Better data leads to better scientific understanding

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Petteri Nurmi, professor of computer science, develops computational methods that can enhance data collection processes and aid data-driven decision-making.
Petteri Nurmi
Petteri Nurmi explores novel ways to enhance data collection processes, particularly in the context of natural ecosystems. (Image: Maarit Kytöharju)

What are your research topics?

My research group works on networked and embedded sensing systems, focusing on how they can be utilized as tools to support scientific endeavours. These systems are used on devices with network connections and integrated sensors, such as smartphones, environmental sensors, drones, and autonomous vehicles. 

Examples of our research include creating data collection, AI, and machine learning methods to enhance data quality, and examining the potential security and privacy risks associated with data use. Ultimately, my research aims to leverage these technologies to advance scientific understanding and provide new and improved research methodologies.

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

Our research primarily impacts empirical-driven analysis by developing innovative methods for collecting scientific measurements. These advancements not only enhance data collection processes but also have significant potential in data-driven decision-making across society, such as in business and policy making. These technologies also have commercial potential, and some of my findings have led to commercial innovations.

What is particularly inspiring in your field right now?

The current excitement in my field surrounds the integration of advanced AI technologies into everyday devices. Modern smartphones already integrate powerful AI assistants, and there are initiatives to bring AI techniques to smartwatches, wearables and other everyday devices. 

Personally, I am motivated to explore novel ways to enhance data collection processes, particularly in the context of natural ecosystems, with oceans and aquatic environments being especially close to my heart. 

Additionally, the potential for quantum computing in embedded systems fascinates me, as it opens new avenues for research that could revolutionize how we process and analyse data.

This news item was originally published on the University of Helsinki website on 2.12.2024

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