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Campus E1 1
66123 Saarbrücken (Germany)

Short Bio

Prof. Bernd Finkbeiner, Ph.D. is a faculty member at the CISPA Helmholtz Center for Information Security and a professor for computer science at Saarland University. He obtained his Ph.D. in 2003 from Stanford University. Since 2003, he leads the Reactive Systems Group, which became part of CISPA in 2020. His research focus is the development of reliable guarantees for the safety and security of computer systems, including specification, program synthesis and repair, and static and dynamic verification. 
 

CV: Last four stations

2020 - now
Faculty member at CISPA
2006 - now
Professor at Saarland University
2003 - 2006
Junior professor at Saarland University
1996 - 2002
Research assistant at Stanford University

Publications by Bernd Finkbeiner

Year 2017

Conference / Medium

Proceedings Sixth Workshop on Synthesis, SYNT@CAV 2017, Heidelberg, Germany, 22nd July 2017.

Conference / Medium

Runtime Verification - 17th International Conference, RV 2017, Seattle, WA, USA, September 13-16, 2017, Proceedings

Conference / Medium

ESOP
Programming Languages and Systems - 26th European Symposium on Programming, ESOP 2017, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2017, Uppsala,

Conference / Medium

37th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2017, December 11-15, 2017, Kanpur, India

Article

CoRR

Conference / Medium

TACAS
Tools and Algorithms for the Construction and Analysis of Systems - 23rd International Conference, TACAS 2017, Held as Part of the European Joint Conferences on Theory and Practice of Softwa

Conference / Medium

CAV
Computer Aided Verification - 29th International Conference, CAV 2017, Heidelberg, Germany, July 24-28, 2017, Proceedings, Part II

Conference / Medium

37th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2017, December 11-15, 2017, Kanpur, India

Teaching by Bernd Finkbeiner

2020

Neural-Symbolic Computing

In this seminar, we will explore new research that shows that deep neural networks are, in fact, able to reason on “symbolic systems”, i.e., systems that are built with symbols like programming languages or formal logics.

2019/20

Verification

This course takes an up-to-date look at the theory and practice of program verification.

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