Sandra Kiefer completed her undergraduate studies in Bioinformatics and Mathematics at Goethe University Frankfurt, with theses on the Graph Isomorphism Problem and the diameter of polytopes under the supervision of Nicole Schweikardt and Thorsten Theobald, respectively. During her Master’s studies in Mathematics, she further specialised in Group Theory and Combinatorial Optimisation, including one year at the University of Santander in Spain. After obtaining the M.Sc., she moved to RWTH Aachen University, where she has been working on combinatorial algorithms in the context of the Graph Isomorphism Problem under the supervision of Martin Grohe and Pascal Schweitzer. Her research visits to the Australian National University in Canberra and the University of Warsaw have led to collaborations with Brendan McKay and Mikołaj Bojańczyk. In addition to her research, she successfully completed an M.Ed. degree in Mathematics and Spanish.

Sandra obtained her Ph.D. in Computer Science in March 2020. As a postdoctoral researcher, she has continued her work at Martin Grohe’s chair at RWTH Aachen University and has established interdisciplinary collaborations broadening her field of research. She is currently on leave from RWTH Aachen on a temporary position at the University of Warsaw, where she engages in a continuation of her project on a higher-order functional programming language with Mikołaj Bojańczyk.

SWS   Info

AG Audience

English

60 Minutes

Saarbrücken

Graphs are widespread models for relations between entities. One of the fundamental problems when dealing with graphs is to decide isomorphism, i.e., to check whether two graphs are structurally identical. Even after decades of research, the quest for an efficient graph-isomorphism test still continues. In this talk, I will discuss the Weisfeiler-Leman (WL) algorithm as a powerful combinatorial procedure to approach the graph-isomorphism problem. The algorithm can be seen as a link between many research areas (the ""WL net""), including, for example, descriptive complexity theory, propositional proof complexity, and machine learning. I will present work regarding the two central parameters of the algorithm – its dimension and the number of iterations – and explore their connection to finite-model theory. I will also touch on some past and ongoing projects in other areas from the WL net.

--

Please contact MPI-SWS office team for link information.

Danielle Dalton

+49 681 9303 9106

--email hidden

passcode not visible

logged in users only