Computers Don't Byte

Assistant professor Derya Soydaner explores how AI and art collide, revealing why creativity, perception, and machine learning are far more intertwined than they seem. From testing whether large language models can recognize artistic styles to imagining a ‘museum buddy’ that guides visitors through galleries, this episode uncovers how technology might reshape the way we experience culture.

Soydaner also dives into AI‑generated music, artistic authorship, and the tension between human struggle and machine‑made creativity. A thoughtful look at what we gain—and risk losing—as generative AI becomes part of our creative world. 

Idea by Dimitra Kouimtzidou
Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou
Interview, production & editing by Michiel van Poelgeest

In this episode a surprising crossover between ancient archaeology and modern computer science. Anthropologist‑turned‑computer‑scientist Sebastian Fajardo Bernal reveals how early humans developed complex technologies like birch‑bark glue, and how their problem‑solving strategies mirror the logic behind today’s algorithms. It’s a fresh look at innovation through the lens of deep history.

Sebastian also explains how models such as Petri nets help researchers understand technological evolution and even inspire new ways to teach AI systems to interact with the physical world. It shows how looking back thousands of years can spark new ideas for the technologies that will define our future. 

Idea by Dimitra Kouimtzidou
Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou
Interview, production & editing by Michiel van Poelgeest

In this episode postdoc in Hybrid Intelligence Centre, Tom Kouwenhoven tells all about his research which focusses on how humans and machines learn to communicate. From chatbot misunderstandings to experiments where people and AI invent entirely new languages, Tom shows how collaboration can work even when both sides interpret information differently.

The conversation also dives into visual intuition, like the Bouba–Kiki effect, and why shared human preferences matter when designing future AI systems. It provides an honest view of how far human–machine communication has come and the challenges that continue to shape its future.

Idea by Dimitra Kouimtzidou
Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou
Interview, production & editing by Michiel van Poelgeest

Mathematician and optimization expert Elena Raponi takes us from car‑crash simulations to her teenage quest for the perfect pizza. Through her stories, she reveals how Bayesian thinking shapes the way we learn, explore, and refine our choices—whether we’re comparing pizza places or navigating complex engineering problems.

The conversation dives into black‑box optimization, algorithm design, and the surprisingly human logic behind making choices—from selecting a Netflix series to engineering safer cars. The episode offers an accessible look at how optimization shapes everyday decisions and high‑stakes scientific challenges alike.

Idea by Dimitra Kouimtzidou
Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou
Interview, production & editing by Michiel van Poelgeest

Game AI expert Mike Preuss takes us from the world of Go‑playing algorithms to cutting‑edge chemistry. Hear how Monte Carlo Tree Search, the technique behind AlphaGo, helped enable the first fully automated method for chemical retrosynthesis—an achievement published in Nature.

The Game Lab that Mike runs at LIACS improves game mechanics, collaborates across disciplines, and uses games for education, psychology, and even language learning. From smarter strategy units to serious games that train pilots, this episode shows why games—and game AI—matter far beyond entertainment.

Idea by Dimitra Kouimtzidou
Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou
Interview, production & editing by Michiel van Poelgeest

In this episode, assistant professor Eleftheria Makri takes us from a classic 1980s cryptography puzzle to today’s urgent questions about data privacy, secure computation, and the looming impact of quantum computing. Through clear examples—from billionaire dinner bills to medical diagnostics—she shows how we can extract useful insights from data without ever exposing the data itself.

Makri explains why privacy isn’t about secrecy but about control, and how secure computation can unlock collaboration in fields like healthcare and finance without exposing sensitive data. She also highlights the urgency of preparing for a post‑quantum world, where today’s encrypted information could become tomorrow’s open book.

Idea by Dimitra Kouimtzidou
Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou
Interview, production & editing by Michiel van Poelgeest

All systems are go! Assistant professor Henning Basold guides us through the fascinating world of systems—from the biological structures that make us who we are to the complex cyber‑physical systems behind rockets, trains, and self‑driving cars.  

How do category theory, logic, and formal verification help us understand, model, and secure the technologies we rely on every day. Why do systems fail? How can we prove they’re safe? And what does it take to describe the world mathematically? Tune in for a thought‑provoking journey into the hidden structures that shape the world around us.

Idea by Dimitra Kouimtzidou
Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou
Interview, production & editing by Michiel van Poelgeest

What’s the difference between a zebra and a zebrafish? Assistant professor Rita Pucci, who works at both LIACS and Naturalis, brings together biodiversity and computer science. She’s developing a model that can recognise unique skin patterns of individual animals within a herd: a breakthrough that could transform how wildlife is monitored.

It could also reveal whether inbreeding is occurring—crucial information for species like zebras, where inbreeding can have devastating consequences. But before the model can reliably identify patterns in zebra coats, it first needs to learn how to generate patterns itself. And for that, it is trained on thousands of images of zebrafish.

Idea by Dimitra Kouimtzidou
Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou
Interview, production & editing by Michiel van Poelgeest

How can data help speed skaters push past their limits? Associate Professor Arno Knobbe specializes in sports data science. His research dives deep into the tiny details that can decide the outcome of a race. How and where do speed skaters find tenths of seconds to beat their rivals?

Arno's research helps olympic athletes study the 'corners' of the ice rink, where, as it turns out, every athlete needs a slightly different approach to glide through at top speed. And this isn’t just theory; his insights play a role at the 2026 Winter Olympics. 

By collecting specific training data for each individual skater, Knobbe and his team can build the ultimate training schedule — one that ensures an athlete peaks at exactly the right moment: race day. And the impact goes far beyond elite sports. Even older adults wearing a smartwatch can benefit from the same principles, using data to better understand their health and daily activity.

Idea by Dimitra Kouimtzidou
Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou
Interview, production & editing by Michiel van Poelgeest