) for 12 participants; assisted in instruction of students with visual, cognitive, and physical disabilities.