I am a doctoral researcher in astrophysics with a strong background in data science and machine learning, currently working at the Institute of Astrophysics in Crete. My academic background includes a BSc in Physics from the Aristotle University of Thessaloniki, an MSc in Astrophysics from the University of Bonn, and an upcoming PhD defense (summer 2025) from the University of Crete. To broaden my technical expertise, I am also pursuing a second MSc in Data Science & Machine Learning from the Hellenic Open University, expected to graduate in 2026.Over the years, I’ve led multiple international projects, collaborating with scientists across Europe and contributing to high-impact research publications. My work has ranged from proposing innovative mechanisms for supernova formation to analyzing decades of gravitational wave data, and I bring extensive experience in Python, numerical modeling, and data visualization.In my current role, I develop numerical models to simulate the evolution of massive stars, working with diverse datasets and employing advanced techniques like generative adversarial networks for data augmentation. I also excel at translating complex findings for both technical and non-technical audiences, drawing on my experience as a course instructor and assistant lecturer.Driven by a passion for problem-solving and a deep understanding of astrophysical phenomena, I am now looking to transition from academia to industry. My goal is to leverage my data science and machine learning skills in a dynamic tech environment, continually expanding my knowledge while making an impact through innovative research and development.As an active member of professional societies such as the Hellenic Astronomical Society, European Astronomical Society, and International Astrostatistics Association, I remain engaged with both the astrophysics and data science communities, eager to contribute to cutting-edge developments in both fields.