Hello!

I'm Navid Tavakoli Shalmani

A Data Engineer & Environmental Data Specialist

My projects My Experience

Hello!

I'm a
Data Engineer based in Italy

Download My Resume

About

About Me

Passionate about using data, AI, and geospatial tools to create sustainable solutions.

  • Name: Navid Tavakoli Shalmani
  • Date of birth: May 01, 1988
  • Email: [email protected]
  • Phone: +39-388-378-7072

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EDUCATION

EDUCATION

My education combines fundamental sciences with engineering, providing me with a deep and comprehensive perspective to tackle complex technical and scientific challenges. This blend allows me to seamlessly integrate theoretical concepts with practical engineering applications.

2021 – 2024
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MSc in Environmental Engineering

Università di Bologna

Thesis Title:

Advanced Deep Learning Models for Urban Building Footprint Extraction and Renewable Energy Analysis

Developed deep learning models to extract building footprints from satellite imagery of Turin and Bologna, aiding urban planning and renewable energy analysis. achieving high accuracy and adaptability. Predicted rainfall and solar potential, automated footprint extraction, and refined municipal data via web scraping and data wrangling to enhance model precision.

2013 – 2016
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B.Sc. in Civil Engineering

University of Azad

Thesis Title:

Data-Driven Assessment of Building Performance for Sustainable Construction

Used Python and MATLAB to analyze building performance data, identifying trends in material efficiency and energy use to support sustainable design and optimize construction practices.

2007 – 2011
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B.Sc. in Computer Science

University of Guilan

Thesis Title:

Discrete Computational Models for Urban Growth: A Data Engineering Perspective

Built data workflows for preprocessing, transformation, and visualization, gaining solid foundations in data modeling, algorithm design, and computational analysis with applications relevant to data engineering.

Experiences

My experiences

Quick learner, eager to innovate, and skilled at turning complex data into impactful, sustainable outcomes.

2019-2021

Data Engineer – Environmental and Socioeconomic Analytics

RavisCo, Iran
  • Developed and maintained automated data pipelines and dashboards using Python, SQL, Tableau, and Excel for real-time business intelligence.
  • Integrated and analyzed environmental and socioeconomic datasets to support sustainable development.
  • Performed geospatial analysis to optimize ATM locations, improving accessibility by 15%.
  • Built predictive models for cash demand forecasting to enhance resource allocation accuracy.
2015-2018

Junior Data & Sustainability Engineer

Kolbe Construction Co, Iran
  • Analyzed environmental and construction data to support sustainable urban development.
  • Conducted GIS-based site assessments using satellite imagery.
  • Developed predictive models to optimize building energy efficiency based on smart home data.
2012-2013

Junior Data Analyst

GSS Co, Iran
  • Managed data entry and created dashboards with Excel and Tableau.
  • Conducted initial exploratory data analysis for marketing and sales teams.
April 2012 – September 2012

Data Analyst Intern

GSS Co, Iran
  • Assisted in data collection, cleaning, and visualization using Excel and Python.
  • Supported team with basic data analysis and report preparation.
2011 - 2012

Teaching Assistant

University of Guilan, Iran
  • Assisted in teaching computational mathematics courses, including MATLAB programming, Python basics, and numerical methods.
  • Supported students during lab sessions, clarified programming concepts, and graded assignments to enhance learning.

Certifications

My Certifications

I’m always eager to learn new skills and pursue certifications that expand my expertise and fuel innovative solutions.

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Data Analysis with R Programming
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Data Engineering Professional
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Applied Machine Learning: Foundations
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R Programming Basics for Data Science
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Decarbonising Hard-to-Abate Transport Modes
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Health and Safety Training
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Python Programming
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Getting Started with AI and Machine Learning
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Green Building Studio: Energy Analysis
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Revit Insight: Energy Analysis
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Sustainability for Design, Construction, and Manufacturing
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LEED Green Associate Prep
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BIM Foundations
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Green Building Concepts Foundations
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Introduction to ESG
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LCA Construction Bootcamp

Skills

My Skills

Strong analytical and problem-solving skills with proficiency in data science, geospatial tools, and programming. Quick learner with the ability to adapt to new technologies and deliver effective solutions.

Python

R Programming

MATLAB

SQL

Machine Learning

Deep Learning

Data Visualization (Tableau, matplotlib, seaborn)

QGIS / GIS

Remote Sensing / GDAL

SGems

Apache Spark

Apache Flink

Apache Kafka

Apache Airflow

Docker

Kubernetes

AWS Cloud

Grafana

Git & CI/CD (GitHub Actions)

Languages

My Languages

Proficiency levels in languages I speak.

English Flag English

C1 (Advanced)

Italian Flag Italian

A2 (Elementary)

Persian Flag Persian

Native

Project

My Projects

Developed and delivered diverse projects applying data engineering, machine learning, geospatial analysis, and computer vision, with practical implementations in environmental monitoring, urban planning, and sustainability.

TOP – Turin Open Platform

Turin Open Data Platform (TOP) is a real-world prototype of a smart city KPI dashboard. It is a project designed to demonstrate how Key Performance Indicators (KPIs) can empower smart cities. By collecting, cleaning, and visualizing near real-time data from multiple sources, this platform provides valuable insights into the urban environment of Turin, Italy.

🔗 Live Demo

GDPR-Aware Reddit Data ETL Workflow Implemented with Apache Airflow and PostgreSQL

This project implements an automated data pipeline using Apache Airflow to extract data from Reddit, store it as CSV files, transform and combine the data, and finally load it into PostgreSQL. The workflow is designed with GDPR-awareness, ensuring proper handling and archiving of raw and processed data.

Computer Vision Deep Learning DeepLabV3 ResNet Backbone for Image Segmentation

Applied deep learning models like DeepLabV3 with ResNet50 backbone to extract building footprints from satellite imagery for urban planning.

Geostatistical Modeling and-Environmental Data Analysis

Conducted thorough O3 density study in 5 European countries using EEA data. Analyzed with R Studio: distance calculations, variogram modeling (linear, spherical, Gaussian, exponential), model comparison via cross-validation. Optimal model chosen. Produced kriging maps in SGems.

Geospatial Data Preparation for Deep Learning

A collection of Python scripts for preprocessing and postprocessing geospatial imagery, designed to prepare satellite and aerial data for deep learning models. Includes tools for raster clipping, merging, tiling, CRS adjustment, format conversion, and vectorization of model outputs — bridging Remote Sensing and Computer Vision workflows.

COVID-19 Data Web Scraping and Analysis

Perform web scraping to extract a global COVID-19 dataset from a public Wikipedia page, followed by comprehensive data analysis tasks on the collected data.

Movie Library Desktop Application

Conducted thorough O3 density study in 5 European countries using EEA data. Analyzed with R Studio: distance calculations, variogram modeling (linear, spherical, Gaussian, exponential), model comparison via cross-validation. Optimal model chosen. Produced kriging maps in SGems.

Contact

Contact Me

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