Microsoft Research’s AI4Science initiative comes to Amsterdam Science Park. We talked to Paola Gori Giorgi, who is principal research manager at Microsoft Research and still affiliated as professor of theoretical and mathematical chemistry at the VU, about why the Science Park is an ideal place for knowledge exchange. “We want to be part of the ecosystem,” she says.
Working with scientists from different fields is crucial for Gori Giorgi’s work. “My particular discipline – this strange field called quantum chemistry – is a field that is extremely interdisciplinary because it lies in between chemistry, physics, mathematics and computer science,” she says. “No one has all this expertise to the highest possible level. So it means you really have to join forces with the people who have the complementary knowledge.”
The research by Gori Giorgi’s team on ways to accelerate scientific discovery with AI marks a move away from a data-driven approach. “This is a bit the old idea,” she says. “The new idea is that we know the exact equations for many interesting phenomena, in my case for predicting chemical reactions, but the equations are too difficult to be solved. We can use them but only to simulate small systems or smaller timescales. With artificial intelligence, we can accelerate these equations to a larger timescale and to larger systems.” But that requires a real team effort. “If you really want to take the next step, and really try to solve a lot of the issues that hamper the predictive power of these calculations, you need a huge collective effort.”
Paola Gori Giorgi, Professor of theoretical and mathematical chemistry “If we produce data, we like to make it open access so that other scientists use it – a lot of the things we do are made available to the scientific community ”
It’s a way of working that is perhaps more at home in a corporate research environment than in academia, where colleagues often compete with each other for grants, says Gori Giorgi. “In Microsoft Research internally, you don’t compete with anyone. They reward big, collaborative projects – the idea is to do research projects that are too large-scale for academia, and we are really incentivised to collaborate.” This doesn’t mean there’s a disconnect from the scientific community – much the opposite. “Because we do fundamental research, we publish scientific articles, we go to conferences. And part of our work is to let Microsoft Research build a reputation in the field. If we produce data, we like to make it open access so that other scientists use it – a lot of the things we do are made available to the scientific community.”
Paola Gori Giorgi, Professor of theoretical and mathematical chemistry “This collaborative approach makes Microsoft Research a perfect fit for the Science Park ”
Of course, this collaborative approach makes Microsoft Research a perfect fit for the Science Park. “There’s a lot of overlap,” says Gori Giorgi. “Max Welling, who started the lab together with Rianne van den Berg, is also still a professor at the UvA’s computer science department. And particularly in my field, we have contact with other scientists who work on similar topics, like the computational chemistry group at the UvA, and the quantum chemistry groups at the VU. We are also funding PhD students at both universities to foster scientific exchange.”
And there is a hope for more informal scientific conversations. “We aim for a lot of exchange. The idea really is to be part of the ecosystem of AI for science in Amsterdam,” says Gori Giorgi. Some of the PhD students from the UvA and the VU could attend talks or give presentations, and there is talk of Friday afternoon socials involving pizza. Gori Giorgi is also enthusiastic about the potential of her future workspaces at Matrix ONE: “I visited it – super nice! The project for the interior includes whiteboards in the corridor where you can stop and just start to write equations and discuss them with your colleagues. I’m really looking forward to going there.”
What’s the dream for Gori Giorgi’s time at the Science Park? “What’s expected from us is great breakthroughs that really accelerate the discovery cycle. For instance, with the help of machine learning you can have computational chemistry calculations with which you can much more easily predict materials’ properties. This would dramatically accelerate the discovery cycle for materials for sustainability, or for catalysts for solutions to important problems such as carbon capture. In addition to sustainability, drug discovery is another topic to which computational chemistry is linked. The dream is to really contribute to one of these big fundamental challenges.”
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