Liang Wu is a quantitative trader and AI researcher with nine years of applied experience building and deploying deep learning systems across mobile, autonomous driving, and academic settings. Trained in computer vision and machine learning through MPhil research at HKUST and Nanjing University and an MS in Financial Engineering, he bridges rigorous research with production-grade model deployment. His work spans roles at Alibaba, ReadSense, AllRide.ai, and a recent mobile deep learning stint at Tap, reflecting deep expertise in perception, image/text analysis, and on-device inference. Now freelancing as a quantitative trader in Hong Kong, he brings a data-driven, model-centric approach to markets informed by hands-on algorithm engineering. An active researcher with a Google Scholar profile and a personal site, he blends academic publishing with pragmatic product engineering—often optimizing models for resource-constrained environments.
8 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Financial Engineering, Master of Science - MS, Financial Engineering at CityU College of Business
Master of Philosophy, Research in Computer Vision and Machine Learning, Master of Philosophy, Research in Computer Vision and Machine Learning at Nanjing University
Hong Kong University of Science and Technology (HKUST)
use eye gaze to control the movement of a vehicle in ros
Contributions:4 PRs, 5 pushes in 3 years 1 month
roboticsrosbageye-gazeeyevehicle
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