“WUR should be the meeting place for AI and domain science”

His academic career has taken Ricardo from the University of Campinas, Brazil, to the United States, Norway, and ultimately to what he feels is home: Wageningen. He first came to Wageningen in 2017, visiting one of his students for three months. Ricardo and his family then decided to go on sabbatical leave in 2018 to live in either Groningen, where he was and still involved in a sports science project or Wageningen; because of Ricardo’s involvement with projects in the area of phenology – specifically the use of AI to assess the impact of climate change on plants – they chose Wageningen.

“It was an incredibly inspiring experience. Back in Brazil, where I’m from, I had a lot of administrative tasks, but here in Wageningen, I was able to reboot my research again. Considering our experience in Wageningen and the politically and financially unstable scenario in Brazil, as well as the lack of resources for research there, we realised that our future was abroad. We went back to Brazil late 2018, and moved to Norway seven months later, where I worked at the Norwegian University of Science and Technology (NTNU). I taught computer graphics courses, focusing on modelling, simulation, and visualisation.”

“Fast forward two years and I get a very exciting phone call from WUR, about the this very position. Our experience in 2018 was so good, that returning here last July felt like coming home. My family and I are so happy, and we’re here to stay.”

What makes WUR so appealing to you?

“I see a lot of opportunities here – that’s what makes WUR such a special place. There’s so much knowledge available in the areas of agri-food, animals, nutrition, environment, and social sciences, which is incredibly important for various reasons. First of all, all the research conducted in these areas presents us with tons of amazing data that can be used for analysis; using data science and AI, in consequence, can lead to unexpected knowledge discoveries. Secondly, WUR is doing cutting-edge, state of the art research in those areas, meaning that we have the best people working on this. Together, we can address research questions that are relevant worldwide, such as: how can we feed 10 billion people in 2050?”

“Moving from my comfort zone of computer science into the domain of food and living environment excites me, because this enables us scientists to really address relevant problems that may be impactful for different societies, multiple countries, even whole populations – that’s my drive.”

How does that collaboration work?

“In order to adopt and develop AI and machine learning, we need to know how to model domain knowledge, how to map domain problems to research in AI, and how to interpret AI results. The researchers at WUR can help us computer scientists make sense of those data and results, because they know, for example, how plants work. Also, they can help us identify when something doesn’t make sense, which could indicate that there’s a problem with the model we’ve made. Working in data science requires that cross contamination of my expertise and theirs.”

“In fact, I would say that my focus in my research is collaboration, both with seasoned and prospective researchers. That’s also part of these new AI positions at WUR; Anna Fensel, Ioannis Athanasiadis and I are expected to interact with and contribute to different research groups. If you imagine the research groups as vertical pillars, we get to move through them horizontally. That makes this quite a unique position.”

What is your assignment within this specific position?

“That’s a hard question, because part of our shared mission is to support the university with defining their vision for AI and data science, so our respective roles are not set in stone. Our main goal is to help develop successful teaching and research activities in the areas of data science and AI within all the different WUR research groups. This means we contribute to defining programmes, strategies and sets of actions that strengthen how WUR manages and benefits from data science and AI technologies.”

“Each of us is appointed to a different science group; mine is the Farm Technology group, where research focuses, for example, on how to apply computer vision or robotics to support farm activities, and on how to develop control methods for greenhouses. Right now I’m still in the process of mapping the challenges this group addresses in the WUR domains to research venues in data science and AI. I’ve also been engaged in fruitful conversations with nutrition researchers, and I’m involved in proposal writing for social sciences, plus there’s an ongoing research activity for environmental sciences, and I’ll be involved in the Wageningen Data Competence Center (WDCC) programmes. I intend to connect with different science groups as much as possible.”

When people think of a university with data science and AI in their repertoire, they usually don’t think of WUR straightaway...

“No, and I want to help improve WUR’s visibility, to get to the point where anyone who is interested in data science and AI in the domains of food and living environment thinks of WUR first thing. WUR should be the meeting place for AI and domain science. The WDCC is already working on this, organising activities such as workshops and other events that can bring together researchers and experts from Dutch and international communities alike. We need to make people aware of the fact that we have been able to greatly develop AI talent, and that we are moving forward with this to retain and attract more talent. I mean, research is in our blood. We need to team up for European research proposals and contribute to relevant projects so people can actually see that. Basically, we need to improve our visibility, attract talent, and identify relevant research questions.”

What about developing student talent?

“As a researcher, I want to have students and researchers involved in postdocs. I want them to team up, exchange perspectives and experiences, address relevant research questions, and disseminate results together. Currently I’m working on acquiring resources so I can have my own group of students that engages in collaborative research activities within all science groups, both nationally and internationally.”

What do you hope the broader impact of your work at WUR will be?

“I’m hoping that my efforts will help to foster the implementation of sustainable, effective and efficient operations in the private and public sectors, and support better-informed decision-making. I’d like to be able to map and present the possibilities, challenges, and risks associated with the use of data science and AI technologies; to define actions that can lead to policymaking, regulations, and guidelines for the proper use of such technologies as well. Also, I want to develop ideas on how to innovate and how to create new tech that could lead to new companies (such as AI-based decision support systems for the agri-food domain) and jobs (like environmental data scientists)– that’s probably the most tangible impact of what we’re doing. And last but not least, I want to make a difference in education: help people gain knowledge, improve their awareness towards the responsible use of tech in their professional and personal lives.”

“Essentially what I’d like to do is to find ways to develop knowledge and competences to ensure that data science and AI technologies can transform the future of societies in favour of sustainable development.”