ALIREZA ADLI

Languages: English, French, Persian

Programming Languages: Python, SQL, C++, MATLAB, LaTeX

Programming Skills: Object-Oriented Programming, Unit Testing, Logging, Monitoring, Data Structures and Types, Algorithmic Complexity, Database Management Systems, Containerization

Libraries: unittest, NumPy, Pandas, Matplotlib, Seaborn, TensorFlow, Pyomo, OpenCV, Scikit-learn, SciPy, PyQGIS

Tools: Git, Docker, REST API, Flask, FastAPI, ArcGIS, QGIS

Software Architecture: Microservices Architecture, Layered Architecture

• Developing research software projects using Python, consistently following OOP principles.
• Designing and implementing RESTful APIs.
• Developing documentation using LaTeX.
• Holding workshops on programming and presenting research software projects.
• Analyzing geospatial data to generate building LCA-related data using ArcGIS, QGIS, and PyQGIS.
• Supporting researchers with fast solutions to coding issues related to their projects.

• Teaching Python basics.
• Teaching System Dynamics modelling with Python and Vensim.
• Leading group brainstorming sessions and designing system maps, feedback loops, and stock-flow diagrams for class projects.
• Consulting students on designing and developing their projects.

• Teaching Python from basics to advanced topics, including data structures and algorithms, recursive functions, exceptions, file handling, special commands, OOP, and machine learning packages.

• Teaching Python and C++.

• Teaching MATLAB, Visual Basics, Academic English, and Image Processing.

• CityGISOO (Object-Oriented Geographic Information System for Cities) is a Python-based tool originally developed to automate the cleaning of geospatial data in Montreal.
• The project is being expanded to additional cities, starting with Quebec City, Calgary, and Saint John.
• Tools Used: Python, ArcGIS, QGIS, PyQGIS, GeoPandas

• Developing a modular software framework to evaluate carbon emissions in a sectorial and disaggregated manner, following clean architecture principles.
• The design enables easy extension to new sectors and regions through a standardized template.
• The initial implementation evaluates emissions in the building sector based on Life Cycle Assessment (LCA).
• Tools Used: Python, Docker, Git, VS Code, PyCharm, Flask, MySQL

• Analyzed and cleaned building footprint maps of the Greater Montreal Region (CMM) using mtl gis oo and ArcGIS, based on available map layers and LiDAR data (collaboration between NGCI and CMM).
• Tools Used: Python, mtl gis oo, PyQGIS, QGIS, ArcGIS, Git

• Developed a Python tool that abstracts PyQGIS functionalities for analyzing and cleaning building footprints in the City of Montreal.
• Tools Used: Python, QGIS, PyQGIS, GeoPandas

• Developed a full-stack project in collaboration with the Alan Turing Institute (UK) and University College London, using data for sustainable development.
• Tools Used: JavaScript, TypeScript, React, HTML, CSS, Mapbox, PostgreSQL

• Thesis on designing a software framework for evaluating carbon emissions in a district.
• Coursework: Principles of Systems Engineering, Urban Energy Systems, System Dynamics Modelling for Urban Development (all completed with grade 5/5).

• Master’s thesis in intelligent computing (MastersThesis Adli Alireza.pdf).