Vasilis Papagrigoriou

Data Scientist

https://talent.gravityer.com/vasilis-papagrigoriou

MSc Artificial Intelligence & BSc Informatics & Telecommunications

Rhodes, Greece

Key Strengths

Demonstrated interest in Machine Learning and Computer Vision through multiple personal projects (CVML-ConvNN-MMVS, CVML-UMVS, TicTacToeDeepQRL, MLEx4-Bayesian-Learning).
Experience with Python, a core language for Data Science.
Exposure to deep learning frameworks (PyTorch implied by TicTacToeDeepQRL).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and academic in nature, indicating a strong drive for self-learning and exploration. However, the diversity of projects (web development, agents, ML) suggests a broad interest rather than a focused alignment with a specific industry or team culture. The lack of professional experience or team projects makes it difficult to assess collaboration or cultural adaptability.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Projects

vasilispapg

December 3, 2025 – Present

vasilispapg — Dev.to repository

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PhyloFlask

November 22, 2024 – Present

PhyloFlask — a software framework for large-scale phylogenetic profile visualization.

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DEEPNN-RL-ASSIGN3

June 2, 2024 – June 2, 2024

DEEPNN-RL-ASSIGN3 — Dev.to repository

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CVML-GCI

April 28, 2024 – November 26, 2024

CVML-GCI — Dev.to repository

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SmartCity-JADE-Agents

April 22, 2024 – June 16, 2024

SmartCity-JADE-Agents — Dev.to repository

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CVML-ConvNN-MMVS

March 9, 2024 – November 21, 2024

Applications of Convolutional Neural Networks on Multi-modal Video Summarization

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MLEx4-Bayesian-Learning

February 1, 2024 – February 1, 2024

MLEx4-Bayesian-Learning — Dev.to repository

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TicTacToeDeepQRL

January 31, 2024 – January 31, 2024

Tic-Tac-Toe DeepQRL: A Reinforcement Learning based Tic-Tac-Toe game using PyTorch and Tkinter. Features DQN agents that learn, play, and evolve strategies over time, visualized through a responsive GUI.

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CVML-UMVS

November 13, 2023 – March 11, 2024

Unsupervised Multi-Modal Video Summarization is a cutting-edge project that stands at the intersection of computer vision and machine learning. Its primary aim is to automate the process of condensing lengthy videos into succinct summaries without the need for pre-labeled training data.

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Karate-Website

April 20, 2021 – July 28, 2021

Website for Karate for a demo project. -Homepage -Login/Signup page -Quizs -Profile -Tracking scores

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Key Strengths

Demonstrated interest in Machine Learning and Computer Vision through multiple personal projects (CVML-ConvNN-MMVS, CVML-UMVS, TicTacToeDeepQRL, MLEx4-Bayesian-Learning).
Experience with Python, a core language for Data Science.
Exposure to deep learning frameworks (PyTorch implied by TicTacToeDeepQRL).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

Vasilis Papagrigoriou

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit