معرفی
Konrad Kording is a Penn Integrates Knowledge (PIK) Professor in Neuroscience at the University of Pennsylvania. His research focuses on causality, machine learning, and deep learning applications in neuroscience. He leads a highly interdisciplinary lab exploring neural data analysis, Bayesian decision theory, and meta-science. Key projects include developing algorithms for causal inference from observational data and analyzing movement and neural activity using computational models.
Education: PhD in Physics from ETH Zurich, Diploma in Experimental Physics and Computational Neuroscience. Collaborates widely across disciplines, including with bioengineers, statisticians, and clinicians at UPenn and external institutions like MIT and UCSB. Advises graduate students and postdocs in topics ranging from neural decoding to AI ethics. Founded the Kording Lab, emphasizing independent project-driven research with unique lab practices like weekly 'lab teachings' and collaborative coding sessions.
