Invited Speakers

Renaud Lambiotte

Bio: Renaud Lambiotte is professor of Networks and Nonlinear Systems at the University of Oxford. He received his PhD in theoretical physics from Université libre de Bruxelles in 2004, and has been a Research Associate at ENS Lyon, Université de Liège, Université catholique de Louvain and Imperial College London, and professor of Mathematics at the University of Namur. His research interests include network science, data mining, stochastic processes, social dynamics and neuroimaging. He has published around 130 peer-reviewed articles and one book on temporal networks. He is also the co-founder of L’Arbre de Diane, a publishing company at the interface between science and literature.

Website: https://www.maths.ox.ac.uk/people/renaud.lambiotte

Talk title: TBD

Abstract: TBD

Tiago P. Peixoto

Bio: Tiago P. Peixoto is a Full Professor at IT:U, and is also affiliated with the Department of Network and Data Science at the Central European University. He leads the “Inverse Complexity Lab”, which operates at the interface between statistical physics, computational statistics, information theory, Bayesian inference, and machine learning, and has as its main focus the study of inverse problems in network science and complex systems. Peixoto develops and maintains graph-tool — an efficient Python module for manipulation and statistical analysis of graphs and networks. He has a PhD in Physics from the University of São Paulo, and a Habilitation in Theoretical Physics from the University of Bremen. In 2019 he was the recipient of the Erdős–Rényi Prize in Network Science, awarded by the Network Science Society.

Website: https://skewed.de/lab/

Talk title: TBD

Abstract: TBD

Jana Diesner

Bio: Jana Diesner is a Full Professor at the Technical University of Munich, School of Social Science and Technology, Department of Governance, with an affiliate appointment at the School of Computing, Information and Technology. She leads the Human-Centered Computing group. Her interdisciplinary group works on methods from network analysis, natural language processing, machine learning and AI, and integrates them with theories from the social sciences and humanities to advance knowledge about socio-technical systems and responsible computing. Jana earned her Ph.D. at Carnegie Mellon, School of Computer Science. Jana joined TUM from the University of Illinois Urbana Champaign, where she was a tenured professor at the School of Information Sciences. There, she served as the Director of the Ph.D. Program, Director of Undergraduate Programs, and Director of Strategic Initiatives/Data Science.

Website: https://www.gov.sot.tum.de/hcc/team/jana-diesner/

Talk title: TBD

Abstract: TBD