Our research specialties are within artificial intelligence, data science and statistical signal processing, statistical machine learning, biostatistics, and epidemiology and our main research directions are:
Medical AI
In most medical setting, an extensive amount of patient data is generated and recorded every day. These data often contain useful information that can be used to improve current medical procedures and treatment options.
AI techniques rise as a solution to effectively use and integrate these different types of data to advance the healthcare sector towards e.g.:
- Improving diagnostic tools.
- Efficient prognosis of clinical outcomes.
- Highly personalized treatment options.
Energy
Along with the growing demand of modern society, generating affordable and clean energy becomes imperative. Wind and fusion energy are suitable candidates to cover future demand. However, to fully substitute existing energy plants, reliability and availability needs to be improved.
AI, statistical machine learning, and data science span the foundation for accelerating research in clean energy. The challenges faced in this field range from big-data analytics to physical modelling.
Responsible AI
As artificial Intelligence (AI) becomes increasingly integrated into every aspect of our lives, establishing trust and ensuring its acceptance is essential for unlocking its full potential. Our team is committed to designing and deploying AI systems that adhere to ethical principles and societal values. Our work focuses on the core principles of Responsible AI—privacy, fairness, accountability, and transparency—aligning our efforts with regulations like GDPR and the EU AI Act, which underscores the importance of privacy, transparency and fairness in AI systems.
Addressing AI Challenges
Our unit not only focus on applied AI, but also exploring solutions beyond AI. On the same line, we are simultaneously working on solving problems within Optics, developing organoid intelligence, and precision medicine.
