Short CV

Vasileios Kochliaridis is a Computer Engineering and Informatics graduate from the Polytechnic School of the University of Ioannina, having completed his degree in 2021. He completed his PhD in 2026, entitled “Deep Learning Methods for Sequential Decision-Making in Dynamic Systems,” under the supervision of Prof. Ioannis Vlahavas. Since 2021, he has been a member of the Intelligent Systems Lab (ISL). His research focuses on the use of Machine Learning and Deep Learning methods for decision-making in dynamic and uncertain environments. In finance, he has studied deep reinforcement learning algorithms for trading in cryptocurrency markets. In autonomous vehicles, he has developed learning-based methods for end-to-end driving and adaptation to realistic conditions. In robotics, he has worked on learning-based control and manipulation systems for robotic hands. In dynamic systems modeling, he has applied Physics-Informed Neural Networks for the approximation and analysis of physical processes. He has also worked on the use of GANs for synthetic data generation, aiming to support the training and evaluation of machine learning models.

Research Interests

Deep Learning Architectures
Deep Reinforcement Learning Algorithms
Decision-Making in Dynamic Systems
Intelligent Agents
Generative Adversarial Networks (GANs)
Computer Vision
Autonomous Vehicles
Finance & AI
Physical Simulations
Robotics

Journal Publications

Learning with technical analysis and trend monitoring on cryptocurrency markets, Neural Computing with Applications, Springer, volume 35, pages 21445–21462, (2023)
V.Kochliaridis, A. Papadopoulou, I.Vlahavas, UNSURE – A Machine Learning Approach to Cryptocurrency Trading, Applied Intelligence, Springer, volume 54, pages 5688–5710, (2024)
V.Kochliaridis, I.Dilmperis, A.Palaskos, I.Vlahavas, GPS: A Generative Point Sampling Apporach for PINNs,, Engineering with Computers, Springer, pages 1-21, (2025)
V.Kochliaridis, N.Chandrinos, G.Parlitsis, I.Vlahavas, NADAS – Noise-Adaptive Driving Assistance System, Control Engineering Practice
V.Kochliaridis, I.Vlahavas, “Optimizing Pretrained Autonomous Driving Models using Deep Reinforcement Learning”, Applied Sciences, MDPI, Special Issue in Innovative Artificial Intelligence Methods, Tools and Methodologies to Address Challenging Real-World Problems, (2025)

Conference Publications

Vasilis Kochliaridis, Eleftherios Kouloumpris, and Ioannis Vlahavas. TraderNet-CR: Cryptocurrency Trading with Deep Reinforcement Learning, IFIP International Conference on Artificial Intelligence Applications and Innovations. Springer, pp. 304–315, Crete, Greece (2022)
V.Kochliaridis, E.Kostinoudis, I.Vlahavas, Proceedings of the 13th Hellenic Conference on Artificial Intelligence, ACM, Optimizing Pretrained Transformers for Autonomous Driving, pages 1-9, Athens, Greece (2024)
I.Pierros, V.Kochliaridis, I.Vlahavas, Predictive Maintenance Under Absence of Sensor Data, IFIP International Conference on Artificial Intelligence Applications and Innovations. Springer, pages 279-292, Crete, Greece, (2024)
V.Kochliaridis, I.Pierros, G. Romanos, I.Vlahavas, Vit2: Visual Timeseries Estimation using Visual transformers,, International Conference of Pattern Recognition, pages 217-231, Kolkata, India (2024)
V.Kochliaridis, Fillipos Moumtzidelis, I.Vlahavas, Scaling Multi-Frame Transformers for End-to-End Driving, International Conference on Agents and Artificial Intelligence, Springer, pages 496-503, Porto, Portugal (2025)
V.Kochliaridis, C.Moschou, A.Dimitrakopouloy, I.Vlahavas, Learning to InMoov: A Deep Learning Approach to Modeling Human Hand. 28th European Conference on Artificial Intelligence, Bologna, Italy

Other Publications

V.Kochliaridis, Fillipos Moumtzidelis, I.Vlahavas, “Temporal Fusion Transformers for Autonomous Driving”, Lecture Notes in Artificial Intelligence, Springer (2025)