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Vasilis Tsoukas

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Data Analyst
Data Scientist

Vasileios Tsoukas

Hi, I'm Vasilis, a Data Analyst and Scientist. Dedicated and analytical Analyst with strong foundation in data analysis techniques, data visualization, and statistical analysis. Well qualified with SQL and Python, detail-oriented and organized, with the ability to clean and transform data to derive meaningful insights. Proficient in tools such as Excel, Power BI and Tableau.

Transforming complex data into actionable insights. Specialized in machine learning, statistical analysis, and data visualization with 5 years of experience.

Looking to collaborate or explore how my skills can contribute to your team? Feel free to download my CV to learn more about my experience, projects, and expertise in data analysis and science. If you have any questions or would like to discuss opportunities, don't hesitate to contact me.
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What I Do

Data Analysis

I specialize in transforming complex datasets into actionable insights. Using tools like Python and SQL, I perform statistical analyses to identify trends, uncover patterns, and support data-driven decision-making.

Data Visualization

I create intuitive and interactive visualizations using tools like Tableau and Power BI. By presenting data visually, I help stakeholders quickly grasp complex information, identify trends, and make informed decisions. My visualizations turn numbers into stories that drive action.

Research

With a strong background in research methodologies, I conduct thorough investigations to solve problems and answer critical questions. I design experiments, collect and analyze data, and synthesize findings to contribute to the advancement of knowledge in the field.

Business Intelligence

I provide actionable business insights by integrating data from various sources and creating comprehensive dashboards. Utilizing key performance indicators (KPIs), I help organizations monitor progress, identify areas for improvement, and strategize effectively to meet their goals.

Professional Competencies and Industry Tools

Programming Languages

  • Python
  • SQL
  • Dart

Data Analysis & Visualization

  • Power BI
  • Tableau
  • SAS
  • Excel

Libraries

  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Plotly
  • SciPy

Industry Skills

  • Data Warehouses
  • ETL Processes
  • Bioinformatics
  • Health Statistics
  • Data Cleaning and Preparation
  • Data Modeling

Testimonials

Clients

Resume

5 Years of Experience

Education

2025

PHD IN MACHINE LEARNING & EDGE AI

Degree conferral pending (January 21st)

2018

MSC IN INFORMATICS AND COMPUTATIONAL BIOMEDICINE

Direction “Informatics with applications in Security, Big Data Management and Simulation”

2016

BSC IN INFORMATION TECHNOLOGY

Department of Information Technology and Telecommunications

Experience

June 2023 - November 2024
Dextera - Contract 16 Months

Researcher / Software Engineer

  • Conducted comprehensive healthcare systems analysis resulting in an implementation study, interoperability assessment, and publications including a peer-reviewed article and conference paper
  • Designed and implemented web-based healthcare platform integrating Tableau dashboard for dynamic data visualization and performance monitoring
  • Developed Python automation scripts for teleconsultation duration analysis, reducing manual processing time by 50%
October 2019 - October 2024
Intelligent Systems Laboratory

Researcher / Analyst

  • Research and Development in the field of Machine Learning for limited hardware
  • Developed machine learning models and web platforms for multiple National and Horizon-funded research projects

Projects

2024
GR Ministry of Health

GREECE’S NATIONAL TELEMEDICINE NETWORK

  • Utilized Python to analyze 30000+ healthcare records to identify key health trends and get insights on systems utilization
  • Implemented an end-to-end data warehouse using PostgreSQL with seamless data integration via RESTful APIs
  • Created robust ETL pipelines for automated data extraction, transformation, and loading
  • Applied Machine Learning to produce a model for calculating CO2 emission reduction with an accuracy of 78%
2023
Intelligent Systems Laboratory

RESEARCHERS REPOSITORY AND ANALYSIS

  • Extracted and analyzed data across 12 related research database tables using complex SQL queries and JOIN operations
  • Transformed and filtered data by using aggregating and filtering function to improve reporting process
  • Created a Dashboard by utilizing Power BI to identify key business intelligences that can improve researcher’s performance
  • Consulted with client to determine the best metrics to be displayed on final product
2022
EU and GR Research

INTELLIGENT DISTRIBUTION ROUTING SYSTEM (SMART DELIVERY)

  • Developed an algorithm combining Hopfield, routing optimization and ML to optimize fleet management and distribution
  • The final model could achieve a 25% of maximum distance saving and a 14% of overall delivery time saving
  • Created a Dashboard by utilizing Matplotlib, Seaborn, and Flask
  • Consulted with potential clients to determine the best metrics (KPIs) to be displayed on final product

