Profile
Max Wassermann is a PhD student affiliated with the Universitätsklinikum Tübingen, studying the information represented in the Medial Temporal Lobe regions during viewing of natural stimuli as part of the displayed text: CRC 1233 “Robust Vision” Max conducts his work within the C3N group under the supervision of [displayed text: Dr. Stefanie Liebe][url: https://liebelab.github.io/members/stefanie-liebe.html] and collaborates as an associate PhD student with Dr. Jacob Macke from the [displayed text: Machine Learning in Science group][url https://www.mackelab.org/]. He has a background in engineering but later attained a Bachelor’s and Master’s degree in Cognitive Science at Osnabrueck University, where he focussed on machine learning and neuroscience. He has experience in the domain of Data Science and researched the temporal evolution of representational geometries in MEG data with [displayed text: Tim Kietzmann][url: https://www.kietzmannlab.org/] at Osnabrueck University, aswell as utilizing information-theoretic methods such as active information storage and transfer entropy on spike trains and local field potentials with [displayed text: Michael Wibral][url: https://www.uni-goettingen.de/en/603144.html] at Georg-August-University Goettingen. He will investigate which stimulus features produce clusters in the LFP and single unit activity of human subjects and examine machine learning models whose embeddings align with these neural recordings based on representational similarity analysis. He is interested in normative modeling, applying machine learning methods to neuroscience and how insights into biological and artificial minds can inform one another.