Curriculum Vitae
Education
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University of Thessaly
— October 2024 | today
PhD Candidate - Department of Computer Science and Biomedical Informatics
Thesis title: Supervised Dimensionality Reduction and
Classification with Convolutional Autoencoder Neural NetworksKnowledge Discovery through Novel Artificial Neural Networks Algorithms
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University of Thessaly
— September 2021 | February 2023
Master of Science in Informatics and Computational Biomedicine
— Overall Grade: 10/10
Dissertation title: Supervised Dimensionality Reduction and
Classification with Convolutional Autoencoder Neural Networks — Dissertation Grade: 10/10
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University of Thessaly
— September 2017 | July 2021
Bachelor of Science in Computer Science and Biomedical Informatics
— Overall Grade: 8.78/10
Dissertation title: Autoencoder Neural Networks for Image Clustering
— Dissertation Grade: 10/10
Experience
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Link Technologies S.A.
— Thessaloniki,
Greece
Artificial Intelligence Engineer — April, 2024 | December, 2024
Achievements:
- Engineered machine learning and deep learning pipelines for anomaly detection within vehicle fleet management systems.
- Implemented automated data workflows and streamlined model deployment using Apache Airflow and SQL Server.
- Conducted troubleshooting and optimization of existing algorithms to improve detection accuracy and system reliability.
- Tech Stack: SQL Server, Apache Airflow, BitBucket, Python (e.g. Numpy, Pandas, Scipy, matplotlib, pyOD and darts), Git and Github.
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Intelligent Systems Laboratory (iSL)
— Lamia,
Greece
Deep Learning Researcher — September, 2021 | October, 2023
Achievements:
- Conducted novel research on Deep Learning methodologies with a specialized focus on Deep Clustering algorithms.
- Published 4 scientific papers in eminent international journals and workshops, serving as the first author on two publications.
- Collaborated on grant writing proposals and presented detailed research findings and technical reports to supervisors.
- Tech Stack: Python (Numpy, Pandas, Scikit-learn, Matplotlib, Seaborn, PyTorch, Keras and Tensorflow), R (tidyr, dplyr plotly, ggplot, caret), Linux, Bash Scripting, Git and Github, Microsoft Excel, LaTeX.
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University of Thessaly
— Lamia, Greece
Developer of Deep Learning Methods — March, 2022 | August, 2022
Achievements:
- Served as a developer for the research project "Clustering Big Data", designing and implementing deep learning architectures for handling large-scale datasets.
- Executed rigorous experimental protocols to validate deep learning models, documenting results for scientific publication.
- Tech Stack: Python (Numpy, Pandas, Scikit-learn, Matplotlib, Seaborn, PyTorch Keras and Tensorflow), Linux, Bash Scripting, Git and Github, Microsoft Excel, LaTeX.
Scholarships
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2025:
Scholarship from the European Union-NextGeneration EU for implementing the project with title \textit{"Bridging big omics, genetics and medical data for the broad implementation of Precision Medicine in Greece"} (Grant Number: 7558).
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2022:
Scholarship from the University of Thessaly for implementing the project with the following title \textit{"Supporting the educational activities of the University of Thessaly through remedial teaching in addition to the main lectures for the academic year 2021-2022"} (Grant Number: 1010700). During this scholarship i participated as a teaching staff for the remedial teaching of the undergraduate subjects \textit{"Mathematical Analysis II"} and \textit{"Discrete Mathematics"} of the Department of Computer Science and Biomedical Informatics of the University of Thessaly.
Technical Skills
- Operating Systems: Linux and Windows Operating Systems.
- Programming Languages: C, Python, R, Java, Octave, MATLAB, Bash.
- Web Development Stack:HTML, CSS, JavaScript.
- Statistical Software: SPSS.
- Data Science, Visualization and Deep Learning Tools in Python:
PyTorch, Keras, Tensorflow, Numpy, Matplotlib, Seaborn, Pandas, Scikit-Learn.
- Data Science and Visualization Tools in R: tidyr, dplyr plotly,
ggplot, caret.
- Databases:
- Relational Database Management Systems: MySQL, SQL Server.
- Web frameworks: FastAPI, Spring Boot.
- Software Platform: Docker.
- Version Control Systems Git and Github, BitBucket.
- Document preparation: LaTeX~and MS Office.
Languages
- Greek: Fluent.
- English: Proficient level (C2 degree).