Xi Yang
Senior Machine Learning Engineer at Red Hat
Shenzhen, Guangdong Province, United States
Summary
👤
Senior🎓
Top SchoolXi Yang is a Senior Data Scientist with dual Ph.D.s in Computer Science & Engineering and Chemical Engineering and nine years of experience translating research-grade methods into production ML systems. Based in Shenzhen, he currently builds and deploys agentic LLM applications at Aspen Technology, specializing in fine-tuning (SFT, RL), PEFT, RAG, tool-integrated reasoning, and LLMOps for domain-specific tasks. His background spans physical modeling and thermodynamics to transportation and sensor data mining, giving him uncommon strength at the intersection of physics-informed models and modern deep learning. Proficient in Python, TensorFlow, PyTorch and Keras, he focuses recently on low-level vision and AIGC research as reflected in his GitHub activity. A published researcher with top-tier conference and journal papers, he combines rigorous academic training with pragmatic production deployment experience. Colleagues describe him as a collaborative problem-solver who bridges multidisciplinary teams and complex technical domains.
9 years of coding experience
11 years of employment as a software developer
High School Diploma, High School Diploma at Chengdu NO.7 High School 成都市第七中学Bachelor's degree, Chemical Engineering, Bachelor's degree, Chemical Engineering at Tianjin UniversityDoctor of Philosophy - PhD, Computer Science and Engineering, Doctor of Philosophy - PhD, Computer Science and Engineering at University of ConnecticutMaster of Science - MS, Chemical Engineering, Master of Science - MS, Chemical Engineering at University of Florida
English, Chinese
Github Skills (18)
depth9
image-quality8
optical-flow8
denoising8
super-resolution8
depth-estimation8
interpolation7
image-restoration6
computer-vision5
raw-image5
video-quality5
sampling5
pytorch5
image-processing4
deep-learning3
Programming languages (2)
Github contributions (5)
IanYeung/RealVSR
Aug 2021 - Nov 2021
Dataset and Code for ICCV 2021 paper "Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme"
Contributions:8 commits, 6 pushes, 1 branch in 3 months
super-resolution
IanYeung/MGLD-VSR
Nov 2023 - Jan 2025
Code for ECCV 2024 Paper "Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolution"
Contributions:8 pushes, 24 comments, 4 issues in 1 year 1 month
super-resolution
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