Philip Krejov
Head Of Hardware at Bigscreen VR
California, United States
Summary
👤
Senior🎓
Top SchoolPhilip Krejov is a hardware-minded software leader with 9 years of experience blending computer vision research and product-focused R&D to deliver photoreal volumetric capture systems for entertainment and VR. Currently Head of Hardware at Bigscreen VR, he previously led volumetric reconstruction and compression breakthroughs at Intel Studios—implementing lossless RAW compression that yielded 10x storage savings and calibrating large 8K multi-camera rigs for view-dependent rendering. His academic pedigree (PhD in Computer Vision) and applied work span hand, face, and body tracking, machine learning-driven annotation, and real-time C++/CUDA systems, with publications in hand pose estimation and novel HCI methods. Comfortable bridging CTO-office research and production engineering, he combines deep technical fluency with product impact—an unusual mix that has saved millions in production costs while advancing immersive filmmaking.
9 years of coding experience
6 years of employment as a software developer
Bachelor of Engineering (BEng), Computer Science, First, Bachelor of Engineering (BEng), Computer Science, First at Surrey UniversityIMIAL Technical Certificate in Vehicle Fitting, Distinction, IMIAL Technical Certificate in Vehicle Fitting, Distinction at Dumfries and Galloway CollageDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Surrey
Github Skills (28)
intel10
hardware10
payment-methods10
sdk10
in-app-purchase10
computer-vision10
camera-api9
realsense9
research-and-development8
depth8
ethernet8
encoder-decoder7
external7
jupyter-notebook6
cpp5
Programming languages (4)
Github contributions (5)
krejov100/DepthCodec
Aug 2018 - Dec 2022
Compression and Decompression lib
Contributions:83 commits, 4 PRs, 76 pushes in 4 years 4 months
deflatedecompressioncompressionsnappygzip
krejov100/sandbox
Jan 2018 - Apr 2018
Contributions:34 commits, 2 PRs, 38 pushes in 2 months
deep-learningpytorchcomputer-visionperception
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