Senior Machine Learning Engineer 👨🏽‍💻 focusing on Bioinformatics 🧬

I've been coding since 2015. What pulled me toward bioinformatics was the sheer amount of biological data out there and how much ML can do with it. Today I build production AI systems in industry and research multi-modal AI for precision medicine in my PhD. I'm broadly interested in AI systems that are accurate, interpretable, and reliable enough for real clinical use.

• PhD in Computer Science · Bioinformatics & Multi-modal AI
  Ionian University, Corfu · 2025 – Present
  Thesis: "Advancing AI for Integrative Bioinformatics in Precision Medicine". Developing interpretable, scalable multi-modal AI that integrates medical imaging, clinical text, and omics data for clinical decision support, disease stratification, biomarker discovery, and personalized treatment. Supervised by Prof. Andreas Kanavos.

• Diploma (M.Eng) in Electrical & Computer Engineering
  National Technical University of Athens (NTUA) · 2015 – 2022
  GPA 9.11/10 (top 5%). Thesis: Machine & Deep Learning Classification and Visual Explanation of Dyslexia and Spelling Deficiency using fMRI data (GLM 1st Level Analysis, Atlas Analysis, Graph CNNs, Grad-CAM).

• Minor in Finance
  Deree, American College of Greece · 2017 – 2020
  GPA 3.82/4. Investments, Portfolio Management, Machine Learning. Stavros Niarchos Foundation scholarship.

• Summer Program: Foundations of Neuroscience
  Harvard University · 2021

• PhD Researcher · Ionian University · 2025 – Present
  Multi-modal AI for precision medicine: CNNs for medical imaging, transformers for clinical NLP, explainable AI (SHAP, Grad-CAM), and LLM + RAG systems over medical literature and omics databases.

• AI Researcher & Tech Consultant, Mental Health Projects · KLIMAKA NGO · 2025 – Present
  Building LLM-powered tools for suicide prevention and crisis response, including adaptive questionnaires developed with Laiko General Hospital for emergency clinical use. Built an internal AI platform (DSM-5 RAG chatbot, Whisper speech-to-text pipelines) and ensure sensitive data is handled securely and in line with GDPR.

• Machine Learning Research Assistant · Biomedical Research Foundation, Academy of Athens (BRFAA) · 2021
  ML/DL classification of Parkinson's disease on tabular data from the Greek Parkinson's Database. Under the supervision of Ioannis Michalopoulos, co-built an ML web tool for COVID-19 severity prediction.

• Data Science Intern · NCSR "Demokritos" · 2019
  Diagnostic classification of Alzheimer's disease from patient speech and text (LSTM, CNN, BERT).

• Senior Machine Learning Engineer · Grid Dynamics, Kraków · 2025 – Present
  Architecting production ML systems across the full lifecycle on GCP/AWS. Built an end-to-end robotic inspection system on the Wandelbots NOVA platform (SAM3, FoundationPose, DINOv2), reaching 0.44 mm average error in lab conditions. Delivering LLM features, RAG pipelines, and semantic search, plus mentoring and code reviews.

• Data Scientist, Compliance Analytics · HSBC, Kraków · 2024 – 2025
  Led analytics across investigations, transaction monitoring, and financial crime. Built 3 internal tools, implemented RAG architectures for compliance analytics, and presented ML work at Kraków University of Economics and HSBC Summer School.

• Automation Specialist, Advanced Data Analytics · Uber, Kraków · 2021 – 2024
  Delivered 25+ automation and data science projects (real-time and batch) across EMEA, including NLP on driver feedback and restaurant churn prediction. Started as a Local Operations Intern (Data Analytics) in 2021.

My research has resulted in three peer-reviewed publications and one manuscript currently under review.

• Adaptive LLM-Generated Questionnaires for Suicide Risk Assessment: A Clinical Pilot in Greece
  D. Georgiou, A. Makrigiannis, V. Gerogiannis & A. Kanavos
  2nd NICE TEAS EUROPE Conference, 2026

• Explainable Analysis of High-Confidence Glioma–Meningioma Misclassification in Brain MRI
  P. Mintsopoulos, D. Georgiou & A. Kanavos
  GeNeDIS 2026, Athens · Under review

• A Generalization of Multi-Source Fusion-Based Framework to Stock Selection
  D. Georgiou, V. Snášel & J. D. Velásquez
  Information Fusion, Elsevier, 2024 · Elsevier Link · Ranking Q1

• A Machine-Learning-Based Web Tool for the Severity Prediction of COVID-19
  A. Christodoulou, M. S. Katsarou, C. Emmanouil, M. Gavrielatos, D. Georgiou & I. Michalopoulos
  BioTech, MDPI, 2024 · MDPI Link

• LLM-Powered Pipeline for Post-Call Analysis of Suicide Crisis Hotline Recordings
  34th Panhellenic Psychiatry Congress, Alexandroupoli, 2026 · Poster

• Machine & Deep Learning for Parkinson's Disease Classification
  6th HBP Student Conference on Interdisciplinary Brain Research, 2021 · Poster

• 1st Place Worldwide · BR4N.IO Hackathon × IEEE SMC 2025, Vienna (Data Analysis track, 69 teams, 50+ countries)
• 2nd Place Nationwide · EIT Health i-Days 2025 (HygeIA, AI-powered first-aid app with a Greek LLM)
• Top 4% Worldwide · IEEEXtreme 13.0 (159th of 4,103 teams)

My goal is to combine machine learning engineering, bioinformatics, and applied research to deliver AI systems with real clinical and business impact. I'm especially interested in multi-modal AI, explainable AI, clinical NLP, genomics, and medical imaging.

🌍 Based in Kraków, Poland 🇵🇱 · 🤝 Open to collaborating on ML and AI projects