Dániel Terbe
Researcher Developer In The Computational Optical Sensing And Processing Laboratory
Budapest, Hungary
Summary
👤
Senior🎓
Top SchoolDániel Terbe is a researcher-developer with 10 years of experience at the intersection of physics, computer science and AI, currently working on computational optical sensing at MTA SZTAKI in Budapest. He specializes in machine learning for computer vision and image processing, with applied expertise in remote photoplethysmography (camera-based pulse estimation) and digital holographic microscopy, including real-time implementations for resource-constrained embedded systems and mobile apps. Trained originally as a physicist with an Info-Bionics MSc, he brings a strong quantitative background in statistical inference and biophysical neuron modeling that informs his data-driven approach to imaging problems. Dániel has a track record of translating academic literature into deployable algorithms and prototypes, and frequently bridges experimental optics with deep learning pipelines. Colleagues describe him as comfortable moving "from the external to the internal"—from physical measurement systems to the neural models that interpret them—making him adept at multidisciplinary, application-focused research engineering.
10 years of coding experience
5 years of employment as a software developer
Bachelor of physics, Physics, 4.5, Bachelor of physics, Physics, 4.5 at Eötvös Loránd UniversityMaster's degree, Info-Bionics, Master's degree, Info-Bionics at Pázmány Péter Katolikus Egyetem
English, German
Github Skills (124)
python10
deep-learning10
gpu10
forecast10
uncertainty10
gpu-acceleration10
numpy10
ai10
neural-network10
experiment10
tensor10
artificial-intelligence10
basler10
clearml10
pytorch10
Programming languages (7)
Github contributions (5)
terbed/parameter-inference
Oct 2016 - Jun 2023
Contributions:182 pushes, 2 branches in 6 years 9 months
terbed/PyTorch-YOLOv3
Mar 2020 - Apr 2020
Minimal PyTorch implementation of YOLOv3
Contributions:63 commits, 56 pushes in 1 month
pytorch
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