cv
Basics
Name | J.D. Peiffer |
Label | PhD Candidate |
jd.peiffer {at} gmail.com | |
Phone | (312) 238-1475 |
Url | https://peifferjd.github.io |
Summary | J.D. is a PhD Candidate working at the intersection of computer vision and biomechanical modelling. |
Education
Awards
- May 2022
Graduate Research Fellowship
National Science Foundation
- June 2024
T32 Training Grant
National Institutes of Health
Publications
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2025.07.11 Portable Biomechanics Laboratory: Clinically Accessible Movement Analysis from a Handheld Smartphone
arXiv
Develops a method for fitting biomechanical models to data collected from a handheld smartphone in clinical settings.
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2024.11.22 Differentiable Biomechanics for Markerless Motion Capture in Upper Limb Stroke Rehabilitation: A Comparison with Optical Motion Capture
arXiv
Validates our computer vision approach to gold standard biomechanics in the upper limb.
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2024.09 Biomechanical Arm and Hand Tracking with Multiview Markerless Motion Capture
2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)
Applies earlier joint optimization of biomechanical models to the ARMS Lab's leading hand model.
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2024.09 Fusing Uncalibrated IMUs and Handheld Smartphone Video to Reconstruct Knee Kinematics
2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)
Presents a deep learning approach to fit a biomechanical model to video and IMU data collected during walking.
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2024.04.01 Hyperpolarized 129Xe MRI, 99mTc scintigraphy, and SPECT in lung ventilation imaging: a quantitative comparison
Academic Radiology
Compares a recently FDA approved method for lung imaging to the clinical standard in a large patient cohort.
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2023.9.24 Optimizing Trajectories and Inverse Kinematics for Biomechanical Analysis of Markerless Motion Capture Data
2023 International Conference on Rehabilitation Robotics (ICORR)
Develops a novel approach to jointly optimize body scale and joint paramaters for markerless motion capture.
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2023.09.01 Self-Supervised Learning of Gait-Based Biomarkers
Predictive Intelligence in Medicine
Creates a transformer that given timeseries of gait data learns a self-supervised embedding space useful for downstream tasks.
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2023.08.01 Enhanced selectivity of transcutaneous spinal cord stimulation by multielectrode configuration
Journal of Neural Engineering
Explores electrode placement and configuration to improve the selectivity of transcutaneous spinal cord stimulation.
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2023.03.19 Markerless Motion Capture and Biomechanical Analysis Pipeline
arXiv
Hardware and software pipeline for markerless motion capture and biomechanical analysis.
Skills
Machine Learning | |
Jax | |
PyTorch | |
Computer Vision | |
Self Supervised Learning | |
Deep Reinforcement Learning |
Biomechanics | |
Mujoco-MJX | |
Myosuite | |
Neurophysiology |
Wearables | |
IMU Fusion |
Software Development | |
Docker | |
Kubernetes | |
Git | |
Python | |
SQL |
Projects
- 2025.06 - Present
Single camera biomechanical human pose estimation
Accurately recovering human pose from a single camera could democratize access to biomechanical analysis and enable big data studies of human movement. My algorithms incorporate physical constraints to improve accuracy and interpretability.
- Computer Vision
- Deep Learning
- Biomechanics
- 2022.09 - 2024.10
Video-IMU fusion for human pose estimation
While video is a powerful and accessible sensor, it will always be limitied by occlusions. This work combines video and IMU data to improve accuracy and robustness of human pose estimation.
- Computer Vision
- Deep Learning
- Sensor Fusion
Volunteer
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2023.04 - Present Speaker
National Biomechanics Day
Developed interactive sessions for high school students to learn about biomechanics, prosthetics and computer vision.
- Awarded 'Climate Hero' award by Greenpeace for my efforts organizing the march.
- Men of the year 2014 by Time magazine