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Hi there šŸ‘‹, my name is Sambadi

Geospatial Data Scientist

Biostatistician and Data Scientist

I am a Geospatial Data Scientist with a passion for unveiling the stories told by data within the realms of ecology, climate change, environmental security, and agriculture. I've been extremely fortunate to have worked at several prestigious organizations, including the Global Water Security Center, NASA, Bayer, and Becton Dickinson and Company, where I've harnessed data science to answer pertinent questions in climate change, sustainable agriculture, biodiversity conservation, and climate change mitigation.

Skills: R/Python/Data Science/Ecology/GIS

  • šŸ”­ Iā€™m currently working on projects pertaining to Environmental Security and Climate Change.
  • šŸŒ± Iā€™m currently learning Spatial Statistics, working with APIs and SQL
  • šŸ‘Æ Iā€™m looking to collaborate on Data Science Projects
  • šŸ¤” Iā€™m looking for help with expanding my current knowledge about model deployment and working with APIs as well as databases
  • šŸ“« How to reach me: [email protected]
  • šŸ˜„ Pronouns: He/him/his
  • āš” Fun fact: I share my birthday with Jennifer Lawrence, Ben Affleck and the day of Indian Independence. I am also semi-professional musician and I enjoy composing instrumental rock and metal music.

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Sambadi Majumder's Projects

applying-xai-approaches-to-ecology icon applying-xai-approaches-to-ecology

"šŸŒæ A comprehensive repository dedicated to applying eXplainable Artificial Intelligence (XAI) in ecology. Dive into interpretable machine learning techniques to assess intraspecific trait variations and explore datasets, visualizations, and more. šŸ“ŠšŸŒšŸ“ˆ"

auraldatasuite icon auraldatasuite

Data Sonification Meets Music: A symphonic blend of data-driven sounds with inspired musical compositions.

chronoclimatehub icon chronoclimatehub

An interactive visualization platform showcasing timelapse videos of global climate shifts. Dive into captivating visuals that chronicle changes in temperature, precipitation, desertification, air pollution, and more. Witness the evolving narrative of our planet, one frame at a time.

enviroinfer-sundarbans icon enviroinfer-sundarbans

Utilizing Interpretable Machine Learning to Analyze and Assess the Environmental Factors Affecting Vegetation Health in the Sundarbans Mangrove Forest.

georflow icon georflow

Effortlessly handles geospatial data with geoRFlow, your comprehensive R package for geospatial tasks. For data import and quality checks using workflow automation.

geovizhub icon geovizhub

"A hub for innovative geospatial data visualizations using Python and R. Explore, analyze, and visualize geographical data in an interactive and intuitive manner."

inventory icon inventory

This repository is a curated collection of R functions developed by Sambadi Majumder. This serves as a comprehensive inventory of functions, catering to various domains.

machinelearningfunctionaltraitdivergence icon machinelearningfunctionaltraitdivergence

This repository is dedicated to the study of functional trait divergence using machine learning methodologies. It encompasses datasets, code, tables, and visual representations pertinent to the research.

pyearthly icon pyearthly

"pyearthly effortlessly handles geospatial data, especially in in the context of data import and quality checks using workflow automation."

spatialdatachronicles icon spatialdatachronicles

Explore the realm of spatial data with Sam through the Spatial Data Chronicles portfolio website. This repository hosts all essential files to navigate the journey, sharing insights and projects on GIS, remote sensing, and spatial analysis.

yield_forecast_sunflowers icon yield_forecast_sunflowers

This repository contains code and data for analyzing sunflower agricultural yield in the US for identifying specific climate variables and thresholds that influence yield using interpretable ML approaches as well as to forecast future county-wide yield across three future timeframes.

yieldscapeusa icon yieldscapeusa

About YieldScape USA is a dynamic, user-driven dashboard enabling the visualization of crop yield data across the US. By uploading a tailored RDS file, users can explore yearly yield variations at national, state, and county levels through an interactive, full-screen map.

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