Wentao Huang
Researcher at Johns Hopkins University School of Medicine
Baltimore, Maryland, United States
Summary
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Top SchoolWentao Huang is a researcher with eight years of experience at the intersection of computational neuroscience and machine learning, currently based at Johns Hopkins University School of Medicine. He develops mathematical theories rooted in information theory to explain neural phenomena and to design efficient, brain-inspired deep learning algorithms. His work spans computer vision, image/video processing, NLP, and intelligent systems, with practical applications from robotics to algorithmic trading. Strong mathematical modeling and software skills (Python, Matlab, C/C++) allow him to translate theory into robust, compact learning systems. Previously he contributed as a research associate at Los Alamos National Laboratory, bringing experience in high-impact, interdisciplinary research. He aims to create miniaturized, efficient, and robust brain-like learning architectures that bridge neuroscience insights and real-world AI applications.
7 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy (Ph.D.), Computational neuroscience, computer vision, image processing and machine learning, Doctor of Philosophy (Ph.D.), Computational neuroscience, computer vision, image processing and machine learning at Xidian University
Chinese, EnglishGithub contributions (3)
hwtsky/Population-Infomax
May 2018 - Jun 2018
Contributions:1 push, 1 branch in 20 days
hwtsky/color-vision
Jul 2018 - Jul 2018
Contributions:2 pushes, 1 branch in 1 day
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