Zheng Yuan is a highly skilled and accomplished computer vision technologist with 10+ years of experience in various image and video processing, compression, and machine learning topics. He holds a PhD in Electrical and Computer Engineering from the University of Florida, an M.S. in Electrical Engineering from Shanghai Jiao Tong University, and a B.S. in Electrical Engineering from Jilin University. He has also completed coursework in data visualization, building successful startups, and product-market fit at Stanford Continuing Studies.

Yuan's expertise includes traditional machine learning and deep learning, feature engineering, modeling, Naive Bayesians, logistic regression, boosting trees, SVM, linear regression, convolution neural networks, RNN, and model selection. He has designed and implemented algorithms for visual object classification, image and video segmentation, video compression, retargeting, semantic summarization, deblurring/denoising, and quality estimation. Yuan's research in computer vision encompasses video feature representation, semantic analysis, segmentation, visual recognition, and camera geometry.

Yuan is proficient in C/C++, Python, NumPy, and Matlab, with a deep and profound mathematical and statistical background, including matrix theory, modern multivariate statistical techniques, optimization, and statistical inference. He stays up to date on industry standards such as HEVC, HDR, H264/AVC, AVS2, MPEG-DASH, and emerging technologies.

Yuan has worked in various roles, including Principal Member of Technical Staff at Salesforce, Deep Learning Software Engineer at NVIDIA, Senior Research Scientist at Real Communications Inc. at Realtek Semiconductor Corp., Research Intern at InterDigital Communications, Research Intern at Huawei Technologies, Research Assistant at the University of Florida, and Software Engineering Intern at Intel Corporation.