We've Come a Long Way
AiDEAS is a team of proven researchers, engineers and seasoned entrepreneurs with extensive track records in many areas of AI and machine learning development. Our team members have unique expertise in developing novel algorithms for solving important existing and/or emerging problems as well as leading award-winning academic research. The entire AiDEAS crew is excited and driven to change the way we sense, comprehend and act by building high-end AI and machine learning.
Thinking of joining us? We’d love to hear from you!
The core team
Co-founder - Serafeim Moustakidis
Dr Serafeim Moustakidis has wide experience in computational intelligence, machine learning and data processing with more than 12 years of research experience in various fields. His research focuses in developing novel algorithms for solving important existing and/or emerging problems. His main scientific interests cover various application fields such as Deep Learning, Big Data, Biomechanics, Bio-economy, Health, Remote Sensing, Energy Optimization, Non- Destructive Testing (NDT) and machine learning-empowered imaging. He has been involved in the technical implementation, scientific or overall management of 25 R&D projects of a total budget of 35 million Euros. Serafeim has also been active in EU proposal writing since 2010 and has managed to secure more than €9.2 million (in FP7 and Horizon2020). He has worked for several research organisations across Europe.
Co-founder - Patrik Karlsson
holds a MSc. in Materials Science from Uni of Nancy. Has worked for several years at Fraunhofer Institute on Electron beam/Plasma techniques. He has been involved in numerous Industrial Research projects and more than 15 years in EC funded projects. Has participated and lead more than 32 Research & Innovation Projects (being the coordinator of three) of a total budget greater than €105 million. Research involved nanotech&advanced materials, eLearning, AAL&rehabilitation, wearable sensors, WSN for agriculture, robotics & mechatronics, NDT, machine learning for defect detection and classification. In addition to his strong PM and technical background he also has significant financial and exploitation expertise.
Dr George Georgoulas received his Diploma and PhD from the Department of Electrical and Computer Engineering of the University of Patras in 1999 and 2006 respectively. His expertise and research interests involve areas of Software Engineering such as Machine Learning, Computational Intelligence, Data Mining, Signal Processing, Evolutionary Optimisation and Soft Computing with various application areas. He has authored more than 100 papers in international conferences and journals, two book chapters, and he also holds a Greek patent in fault detection of induction machines.
Senior ML scientist - George Georgoulas
Senior data analyst - Zoumpolia Dikopoulou
Dr. Zoumpolia Dikopoulou received the BSc. degree (Hons.) in Computer Science in 2006 from the Technological Educational Institute of Lamia, Greece. In 2011, she completed her MSc. degree (Hons.) in Computer Science in from the Ionian University, Corfu, Greece. She has been awarded the academic degree of Doctor of Sciences: Computer Science from Hasselt University, Belgium or her dissertation on “Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps”. Moreover, she is author and co-author in scientific journals and conferences. In addition, she is a developer of the “fcm” package in R programming language. Finally, her research interests are focused on graphical models, machine learning, graph theory, fuzzy logic, fuzzy cognitive maps, data science and aggregation methods.
ML engineer - Konstantinos Stergiou
Konstantinos Stergiou received a Bachelor’s Degree from the Department of Physics at the Aristotle University of Thessaloniki, and holds a Master’s Degree in "Econophysics and Financial Predictions" from the Department of Economics at the University of Thessaly. He is currently a Ph. D. student in the Civil Engineering Department at the University of Thessaly focused on “Forecasting the availability and value of energy resources with data analysis and machine learning algorithms”. He is experienced in developing machine learning models such as Neural Networks by the use of Python and has a good command of R language and Matlab.