Hannah Pinson, Assistant Professor of AI at Eindhoven University of Technology

I am interested in obtaining fundamental insights in deep learning. My current focus is on questions about inductive bias, implicit regularization and generalization, and I mainly study the interplay between dataset structure, neural network architecture and gradient descent. I also teach about the use and understanding of neural networks at a master’s level, and I supervise several research projects in AI.

I obtained a master’s degree in Physics and one in Computer Science/AI, both at the Vrije Universiteit Brussels (VUB), Belgium. My master’s studies were completed with a year-long research stay with the Max Tegmark group at MIT in 2017. I later obtained the Agoria award for the best thesis in technology and innovation for my thesis project.

In 2018, I started my PhD as an FWO fellow under the supervision of Prof. Vincent Ginis at VUB. My thesis was titled: Form and Function in Neural Networks: On the Interplay Between Dataset Structure, Network Architecture, and the Evolution of Learning. During my PhD I remained a visiting researcher at MIT, and I also learned to experiment with real neurons and analyze neural network recordings in the labs of Prof. Michael Levin at Tufts University and of Prof. Mustafa Sahin at Harvard Medical School. I completed my PhD in June 2023.

In September 2023 I started as an Assistant Professor of AI at the Data and AI cluster at Eindhoven University of Technology. To be continued!