Ebrahim Jahanshiri Email & Phone Number

Gothenburg, SE

Cambridge, England, United Kingdom

• Developed a database for more than 500 agronomic studies that were published across European agroclimatic zones from 1972 to 2022: https://zenodo.org/records/8406516
• Developed a crop model to assess the potential of Proso millet as a climate-resilient crop for sustainable diversification. https://zenodo.org/records/7456224
• Developed a Global knowledge base for agricultural diversification with MYSQL, PHP on Google Cloud Platform (GCP): https://github.com/geoej/RADIANT-DB
• AiSQLQury: an Retrieval Augmented Generation (RAG) based Large Language Model (LLM) extension for domain specific data augmentation: https://github.com/geoej/AiSQLquery
• MlOps: end-to-end model production with MLflow and DVC deployment: https://github.com/geoej/EndtoEndDVC

All things data science, developed innovative solutions, as showcased in projects like AgroLingua and LandSupport, while actively contributing to the field through publications and presentations.

Kuala Lumpur, Federal Territory Of Kuala Lumpur, Malaysia

• Developed R code to compare specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property: http://psasir.upm.edu.my/id/eprint/60054
• Developed a spatial regression techniques for prediction of house property values.
• Developed PFMap macro creates continuous availability and application maps for precision farming. A stand-alone ArcGIS macro developed with ArcObjects and VBA.
• Participated in the development of Hyperspectral analysis of oil palm fruit project that to 2 patents.
• Developed a comprehensive review of spatial analysis of Property sales. The published paper has received more than 100 citation: https://core.ac.uk/download/pdf/153802057.pdf
• Developed Shiny PFMap software, soil mapper using R statistical libraries https://geoprocessing.shinyapps.io/geoprocessing/ data for testing the App: http://b.link/a69

Chelmsford, England, United Kingdom

• Awarded “Realising Dynamic Value Chains for Underutilised Crops (RADIANT) - HORIZON 2020 SFS-01-2020”. H2020 European Union. Granted 220,000 Euros. https://www.radiantproject.eu
• Developed a multistage suitability assessment based on available data at local, regional and global level (SQL database, Google Earth Engine, local meteorological and prices datasets) to provide initial evidence for.
• Developed an analysis framework for diversification in the United Kingdom, considering climate, soil, economics, and market demand. API database of 2700 crops, combined GIS and data mining to determine the most.
• Developed a data-driven approach for shortlisting underutilized crops (UCs) for sustainable agricultural diversification across Italy: https://www.mdpi.com/2073-4395/12/7/1636
• Quantified the fitness of global datasets for forest Loss quantification in Amazonia based on R and Google Earth Engine: https://github.com/geoej/ForestLossDatasets/
• Carried out spatial suitability analysis of bambara groundnut in China using stochastic environmental research and risk assessment, sub-daily swat models, cluster analysis, economic data, climate data, soil data, crop.

Gothenburg, Vastra Gotaland County, Sweden

Utilised the Spatial Generative Adversarial Neural Networks (SpaceGAN) and machine learning models to predict soil properties at unsampled areas (due to high cost). The results show that this method can improve the accuracy of soil information.- Spatial Generative Adversarial Networks (SpaceGANs)- Data mining from published resources- Machine learning.

Crops For The Future

• Awarded EUR 290,000 for the project: “Development of Integrated Web-Based Land Decision Support System Aiming Towards the Implementation of Policies for Agriculture and Environment”..
• Lead a team of 24 data specialists, and software developers to develop CropBASE suite of Apps for agricultural diversification: https://www.cropbase.co.uk
• Crop suitability mapperhttps://www.cropbase.co.uk/src/cropgrids/cropgrids.php
• AssessCrop: the first evidence-base for new products and their nutrition from underutilised crops:https://cropbase.co.uk/src/assesscrop/assesscrop/product_compare.php
• Developed a Global Knowledge Base for agricultural diversification: https://cropbase.co.uk/cropbasev5/
• Utilised Support Vector Machines algorithm for the economic feasibility assessment of underutilised crops: https://www.sciencedirect.com/science/article/abs/pii/S0168169918306665

Crops For The Future

• Developed a suite of software and tools for diversification of agriculture for more than 10,000 farmers in South East Asia.
• A Nutrition Security Tool demonstrating the importance of Underutilised Food Crops for Sustainable Nutrition Security https://geoprocessing.shinyapps.io/underutilised/
• DSSAT-INPUT: an online DSSAT-compatible crop modelling input generatorhttps://geoprocessing.shinyapps.io/DSSAT-INPUT-Shiny/
• Developed Data frameworks for linking data across different disciplines: https://www.myfoodresearch.com/uploads/8/4/8/5/84855864/_4__fr-2018-104.r1_nur_marahaini.pdf

• Graduate research fellowship funded by The Malaysian Centre of Remote Sensing (MACRES)
• Developed a complete algorithm for geostatistical analysis and mapping that would reduce the number of samples required for mapping by 70%:https://link.springer.com/article/10.1007/s12517-015-1912-6
• Developed object-oriented approach for image segmentation using LandSat data (UGSS)
• Granted RM 135,000 (Ringgit Malaysia). “Developing a cellular automata-based planning decision support system” (01-01-04-SF0979), Ministry of Science, Technology and Innovation

Singapore

• Developed a metadata system for remote sensing data fusion for "Land-use Land-cover Change and Its Environmental Consequences in Southeast Asia" project
• Transcribed records for the project: "Effects of clearance and fragmentation on forest compositional change and recovery after 200 years in western New York"
• Conducted literature search for the project "land-use land-cover change research explored using self-organizing map"

• Recruited qualified and talented candidates
• Processed payroll
• Managed employee performance and disciplinary.
• Update documentation and policies
• Maintained employee records
• Managed finances and benefits

Overseeing the Filteration and screening in seed tomato farms and controlling quality of the seeds separated in the tomato paste plants being a contracting party to the Company.

• Software and hardware troubleshooting (operating systems: Windows, Linux and Mac)
• Network maintenance, printing and email setup
• Training students and researchers for Microsoft Office (Word, Excel, Powerpoint, Operating systems and Visual Basic)
• Teaching Visual Basic for programming to students

• Student assistant for data collection and analysis
• Aiding research projects: design of experiments, field and laboratory data collection, data entry
• Carried out statistical data analysis, hypothesis testing and inferences

Master'S, Applied Data Science, A

Courses: • Python for Data Scientists • Statistical Methods for Data Science • Applied Mathematical Thinking, Master course • Data.

Phd, Gis And Geomatics Engineering

Activities and Societies: Took courses in statistics and geospatial modelling. Thesis project was on testing spatio-temporal regression.

Master'S, Precision Farming

Data analytics in the field of geographic information science as they relate to farming. Optimised a method of statistical representative.

Bachelor'S, Agricultural Engineering