Topic Unraveling Odor Perception with E3 Equivariant Graph Neural Networks Through Self-Supervised Learning About the speaker Christian J. Binder embarked on his academic journey at the Higher School (HTL) for Informatics, honing his skills from 2000 to 2006, before securing a BSc in Bioengineering and Bioinformatics from FH Campus Wien in 2015. Currently, he is finalizing his MSc in Computational Science at the University of Vienna, where he specializes in data mining, machine learning, and the computational aspects of biology and chemistry. Since 2007, Christian has applied his expertise in software engineering across various roles, turning freelance in 2018. He also shares his knowledge as a lecturer in C++ programming for bioinformatics at FH Campus Wien since 2019. Presently, Christian is dedicating his efforts to his master's thesis within the Cheminformatics group at the University of Vienna's Department of Pharmaceutical Sciences. His research is centered on the innovative "odor-map" project, aiming to decode the complexities of odor perception through computational models. | 
