Jason Wang
Researcher, Engineer, and Data Scientist
I'm a Ph.D. Candidate in the School of Data Science at the University of Virginia, working under the guidance of Dr. Stephen Baek. My research focuses on advancing markerless 3D human pose estimation for biomechanical applications, with the goal of making accurate motion analysis accessible outside of specialized laboratory settings.
My work bridges the gap between computer vision and biomechanics, developing methods to extract clinically meaningful measurements from standard video footage. This has applications in sports performance analysis, occupational ergonomics, and clinical movement assessment.
I'm passionate about translating cutting-edge AI research into practical tools that can benefit athletes, workers, and patients.
Education
Ph.D. in Data Science
University of Virginia
Aug 2022 - Present • GPA: 4.0/4.0
Advisor: Dr. Stephen Baek
Dissertation: Advancing Markerless 3D Human Pose Estimation for Biomechanical Applications
M.S. in Data Science
University of Virginia
June 2021 - May 2022 • GPA: 3.9/4.0
B.A. in Mathematical Statistics and Probability
University of Virginia
Aug 2017 - May 2021 • GPA: 3.8/4.0
Professional Experience
Graduate Research Assistant
Aug 2020 - PresentVisual Intelligence Laboratory, Charlottesville, VA
- •Working on a NIOSH Grant to evaluate the efficacy of vision-based approaches for analyzing worker postures, comparing stereo and monocular camera systems against motion capture technology
- •Helped organize and execute a comprehensive study involving 48 subjects subjected to simulated manufacturing tasks
- •Improving 2D-3D lifting capabilities of human pose estimation algorithms with geometric and physical constraints
- •Using generative AI to generate synthetic 3D and 2D poses to improve performance on in-the-wild data
Computer Vision Engineer Intern
Feb 2022 - Aug 2022Biocore LLC, Charlottesville, VA
- •Leveraged multi-view geometry across 30+ camera views to triangulate and reconstruct 3D human body poses of NFL football players
- •Incorporated advanced deep learning techniques to refine human football player poses with heavy occlusions
- •Collaborated with NFL's AWS next-gen stats system to analyze player movements and enhance on-field safety
Data Science Intern
May 2020 - Aug 2020Gamebytes (YC W19), Washington, DC
- •Designed and executed user retention analyses to uncover behavioral patterns correlated with long-term engagement, directly informing product strategy
- •Built data pipelines using Python and SQL to extract, clean, and analyze large-scale user activity databases
- •Contributed to growth strategy that propelled the app from #120 to #3 in the App Store Social Media category
Publications
Assessment of Computer-Vision Based Worker Posture Analysis Methods
Wang J., Guzowski T., Barnett A., Fethke N., Baek S.
IISE Transactions (2026)
Deep Learning for Predicting Pediatric Crohn's Disease using Histopathological Imaging
Sharma A.*, Lawlor B.*, Wang J.*, et al.
IEEE (2022) — * indicates equal contribution
Automated Biomechanical Analysis of Tennis Serve Using Internet Videos
Wang J., Kim E., Ho P., Min S., Kupperman N., Baek S.
ACM Transactions (2026)
3D Computer Vision Pose Estimation to ISB Standard Biomechanical Angle Representation
Wang J., Kupperman N., Baek S.
(2025)
Presentations
2025
Visual Intelligence in Athletic Performance
Sports Research and Technology Innovation Summit, Charlottesville, VA
oral Presentation
Visual Intelligence in Computer Vision and Sports Science Intersection
VIL Lab Summit
oral Presentation
Automated Biomechanical Analysis of Tennis Serve Using Internet Videos
PhD Student Showcase, Charlottesville, VA
poster Presentation
Automated Biomechanical Analysis of Tennis Serve Using Internet Videos
ISB Conference, Stockholm, Sweden
poster Presentation
2024
Assessment of Computer-Vision Based Worker Posture Analysis Methods
Poster Award WinnerPoster Presentation
poster Presentation
2023
Motion Manifold Analysis of Tennis Players: Bridging Online Video Data with Sports Performance Analysis
Presentation AwardAsia-Singapore Conference on Sport Science, Singapore
oral Presentation
Motion Manifold Creation with an Isometric Autoencoder
PhD Student Showcase, Charlottesville, VA
oral Presentation
2022
Deep Learning for Predicting Pediatric Crohn's Disease using Histopathological Imaging
IEEE Symposium on Systems and Information Engineering Design, Charlottesville, VA
oral Presentation
Teaching Experience
DS6040
Bayesian Machine Learning
Summer 2024
DS6270
Numerical Analysis and Optimization for Data Science
Fall 2023
DS6050
Deep Learning
Spring 2023
DS6010
Theory I: Probability & Stochastic Processes
Fall 2022
Skills & Expertise
Languages
ML/DL
Tools
Domains
Research Advisor
Stephen Baek, Ph.D.
Quantitative Foundation Associate Professor of Data Science
Associate Professor of Mechanical and Aerospace Engineering (by courtesy)
Shannon Center Mid-career Faculty Fellow
University of Virginia
Get in Touch
I'm always interested in discussing research collaborations, potential applications of my work, or opportunities in industry and academia.