Cybernetics and Artificial Intelligence Lab
Department of Business Administration
National and Kapodistrian University of Athens
Welcome to the Cybernetics and
Artificial Intelligence Laboratory
Welcome to the Cybernetics and Artificial Intelligence Laboratory, established at the Department of Business Administration of the National and Kapodistrian University of Athens. The lab is headed by Professor Dimitrios Thomakos. The lab aims to do research that can be published in top venues. Our research uses tools and methods of Artificial Intelligence, and lies in the following areas:
- Forecasting
- Decision making
- Cyber security
- Finance
We are always looking forward to collaborating with exceptional students! Thus, please, if you are interested in our projects, please do not hesitate to contact us.

Values: Foundations in Interdisciplinary Excellence
Our laboratory is rooted in the synergy between cybernetics-the science of communication and control in systems-and artificial intelligence. We uphold:

Mission: Advancing Intelligent Systems for Societal Good
Our laboratory exists to pioneer innovations that harmonize theoretical depth with real-world impact.

Vision: A Future of Symbiotic Intelligence
We envision a world where AI and cybernetic systems empower humanity to tackle existential challenges while preserving dignity and diversity.
Foundations of AI

AI Through the Ages: A 50-Word Journey
March 16, 2020
Artificial Intelligence emerged in the 1950s with early logic-based programs. The 1980s saw the rise of machine learning using decision trees. The field revolutionized in the 2010s with neural networks and backpropagation. Today, transformers and reinforcement learning dominate, powering breakthroughs from robotics to drug discovery. AI continues evolving at an unprecedented pace.

AI Ethics: Privacy, Bias, and Accountability
May 19, 2025
The ethics of artificial intelligence concerns the responsible development and use of AI, with respect for privacy, transparency, and human rights. It raises questions about bias, autonomy, and accountability, aiming to balance technological advancement with social responsibility.
AI in Education

How AI Transforms Numerical Computation: Smarter Algorithms, Faster Results
May 19, 2025
Artificial intelligence and numerical computation combine to solve complex problems with greater accuracy and speed. Through algorithms and models, AI optimizes mathematical approaches, enhancing applications in fields such as finance, physics, and engineering.

AI in Forecasting: Boosting Accuracy and Efficiency with Machine Learning
May 19, 2025
Artificial intelligence in forecasting enhances accuracy and efficiency in data analysis. Using machine learning algorithms, it enables pattern recognition and the generation of more reliable predictions in areas such as economics, weather, and market demand.

AI in Finance: Revolutionizing Risk Prediction, Fraud Detection, and Transaction Automation
May 19, 2025
Artificial intelligence in the financial sector is transforming traditional processes by dramatically improving risk prediction, streamlining transaction automation, and effectively detecting fraud. Machine learning algorithms deliver unmatched precision, blazing speed, and enhanced decision-making, driving unprecedented efficiency in finance.

AI-Powered Decision Making: Faster Insights, Smarter Choices
May 19, 2025
Artificial intelligence revolutionizes decision-making by analyzing data and synthesizing information for faster, smarter choices. Advanced algorithms reduce uncertainty while optimizing strategies across business, healthcare, and finance. This transformative technology also adapts to dynamic environments, continuously improving outcomes through machine learning.
ΑΙ Large Language Models

May 19, 2025
LLMs are cutting-edge AI systems trained on vast text datasets to process and generate human-like language. They enable revolutionary applications in translation, content creation, education, and customer service, dramatically enhancing human-computer interaction.
However, these models face challenges: they sometimes generate inaccurate or biased content, reflecting limitations in their training data. Their rapid advancement raises ethical concerns about misinformation, privacy, and societal impact.
Despite these issues, LLMs offer tremendous potential to boost productivity and accessibility across industries. The key lies in developing them responsibly—improving accuracy, reducing biases, and implementing safeguards. As they evolve, LLMs will continue redefining technology's role in our lives, but their deployment requires careful oversight to ensure beneficial and fair outcomes for society.












