Stephen Remde
CTO at Gaist Holdings Limited
Greater Leeds Area United Kingdom
Summary
👤
Senior🎓
Top SchoolStephen Remde is a CTO and technology leader with 13+ years of experience building and scaling research-driven products that blend optimization, machine learning, and computer vision. At Gaist he oversees research, software, and hardware teams, has guided two funding rounds, and commercialized novel technologies that led to patents and academic publications. His PhD work on scheduling geographically distributed workforces and a Jisc-funded project on concept linkage show a strong background in applied AI, optimization, and big-data text mining. He pairs hands-on engineering—illustrated by meaningful contributions to the popular node-fluent-ffmpeg project around input format handling and stream error detection—with strategic product and commercialization experience. Known for mentoring PhD students and shepherding university-industry knowledge transfer, he thrives at the intersection of research and practical delivery. Based in the Leeds area, he combines academic rigor with a pragmatic focus on turning prototypes into funded, market-ready solutions.
13 years of coding experience
3 years of employment as a software developer
KTP, KTP at University of YorkDoctor of Philosophy (Ph.D.) Artificial Intelligence Optimisation Operations Research, Doctor of Philosophy (Ph.D.) Artificial Intelligence Optimisation Operations Research at University of Bradford
English
Github Skills (5)
video-processing10
nodejs10
javascript10
ffmpeg10
api-design9
Programming languages (9)
Github contributions (5)
fluent-ffmpeg/node-fluent-ffmpeg
Apr 2013 - Jun 2013
A fluent API to FFMPEG (http://www.ffmpeg.org)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:8 commits in 2 months
Contributions summary:Stephen primarily contributed to the core functionality of the `node-fluent-ffmpeg` library. Their commits added the capability to specify input formats, providing more control over the video processing workflow. They also introduced error detection for input streams and optimized metadata loading. Furthermore, they removed a dependency and refactored code to reduce meta data loading when not needed.
apivideofluentffmpegfluent-api
smremde/sharp
Sep 2016 - Mar 2024
Contributions:5 pushes in 7 years 7 months
tiffimagenode-jsfastesttiff-images
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