Education

My academic background starts with rigorous computer-science and engineering foundations, then moves toward more research-oriented work on modern AI systems: agents, robotics, biomedical AI, multimodal learning and reliable model evaluation.

University of California, Berkeley

UC Berkeley is one of the leading universities for computer science and machine learning in the United States. My work there was more research-oriented, centered on modern AI systems at the boundary between agents, robotics and biomedical AI.

The central question was how intelligent systems can reason from imperfect evidence, interact with people or physical environments and still remain measurable enough to trust.

This connects directly to my broader research interests: multi-agent workflows, robotics and human-machine interaction, biomedical AI and evaluation methods for systems whose behavior unfolds over time.

Biomedical data science was one concrete setting within a wider research space that included transformers, agents, robotics, multimodal evidence and reliable evaluation under uncertainty.

Academic Work

Core areas

  • AI agents and multi-agent systems
  • Robotics and human-machine interaction
  • Biomedical AI and biomedical data science
  • Transformers, LLMs and multimodal learning
  • Model evaluation and reliable machine learning

Academic work

  • Moved into a more research-centered phase of my academic work. The emphasis was on open-ended questions in modern AI beyond standard coursework and implementation.
  • Studied AI systems that do more than classify static data: systems that reason, interact, coordinate, adapt to uncertainty and support decisions in real settings.
  • Connected agentic AI, robotics and biomedical applications through a common interest in reliability, evidence, evaluation and useful behavior under uncertainty.

Awards

  • Merit scholarship for top academic performance

National Technical University of Athens

The National Technical University of Athens is Greece's historic technical university and the country's top computer-science school. It has a particularly strong tradition in electrical engineering, computer engineering and applied mathematics.

The NTUA degree gave me the full computer-science base: algorithms, data structures, computational complexity, databases, systems and software engineering.

The specialization was closer to intelligent systems and applied mathematics: computer vision, robotics, control systems, optimization and the continuous models used to describe movement, signals and physical systems.

The work on financial language and anomaly prediction connected natural language processing, structured records and statistical pattern detection. It reflected an early interest in using machine learning to identify structure in complex operational data.

Academic Work

Core areas

  • Core computer science: algorithms, data structures and computational complexity
  • Software engineering, databases and computer systems
  • Artificial intelligence, machine learning and data mining
  • Computer vision, robotics and control systems
  • Applied mathematics, optimization and continuous modeling

Academic work

  • Built a broad computer-science foundation before specializing toward AI, vision, robotics and applied mathematics.
  • Developed the continuous-mathematics intuition behind robotics and control: optimization, dynamical systems, signals and model-based reasoning.
  • Connected natural language processing with financial data and anomaly prediction, reflecting an early interest in financial systems and machine learning for structured operational signals.

Awards

  • Papakyriakopoulos award for mathematics performance
  • Eurobank award for top 0.1% high-school performance in national university entrance exams across advanced mathematics, physics, programming, business and writing