Siyan Chen
Image:
Petter Bjørklund / SFI Visual Intelligence

Siyan Chen

Meet Siyan, our newest Doctoral Research Fellow

We happily welcome Siyan Chen as a new PhD Reseearch Fellow at SFI Visual Intelligence's hub in Tromsø, Norway.

Meet Siyan, our newest Doctoral Research Fellow

We happily welcome Siyan Chen as a new PhD Reseearch Fellow at SFI Visual Intelligence's hub in Tromsø, Norway.

By Petter Bjørklund, Communications Officer at SFI Visual Intelligence

Chen joined Visual Intelligence on March 2026 and is originally from China. He holds a Master's degree in Computer Science and Engineering from the Technical University of Denmark. He has experience as an embedded software engineer in industry for Beijing Highlander Digital Technology Co., Ltd., where he was involved in designing computer products, debugging software, and testing products for marine-domain applications.

His current research lie in machine learning and explainable artificial intelligence (AI), with a particular focus on developing robust and practical methods for complex real-world challenges in earth observation and marine applications.

Machine learning for reliable weather forecasting

Chen's PhD project will focus on developing machine learning models for more reliable and adapative weather forecasting in complex Northern Norway environments. He is particularly interested in integrating ideas from neureal operator learning and continual learning to make forecasting models more efficient, flexible, and responsive to new observations over time.

More specifically, his project explores how modern AI methods can improve prediction in settings where conditions change rapidly and available observations may be limited.

"The long-term goal is to support practical decision-making in applications such as environmental monitoring, risk assessment, and weather-related warning systems. Not only could this make models more accurate and adapative, but also interpretable and explainable," Chen explains.

Chen views the project as an opportunity to collaborate with like-minded and leading AI researchers.

"I also see it as a meaningful chance to contribute to safer, more sustainable, and intelligent technologies that can extract knowledge from complex data in the Earth observation and marine domains," says Chen.

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