Chun Ng
Chief AI Officer at AI LENS
Penang, Malaysia
Summary
👤
Senior🎓
Top SchoolChun Ng is a Chief AI Officer and PhD-trained computer vision researcher with a decade of experience building OCR and document-intelligence solutions for fintech and industrial applications. He has led engineering teams and designed scalable, secure platforms that apply text detection, recognition, and LLM-driven features to enable fraud detection and risk assessment. His academic work produced ICText and the Attribute-Guided Curriculum Learning method, and he developed low-light image enhancement techniques (Supervised-DCE) to boost text detection in challenging conditions. Chun combines hands-on research—peer-reviewed at ICDAR and ICPR—with product-focused leadership, moving innovations from datasets and models into production. Based in Penang, Malaysia, he brings a rare mix of deep OCR expertise, practical deployment experience, and a track record of translating niche research (integrated-circuit text recognition) into real-world financial and industrial impact.
10 years of coding experience
7 years of employment as a software developer
Bachelor of Computer Science (Honours) in Software Engineering, Computer Science, Distinction, Bachelor of Computer Science (Honours) in Software Engineering, Computer Science, Distinction at Tunku Abdul Rahman University CollegeDoctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at University of Malaya
English, Malay, Chinese
Github Skills (54)
pytorch10
text-recognition10
tensorrt10
onnx10
openvino10
scene-text10
ncnn10
text-detection10
object-detection10
classification9
image-enhancement9
yolov59
ranking9
deep-learning9
structure-from-motion9
Programming languages (5)
Github contributions (5)
vitrox-technologies/icdar_ictext
Nov 2020 - Mar 2021
Contributions:27 commits, 26 pushes, 1 branch in 4 months
chunchet-ng/Text-in-the-Dark
Sep 2023 - Dec 2025
Text in the Dark dataset. The first extremely low light text dataset based on SID and LOL datasets with a total of 3,075 images and 59,975 texts annotated.
Contributions:13 pushes, 2 branches in 2 years 3 months
image-enhancementocrtext-detectionextremely-low-lighttext-dataset
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