Valentin Hassler

Research Area C: How are we curious?

BA: Statistical analysis of the results of the prize-winning paper "Adaptation to Climate Change: Evidence from US Agriculture (Burke & Emerick, 2016)". Extend and verify the results presented in the paper using new data sources and discuss the implications. MA Integrating segmentation into multiple object tracking: Classical Multiple Object Tracking relies on bounding box matching over time. The thesis uses one of these frameworks and adds the ability to predict instance segmentation masks and use them in further steps to improve tracking results.


"Curious visual representation learning in children and machines"

My PhD project uses computer vision techniques to improve our understanding of curiosity. This involves creating normative models of the human visual system, analysing recorded eye-tracking data, and generating visual stimuli for children that follow specific patterns. These visual inputs help to test different hypotheses about the nature of curiosity.


I am interested in applying deep learning methods to the study of curiosity. I find it fascinating to explore how new methods can reframe established topics and open up new avenues for insight. Curiosity fascinates me because it acts as a gentle nudge, inspiring people to explore the world without immediate extrinsic rewards. This feels particularly personal because I am trying to understand why I do what I do - literally.



  • April 2018 until February 2020 - Chair of Economics VIII, University of Bayreuth, Germany
  • April 2021 until April 2023 - Chair of Medical Statistics, University of Göttingen, Germany