Minghui Zhang is a Senior Data Scientist with nine years of experience turning satellite imagery and large time-series datasets into actionable insights on climate-agriculture interactions. With a PhD from UC Berkeley, he developed the first scalable, field-scale method to estimate crop planting dates across Brazil using cloud-native MODIS analysis and now applies regression models to quantify planting responses to wet-season onset. He blends strong statistical rigor and production-grade tooling—R, Python, Google Earth Engine and GIS programming—with hands-on backend development experience contributing text-extraction features to an open-source OFD document library. Based in the Washington DC–Baltimore area, Minghui has a track record across academia and industry (Plenty, Apella) of moving research into operational impact. Colleagues praise his ability to simplify noisy remote-sensing signals into interpretable metrics that inform agricultural decision-making.
8 years of coding experience
2 years of employment as a software developer
Master of Science - MS, Civil and Environmental Engineering, Master of Science - MS, Civil and Environmental Engineering at University of California, Berkeley
Bachelor of Science - BS, Chemical Engineering, Bachelor of Science - BS, Chemical Engineering at Carnegie Mellon University
Contributions:49 commits, 43 PRs, 43 comments in 8 months
Contributions summary:Minghui primarily contributed to the OFD processing library by implementing features related to text extraction and keyword positioning within OFD documents. They added functionalities to extract text content, locate keywords within text, handle page block nesting, and calculate text width, enhancing the library's text processing capabilities. These additions involve modifications to the core reader and text extraction modules of the library.
Contributions:42 PRs, 52 pushes, 2 comments in 2 years 2 months
txthandwritingreader-writermupdfreader
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