Advanced data analytics and reporting process for greenhouse gas emission reduction commitment through (1) co-developing methodologies for corporate scope 3 greenhouse gas emission calculations and the emission forecasts, (2) programmatic data quality check (completeness, quality, correction and version control), (3) automating the processes of calculating greenhouse gas emissions based on survey and modeled data (python).Established a scientific framework to recommend remote sensing solutions for conservation practice verification for the Global Carbon InitiativeDeveloped and tested digital tools to enhance crop management decisions and behaviors for customers in Asia

Affiliated with the GEMS (Genetics, Environment, Management and Socioeconomics) Informatics Center (https://agroinformatics.org), and worked full-time for the Soil Health Partnership (SHP) to support the program.Built a machine learning model to predict soil organic carbon changes.Led statistical analysis of the SHP’s soil health index, crop yield, soil properties, weather conditions and satellite images of fields (about 100 fields over 2-5 years) under conventional and conservation practices.Led and collaborated with researchers at non-profits (The Nature Conservancy) and universities on writing a non-technical paper on the SHP's approach to soil health.Initiated/coordinated/participated cross-functional team collaboration to deliver farmer-focused science products (data visualization graphics, non-technical paper, and soil and yield report) for the SHP.Developed a research innovation grant proposal with colleagues at UMN on linking satellite images, process-based models and field trials for soil water conservation under cover cropping systems ($122,841, not funded). Communicated the use of remote sensing in managing crop production to farmers (through farmer-focused research meetings and one-on-one conversations).

— Research Experience— Summary: I conducted research on effects of agronomic practices on carbon sequestration and crop yield under various climatic conditions at field and regional scales for US and African countries using big data, process-based modeling and remote sensing techniques. Specifically: Developed and implemented algorithms (in Python on the High Performance Computers) to forecast corn yield in small fields in Tanzania based on the integration of crop modeling, field samplings and questionnaire surveys. The new forecasting system was presented to UN FAO at Tanzania and the Government of Tanzania.Processed and analyzed satellite images, and public weather, soil, crop yield, management and crop type databases.Modeled the effect of tillage, climates and their interactions on the soil carbon and yields of different crops (corn, wheat, soybean, yam, switchgrass and legumes) in US & several African countries.Constructed multiple regression and random forest models to predict crop yield in Tanzania using weather characteristics and remote-sensing vegetation indices.Designed field experiment and collected soil moisture to assess and model soil water routing within a field.Developed, and delivered a crop simulation model without interface to run on batch mode. Deliverables: I published 9 peer-reviewed papers and received grants, awards, and fellowships: https://scholar.google.com/citations?user=6m4hnSoAAAAJ&hl=en— Services — Presented research results at 10+ research and development conferences (invited speaker and an award-winning poster).Developed and hosted programming workshops including introduction to basic programming and using R to model plant leaf expansion.Organized and moderated university events about environmental research and policy, and the application of agricultural technology to food security. Facilitated writing workshops at American Society of Agronomy.Provided review comments to peer-review scientific journals.

I was an instructor for a science literacy course (ISP203 Geology of the Human Environment Laboratory) that was designed for non-science major undergraduates. I taught 3 lab sessions per week with 20+ students per session. I gave a short lecture in the beginning of the class, facilitated students' lab activities, held office hour (1 hour per week) and graded weekly assignments and exams. I also contributed to lab activity development during weekly meeting with the course coordinator.