Meet Daniel Cámpora: assistant professor at the Department of Advanced Computing Sciences, researcher at CERN and one of the lecturers you may encounter during your bachelor’s programme.

Daniel started his career in computer science for one reason only: he loved computers. Today, he helps create scientific breakthroughs in physics. How? He will tell you himself.

Using passion to push research forward

Daniel: “Computers fascinated me in high school. I wanted to know how they worked, so I chose to study Computer Science. I didn’t have any experience with programming back then. I learned to program during my studies, where I also experienced something much more exciting: I found out about all the different subfields of Computer Science I didn’t even know existed. The university became a gateway to discovering my passion, which turned out to be high-performance computing. High-performance computing is about creating extremely fast computers. This becomes relevant in situations where computing is pushed to its limits, for instance when calculating tons of regional, hourly-updated weather forecasts. I personally apply high-performance computing at CERN’s Large Hadron Collider in Switzerland, where I still work alongside my job in Maastricht."

"The Large Hadron Collider is a particle collider, which simulates the universe right after the Big Bang. Over 10,000 people work there to answer fundamental questions about physics. These experiments generate huge amounts of data – around 5000 gigabytes per second for the one I’m involved in. It’s impossible to save all of this information, so an automated system decides what gets saved and what gets thrown away on the spot. I designed and implemented a new version of this system. It is 3 times more efficient than the previous one. It's also cheaper, and it uses less energy. The efficiency boost makes a huge difference, because it essentially means we can do more physics research than before. This extra output provides more insights for the scientific challenges we work on. I am very proud that I have revolutionized the way that data is gathered at CERN.”

Approachable teaching with real-life examples

“I don’t like to put a big distance between my students and myself. I teach in a casual manner and really interact with students. I actually think I have that from my dad. He is a grandmaster in chess, and also a chess teacher. He is very outgoing and social - truly an example for me. In my teaching, I give real-life examples and draw from my own experience. It helps to see the value in the things I teach. I want my students to think: ‘Oh, this is actually useful’. Realizations like that will make it easier to keep paying attention."

"I love to meet students with a passion for the world of computers in my class. Students who are eager to learn, and who still have to find their field of expertise. Studying Computer Science at an academic level provides an ideal playing field, to find that one thing that makes your heart and brain go: BOOM, this is it! Like what happened to me when I discovered high-performance computing. I want that experience for my students. It’s genuinely exciting to push computer science forward, to push the limits of what computers can do for science and society.”

Want to learn more about Daniel's research? Read more about Allen, the new system Daniel designed, on the UM website or - if you are looking for something more technical - over at CERN.