About

My name is Mikkel Lepperød and I work as a Research Scientist at Simula Research Laboratory where I am currently leading a group called bioAI in the department for Scientific Computing. I previously worked with biologically inspired artificial intelligence (AI) as a Postdoc at the University of Oslo (UiO), Norway, and before that I obtained a PhD in Neuroscience at UiO and a Master’s in Applied Mathematics at the Norwegian University of Life Sciences. For publications visit my Google Scholar page.

I aim to understand how animals, as examples of natural intelligence, learn both physical and non-physical relationships in the world through interaction. For example, how animals explore their environment to enable efficient foraging. I believe that building models of these processes is essential to gain this understanding.

My research focuses on developing novel methods in AI, including biologically inspired machine learning techniques to understand the neural mechanisms of memory, action, and sensory processing. My expertise is fundamentally multidisciplinary, combining computational models and simulations with causality research and experimental techniques.

I have always been fascinated by how theoretical knowledge can, sometimes surprisingly, provide insights into how nature works. However, with complex systems like the brain, it can be extremely challenging to determine whether a theory is genuinely insightful. This is why I strive to gain as much knowledge as I can, spanning experimental and computational neuroscience, causal inference, and AI. Although my focus may at times seem scattered across various topics, I truly believe that multi- and even transdisciplinary approaches are absolutely necessary to understand natural intelligence and build artificial agents that are truly intelligent.