Hello! I am Anish Lamsal, an Agricultural Engineer transitioning into the data analytics field as an M.S. Data Analytics student at Binghamton University starting Fall 2026. I blend field engineering expertise with technical data manipulation to optimize infrastructures, map geospatial terrain profiles, and reveal insights hidden within complex datasets.
My experience spans leading multi-ton infrastructure design installations for government ministries, supervising mechanized farming deployments, and executing specialized agricultural field research in remote rural areas. With a passion for sustainable agriculture and data-driven decision making, I bridge the gap between traditional engineering and modern analytics.
When I'm not analyzing field data or designing infrastructure systems, I'm passionate about GIS mapping, sustainable farming technologies, and exploring new analytical frameworks.
📄 Download CVSupervised the comprehensive structural installation execution of major engineering infrastructures for the Ministry of Industry, Agriculture, and Co-operatives, implementing storage systems saving 18,000 bags of crop assets from post-harvest deterioration.
View Technical Documentation →Research Lead analyzing rural survey configurations across regional municipalities, producing data reports detailing operational bottlenecks to support localized technical development panels and sustainable farming practices.
View Research Profile →Multi-axis engineering training modules completed within intensive laboratory programs hosted at IIT Kharagpur, designing scalable sustainable modern tools for agricultural infrastructure and farm mechanization.
View Program Validation →Transitioning into data analytics with a focus on geospatial data, Python-driven analysis, and applied statistical modeling.
Specialized in management, organizational strategy, and business analytics.
Core foundation in agricultural infrastructure, irrigation systems, farm mechanization, and field engineering.
I'm always open to discussing new projects, analytical modeling ideas, or research workflows. Feel free to reach out!
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