Programming Languages

Python

95%

SQL

85%

Dart

80%

Data Analysis and Visualization

Power BI

85%

Tableau

70%

SAS

60%

Excel

85%

Industry Skills

Data Warehouse

85%

ETL Processes

80%

Cleaning and Preparation

95%

Data Modeling

85%

Soft Skills

Analytical Thinking

95%

Team Player

100%

Time management

100%

Portfolio

My Works
Tasks Management Dashboard

Tasks Management Dashboard

Media
Economic Crisis Dashboard

Economic Crisis Dashboard

Media
Financial Performance Dashboard

Financial Performance Dashboard

Media
Cardiovascular Health Dashboard

Cardiovascular Health Dashboard

Media
Covid-19 Dashboard

Covid-19 Dashboard

Media
Combined E-shop Dashboard

Combined E-shop Dashboard

Media

Publications

Scientific Publications
  • Tsoukas, V., Boumpa, E., Chioktour, V., Kalafati, M., Spathoulas, G., & Kakarountas, A. (2023). Development of a Dynamically Adaptable Routing System for Data Analytics Insights in Logistic Services. Analytics, 2(2), 328–345. https://doi.org/10.3390/analytics2020018
  • Tsoukas, V., Gkogkidis, A., & Kakarountas, A. (2023). Internet of Things Challenges and the Emerging Technology of TinyML. 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), 491–495. https://doi.org/10.1109/DCOSS-IoT58021.2023.00082
  • Giannakas, G., Sapounaki, M., Tsoukas, V., & Kakarountas, A. (2024). A Reward Modulated Spiked Timing Depended Plasticity inspired algorithm applied on a MultiLayer Perceptron. Proceedings of the 27th Pan-Hellenic Conference on Progress in Computing and Informatics, 42–47. https://doi.org/10.1145/3635059.3635066
  • Tsoukas, V., Gkogkidis, A., Boumpa, E., & Kakarountas, A. (2024). A Review on the emerging technology of TinyML. ACM Computing Surveys. https://doi.org/10.1145/3661820
  • Boumpa, E., Tsoukas, V., Gkogkidis, A., Spathoulas, G., & Kakarountas, A. (2022). Security and Privacy Concerns for Healthcare Wearable Devices and Emerging Alternative Approaches. In X. Gao, A. Jamalipour, & L. Guo (Eds.), Wireless Mobile Communication and Healthcare (pp. 19–38). Springer International Publishing. https://doi.org/10.1007/978-3-031-06368-8_2
  • Boumpa, E., Tsoukas, V., Chioktour, V., Kalafati, M., Spathoulas, G., & Kakarountas, A. (2023). Smart Delivery for Goods Exploiting ML Algorithms. Proceedings of the 26th Pan-Hellenic Conference on Informatics, 304–308. https://doi.org/10.1145/3575879.3576009
  • Tsoukas, V., Gkogkidis, A., Boumpa, E., Papafotikas, S., & Kakarountas, A. (2023). A Gas Leakage Detection Device Based on the Technology of TinyML †. Technologies, 11(2), 45. https://doi.org/10.3390/technologies11020045
  • Tsoukas, V., Gkogkidis, A., & Kakarountas, A. (2023). A TinyML-based System For Smart Agriculture. Proceedings of the 26th Pan-Hellenic Conference on Informatics, 207–212. https://doi.org/10.1145/3575879.3575994
  • Karageorgopoulou, A., Tsoukas, V., Spathoulas, G., Kakarountas, A., & Koziri, M. (2023). Porting the Paillier Algorithm for Homomorphic Encryption on Portable Devices. 2023 IEEE International Conference on Consumer Electronics (ICCE), 1–5. https://doi.org/10.1109/ICCE56470.2023.10043586
  • Boumpa, E., Tsoukas, V., Chioktour, V., Kalafati, M., Spathoulas, G., Kakarountas, A., Trivellas, P., Reklitis, P., & Malindretos, G. (2022). A Review of the Vehicle Routing Problem and the Current Routing Services in Smart Cities. Analytics, 2, 1–16. https://doi.org/10.3390/analytics2010001
  • Gkogkidis, A., Tsoukas, V., & Kakarountas, A. (2022). A TinyML-based Alcohol Impairment Detection System For Vehicle Accident Prevention. 2022 7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), 1–6. https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932962
  • Gkogkidis, A., Tsoukas, V., & Kakarountas, A. (2022). An Extended Instruction Set for Bioinformatics’ Multiple Sequence Alignment. Electronics, 11(16), 2550. https://doi.org/10.3390/electronics11162550
  • Gkogkidis, A., Tsoukas, V., Papafotikas, S., Boumpa, E., & Kakarountas, A. (2022). A TinyML-based system for gas leakage detection. 2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST), 1–5. https://doi.org/10.1109/MOCAST54814.2022.9837510
  • Tsoukas, V., Gkogkidis, A., & Kakarountas, A. (2022). Elements of TinyML on Constrained Resource Hardware. In M. Singh, V. Tyagi, P. K. Gupta, J. Flusser, & T. Ören (Eds.), Advances in Computing and Data Sciences (pp. 316–331). Springer International Publishing.
  • Tsoukas, V., Gkogkidis, A., Kampa, A., Spathoulas, G., & Kakarountas, A. (2022). Enhancing Food Supply Chain Security through the Use of Blockchain and TinyML. Information, 13(5), 213. https://doi.org/10.3390/info13050213
  • Tsoukas, V., Boumpa, E., Giannakas, G., & Kakarountas, A. (2021). A Review of Machine Learning and TinyML in Healthcare. 25th Pan-Hellenic Conference on Informatics, 69–73. https://doi.org/10.1145/3503823.3503836
  • Tsoukas, V., Gkogkidis, A., Kampa, A., Spathoulas, G., & Kakarountas, A. (2021). Blockchain technology in food supply chain: A state of the art. 2021 6th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), 1–8. https://doi.org/10.1109/SEEDA-CECNSM53056.2021.9566256
  • Tsoukas, V., Gkogkidis, A., & Kakarountas, A. (2020). A Survey on Mobile User Perceptions of Sensitive Data and Authentication Methods. 24th Pan-Hellenic Conference on Informatics, 346–349. https://doi.org/10.1145/3437120.3437337
  • Tsoukas, V., Kolomvatsos, K., Chioktour, V., & Kakarountas, A. (2019). A Comparative Assessment of Machine Learning Algorithms for Events Detection. 2019 4th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), 1–4. https://doi.org/10.1109/SEEDA-CECNSM.2019.8908366
  • Tsoukas, V., Kakarountas, A., Gkogkidis, A., & Giannakas, G. (2019). Multi-screen lock: visual passwords from user’s social data. Proceedings of the 23rd Pan-Hellenic Conference on Informatics, 90–95. https://doi.org/10.1145/3368640.3368657

Contact

Get in Touch

(+30) 694 76 00 484

Lamia, Greece

[email protected]

Available

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