Spring 2019 GRASP Seminar Series: Konrad Kording, University of Pennsylvania, "Understanding Machine Learning, Disease, and Brains"

ABSTRACT
We have surprisingly similar problems between machine learning and neuroscience - it is remarkably hard to know why both work. I will summarize a couple of recent approaches that we are using towards those two aims. However, as with many things in life, neither brains nor machine learning systems seem to overly care about the fact that they should not work. I will thus also discuss thus some recent collaborations with the laboratory of Michelle Johnson where we use pose tracking to ask scientific and medical questions.
 

Presenter's biography

Konrad Kording runs his lab at the University of Pennsylvania. Konrad is interested in the question of how the brain solves the credit assignment problem and similarly how we should assign credit in the real world (through causality). In extension of this main thrust he is interested in applications of causality in biomedical research. Konrad has trained as student at ETH Zurich with Peter Konig, as postdoc at UCL London with Daniel Wolpert and at MIT with Josh Tenenbaum. After a decade at Northwestern University he is now PIK professor at UPenn.