Daniel Groos
Data Scientist
Arendal, Agder, Norway
Summary
👤
Senior🎓
Top SchoolDaniel Groos is a data scientist and AI researcher with 11 years' experience applying deep learning to medical technology and movement science, including PhD work on video-based motion capture and prediction of cerebral palsy in high-risk infants. He has driven research and engineering at NTNU on projects like In-Motion and DeepInMotion, and has applied kinematic analysis to elite sports in collaboration with Olympiatoppen. Comfortable bridging academia and industry, he has experience from Telenor anomaly detection on large network data to front-end component work and digital marketing earlier in his career. Daniel combines rigorous PhD-level modeling with hands-on implementation, often translating research prototypes into practical tools for clinicians and sports scientists.
11 years of coding experience
5 years of employment as a software developer
Norges teknisk-naturvitenskapelige universitetUniversity Admission Certification, General Studies with specialization in Mathematics and Natural Science, University Admission Certification, General Studies with specialization in Mathematics and Natural Science at Dahlske Videregående SkoleNorwegian University of Science and Technology
Norwegian, English, Spanish
Github Skills (57)
openpose10
pose10
tensorlayer10
human-pose-estimation10
mobilenet10
espn10
player10
csv10
feature-matching10
points10
csv-reader10
xai9
python9
classification9
pose-estimation9
Programming languages (3)
Github contributions (5)
daniegr/EfficientPose
Dec 2019 - Jan 2023
Scalable single-person pose estimation
Contributions:55 commits, 18 PRs, 23 pushes in 3 years 1 month
person-pose-estimationscalablefeature-matchingtensorlayerperson
DeepInMotion/MovementOutcome
Sep 2022 - Jan 2023
Contributions:27 PRs, 44 pushes, 26 branches in 3 months
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