Adrian Bulat
Principal Research Scientist at Samsung Electronics
Greater Cambridge Area United Kingdom
Summary
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Rockstar🎓
Top SchoolAdrian Bulat is a Principal Research Scientist at Samsung AI Center Cambridge with 13 years of experience applying deep learning to efficient, real-world computer vision problems. He holds a PhD in Computer Science from the University of Nottingham and has a track record of translating research into robust code, exemplified by his PyTorch-based 2D/3D face alignment library and work on FAN and ResNetDepth models. His background spans academia and industry—from teaching computer vision and C++ labs to building production web systems—giving him a rare blend of theoretical depth and engineering pragmatism. Based in Greater Cambridge, he combines hands-on model development with production-minded optimizations, and is known for readable, well-tested code and contributions that bridge research prototypes and deployable systems.
13 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of NottinghamBachelor's degree, Computer Engineering, Bachelor's degree, Computer Engineering at Gheorghe Asachi Technical University of Iași
English, Romanian
Github Skills (9)
computer-vision10
pytorch10
machine-learning10
deep-learning10
python10
face-alignment10
image-processing9
faster-rcnn8
mask-rcnn8
Programming languages (5)
Github contributions (5)
1adrianb/face-alignment
Sep 2017 - Aug 2021
:fire: 2D and 3D Face alignment library build using pytorch
Role in this project:
ML Engineer
ML EngineerContributions:13 releases, 1 review, 162 commits in 3 years 11 months
Contributions summary:Adrian made initial commits and numerous updates focused on building and refining a face alignment library. Their contributions centered on defining and modifying the core models using PyTorch, including the FAN and ResNetDepth architectures. They also modified utility functions for Gaussian kernel generation, image transformation, and heatmap processing, indicative of their work in the domain of computer vision and machine learning. Furthermore, the user addressed code style issues and integration with test frameworks.
3dface-alignmentpytorchpythondeep-learning
1adrianb/binary-face-alignment
Feb 2017 - Apr 2021
Real time face alignment
Contributions:10 commits, 2 PRs, 7 pushes in 4 years 3 months
face-alignmentdeep-learningtorch7convolutional-neural-networksbinary-convolutions
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