He is paving the way for simpler microscopy

“We are science artists!”

Jesús Pineda throws his arms open and breaks into a laugh, as he often does. The location is the Physics Building, where he spends his days as a doctoral student in Professor Giovanni Volpe’s research group at the University of Gothenburg. He describes the environment as open and encouraging, fostering both creativity and critical thinking.

“I love the freedom of what we do, getting to constantly learn new things and having the chance to help shape the future. All ideas are appreciated in our group, and we’re always having discussions that push the work forward.”

For Jesús, who is from Colombia, the journey toward doctoral studies began when he heard Giovanni Volpe’s presentation at a research conference in Mexico. The concept of how methods based on deep machine learning – a form of artificial intelligence – can improve analyses of pictures taken with microscopes made a huge impression. He is currently in his second year as a doctoral student and has already been a co-author in several notable publications in the subject

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Research that is available to all

Studies of cells in microscopes are a cornerstone of all biomedical and pharmaceutical research. Jesús hopes that the group’s new, effective analysis methods will pave the way for pharmaceutical development and understanding of diseases. An important starting point is therefore that all research results are open access and can thus be read by everyone.

“Today, a lot of research isn’t even available online, but we want our methods to be put to use. The idea is that everyone should be able to use them, even people who aren’t experts in the field. That’s why we want to create a ‘library’ of our methods that everyone can use, to build bridges between microscopy and research on deep machine learning. We’ve already been contacted by research groups that want to use the methods we’ve developed, and that feels fantastic.”

Combined methods create opportunities

Jesús Pineda’s latest project is about combining deep machine learning with the mathematical area of graph theory to facilitate the analysis of microscope images. This has never been done before and creates opportunities to quickly and effectively obtain detailed information from data-dense microscopic images.

“This method makes it possible to simply and reliably analyse lots of cells in motion simultaneously. I see many possibilities and future applications for this,” says Jesús, who points out that it is a huge challenge to work with something that is going to be implemented for the first time.

“It’s tough when there’s nothing else for comparison and everything has to be built from scratch. But at the same time, it’s an incredibly exciting process and maybe we can contribute to creating a brand-new field of research.”

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In hopes of reaching industry

He feels that Sweden is welcoming, and the move to the northern hemisphere has exceeded his expectations. He and his wife have made many friends and they like the food, the culture – and the weather.

“Yes, I actually like the weather. At home it’s always 32 degrees, but here the seasons change which I think that’s great.”

Gothenburg has many companies in the biotech sector, and Jesús would like the research to reach both academia and industry. Together with a few research colleagues, he has started to form a company that will help the biotech industry use AI-based analysis methods to simplify microscopy.

“My top goal is for the research to be put to use,” he says.

Text: Ulrika Ernström