Xiaocheng Huang is an Innovation Engineer with ten years of experience, currently leading a five-person team at Beijing Tengineer AIoT Tech where he bridges algorithm research, solution design, and project delivery for distributed photovoltaic systems and carbon emissions. He has authored and productionized algorithms and C libraries for PV forecasting, anomaly monitoring, group control, and solar capacity analysis in low-voltage distribution contexts. Xiaocheng combines hands-on neural network training and feature extraction with systems thinking—designing digital simulation algorithms, UI interaction flows, and databases to support PV carrying capacity and anti-theft applications. He has translated research into funded grid-technology projects and university collaborations, producing practical tools for carbon flow tracing, emission metering, and energy distribution optimization. Currently completing an online MS in Data Science from the University of Colorado Boulder, he pairs academic rigor with field-proven solutions in China’s smart-grid and renewable energy space.
10 years of coding experience
Bachelor's degree, Electronic Information Engineering, Bachelor's degree, Electronic Information Engineering at 吉林大学
Master's degree, Data Science(online), Master's degree, Data Science(online) at University of Colorado Boulder College of Engineering & Applied Science
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