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:
Health
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.
Optics
Meta-lenses are 2D optical elements with nanostructures that control light waves, allowing for rapid phase and amplitude changes. They offer features like polarization control and higher spatial resolution compared to traditional lenses, making them valuable for applications such as biomedical imaging and virtual reality. However, meta-lenses have drawbacks including stray light issues, tradeoffs between numerical aperture and efficiency, and limitations with single-surface designs.
Freeform meta-surfaces, using more flexible pillar shapes, can address these issues and improve efficiency. The challenge in meta-lens design lies in simulating complex physics due to computation barriers and balancing optimization with manufacturability.
