AI methods help create sustainable transport solutions and protect critical infrastructure

What are your research topics?

I study artificial intelligence, more specifically deep learning methods, to address the challenges of computer vision, time series analysis and optimisation. All the research conducted in my group is based on spatiotemporal data, or data combining both spatial and temporal variability. 

Where and how does the topic of your research have an impact?

Our research is based on a strong sustainability perspective. We investigate, for example, how urban transport should be planned to deliver maximum sustainability benefits. We also work to secure satellite navigation from intentional interference. 

In addition, our research supports sustainable automated navigation systems, currently used in industry and other areas, by making them safer. Automated industrial systems can also be developed to navigate and understand their environment in a more economical and energy-efficient manner.

What is particularly inspiring in your field right now?

As important new methods are constantly being developed in AI and machine learning, keeping track of, and up to speed with, developments is inspiring. I’m also inspired by the significant goals of our research, such as promoting sustainable development and protecting critical infrastructure, as they’re of personal significance to me.

This news item was originally published on the University of Helsinki website on 5.6.2024