Krys Feng is an AI Engineer with 12 years of experience blending academic research and product-focused machine learning to build real-world computer vision and multimodal systems. With an MASc from the University of Waterloo, he developed photometric calibration techniques for visual SLAM and contributed to camera calibration under refraction—work that bridges robust geometric methods and practical deployment. In industry roles he has shipped mobile AI features using Google ML Kit in cross-platform apps and architected LLM and vision-language pipelines for enterprise-scale systems. His team placed Silver (top 3.2%) in the 2023 Kaggle Image Matching Challenge, highlighting hands-on expertise in 3D reconstruction and camera localization. Krys pairs deep optics and imaging experience from earlier R&D roles with recent LLM fine-tuning and inference optimization, making him adept at translating cutting-edge research into production-ready AI solutions.
12 years of coding experience
3 years of employment as a software developer
Bachelor of Science, Electrical and Computer Engineering, Bachelor of Science, Electrical and Computer Engineering at National Chiao Tung University
exchange student, Techonlogy, exchange student, Techonlogy at Reutlingen University
Master's degree, Computer Vision | System Design Engineering, Master's degree, Computer Vision | System Design Engineering at University of Waterloo
Contributions:28 pushes, 1 branch in 5 years 4 months
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