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Data Science · ML · AI · Research Software

Mohinur Yusufjanova builds data systems for research and real-world decisions.

I'm Mohinur Yusufjanova, a Master's student in Data Science at Colorado School of Mines. I build reproducible data workflows, machine learning models, geospatial analyses, and research pipelines that turn messy real-world data into structured insight.

Data ScienceMachine LearningAI ResearchResearch SoftwareSoftware Engineering
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MS Data Science

Colorado School of Mines, GPA 3.9, expected May 2027.

Research Data Pipelines

OCR, web scraping, validation, and dataset development for historical records.

Geospatial Analytics

GeoPandas, QGIS, raster processing, spatial joins, and suitability modeling.

ML + Reproducibility

Python, SQL, model evaluation, technical documentation, and Git workflows.

Featured Work

Projects that show the work behind the keywords.

These projects focus on geospatial analysis, OCR, data mining, research workflows, and practical systems for turning complex data into usable outputs.

View all projects
GeospatialCompleted

April 2026

Solar Energy Site Suitability Analysis

Geospatial decision support for renewable energy planning

A reproducible geospatial suitability model for identifying candidate utility-scale solar locations across Colorado using environmental, infrastructure, and land-use datasets.

Why it matters: Shows applied geospatial modeling, multi-source data integration, and decision-support communication for energy planning.
  • Integrated land use, elevation, protected lands, solar resource, and transmission data.
  • Applied spatial joins, buffering, coordinate transformations, and multi-criteria scoring.
  • Generated maps and visual outputs for energy planning workflows.

Evidence

Suitability scoring workflow
Map outputs
Documented GIS data sources
PythonGeoPandasShapelyPyProjQGISSpatial Analysis
Links coming after repository cleanup
Research ToolsCompleted

April 2026

Historical Economic Geology Education Atlas

Spatiotemporal mapping of academic programs

A geospatial research dataset and visualization workflow showing how economic geology education expanded across U.S. universities over time.

Why it matters: Connects archival data processing with spatial analysis, showing research judgment and technical implementation.
  • Geocoded institutional records and organized historical academic program data.
  • Combined OCR, information extraction, and spatial analytics workflows.
  • Built interactive visualizations for historical and educational research.

Evidence

Geocoded institution dataset
Spatiotemporal visualizations
Reproducible notebooks
PythonGeoPandasOCRGeocodingData Visualization
Links coming after repository cleanup
Data MiningIn Progress

June 2026

University Course Catalog Mining Pipeline

OCR and data extraction for archival research

An end-to-end Python pipeline for discovering, processing, validating, and analyzing historical university course catalogs at research scale.

Why it matters: Demonstrates research software engineering: automation, validation, documentation, and structured dataset creation from messy records.
  • Automated catalog discovery, OCR, information extraction, and validation.
  • Built structured datasets from large collections of archival records.
  • Documented reproducible workflows for downstream research analysis.

Evidence

Before/after OCR examples
Validation reports
Structured CSV or SQL outputs
PythonSQLWeb ScrapingOCRPDF ProcessingETL
Links coming after repository cleanup

Technical Skills

A practical toolkit for data, models, maps, and research workflows.

Recruiter keyword match

ML model evaluationResearch data pipelinesGeospatial decision supportOCR and information extractionReproducible Python workflows

Programming & Data Science

PythonSQLRJavaScriptNumPySciPyPandasJupyter Notebook

Machine Learning & Modeling

Scikit-learnTensorFlowPyTorchClassificationFeature EngineeringModel EvaluationStatistical LearningPredictive Modeling

Geospatial Analysis & GIS

GeoPandasShapelyPyProjQGISGDALRasterioSpatial JoinsRaster ProcessingGeospatial Visualization

Data Engineering & Research Tools

Web ScrapingOCRETL PipelinesData ValidationInformation ExtractionPDF ProcessingDataset Development

Software & Workflow

GitGitHubLinuxBashVS CodeTechnical DocumentationReproducible Research

Experience

Research and teaching work with real technical responsibility.

Research Assistant - AI & Data Mining

Colorado School of Mines

Supporting a research project on the history of economic geology education across U.S. universities through Python-based data mining and archival processing workflows.

PythonOCRWeb ScrapingInformation ExtractionData Validation

Summer 2026 - Present

  • Develop Python workflows to locate, collect, process, and structure historical course catalogs.
  • Apply web scraping, OCR, information extraction, and data mining to build research datasets.
  • Extract, validate, and organize course information from archival records for downstream analysis.
  • Maintain reproducible pipelines, datasets, and documentation for ongoing research.

Graduate Teaching Assistant - Advanced Data Science / Computer Science

Colorado School of Mines

Reviewed technical projects and supported students working through data science, machine learning, and computer science concepts.

Machine LearningStatisticsCode ReviewTechnical Communication

January 2026 - May 2026

  • Reviewed graduate-level projects focused on data analysis, machine learning, and statistical modeling.
  • Provided feedback on data preparation, model evaluation, and analytical approaches.
  • Helped students troubleshoot technical challenges and communicate technical ideas clearly.

About

I like the part where messy information becomes useful.

I'm a data science graduate student at Colorado School of Mines with a background in Business Administration and Marketing. That combination shapes how I approach technical work: I care about building models and pipelines, but also about making data understandable and connected to real decisions.

My current work focuses on data science, geospatial analysis, machine learning, and research software. As a research assistant, I build Python workflows to discover, process, and extract information from historical course catalogs using web scraping, OCR, information extraction, validation, and dataset development.

I'm interested in roles where I can use data science, machine learning, AI, and software engineering to solve real problems, support better decision-making, and build systems that make complex data easier to use.

Contact

Let's connect about data science, ML, AI, research, or software roles.

I'm interested in opportunities where I can work with real-world data, build reproducible systems, and turn complex information into useful insights.

mohinur_yusufjanova@mines.eduLinkedInGitHub
Fort Collins, CO