A pilot internship program lets Berkeley students come to Finland to work with local researchers and leverage supercomputing capabilities.
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For Kevin Luck, a postdoc at FCAI was an important step to a faculty position.
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Patrick Rinke’s pioneering expertise in finding sustainable and climate-friendly materials with machine learning methodology has arguably never been more in demand.
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The impact of creative AI is unfolding before our eyes, yet we struggle to understand it. It’s the perfect time to ask researchers what they see and think.
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FCAI postdoc Ulpu Remes develops ELFI, the open-source software for likelihood-free inference.
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Aalto University visiting professor and member of ELLIS Unit Helsinki, Guoying Zhao, on emotion AI, face analysis and visual intelligence
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FCAI professor Vikas Garg’s research applies deep learning to the fields of quantum computing and drug discovery
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FCAI visiting professor Ievgen Redko explores how and why machine learning works
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FCAI researcher Ayush Bharti boosts wireless communications with signal interaction models
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Matti Nelimarkka investigates the relationship between technology and politics
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Associate professor Laura Ruotsalainen joins FCAI’s steering group, with sustainability-related goals in mind
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FCAI researcher Christian Guckelsberger wants to teach creativity to computers
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In the future robots will work and learn independently, says professor Joni Pajarinen
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As an undergraduate, current Aalto PhD student Tuomas Kynkäänniemi calibrated the sensors of a Mars rover for the Finnish Meteorological Institute (FMI). Now, his research is worlds away.
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Heli Julkunen developed a machine learning method that predicts how different drug combinations kill cancer cells, and now she helps advance preventive healthcare as a data scientist.
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New professor of practice wants to apply his AI expertise and make sure usable innovations are brought from research papers into practical use.
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Milica Todorović uses computational methods for materials science, training AI on her field's vast databases to speed up the search for tomorrow's functional materials.
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FCAI professor Luigi Acerbi develops new methods for approximate Bayesian inference that are both tools for AI and models of human intelligence
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Data Scientist and Researcher Sakira Hassan believes that when we can harness AI to transform data into knowledge and the means to forecast the future, we are not far away from building a smart world of science fiction.
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FCAI’s visiting professor Timo Koski´s scientific interests are probability, genetics, causal inference and Bayesian networks.
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