Dr Michael Tautschnig

Lecturer
Email: michael.tautschnig@qmul.ac.ukTelephone: +44 20 7882 5226Room Number: Peter Landin, CS 432Website: http://www.tautschnig.netOffice Hours: Tuesday 13:00-14:30
Teaching
Programming for Artificial Intelligence and Data Science (Postgraduate)
This module provides an intensive practical introduction to programming in Python, suitable for students with some degree of mathematical or statistical maturity. It covers a range of practical skills and underlying knowledge. These include the basic programming constructs for control, data structuring and modularisation; the use of systems for collaborative development and version control such as Git; unit testing and documentation; project structures and continuous integration/deployment.
Research
Research Interests:
Software VerificationConcurrency
Decision Procedures
Publications
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Bayless S, Buliani S, Cassel D et al. (2025). A Neurosymbolic Approach to Natural Language Formalization and Verification. nameOfConference
QMRO: qmroHref -
Peled R, Kroening D, Tautschnig M et al. (2025). Large Lemma Miners: Can LLMs do Induction Proofs for Hardware?. nameOfConference
QMRO: qmroHref -
Giacobbe M, Kroening D, Pal A et al. (2024). Neural Model Checking. nameOfConference
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(2024). Neural Model Checking. Advances in Neural Information Processing Systems 37
DOI: 10.52202/079017-2742
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Giacobbe M, Kroening D, Tautschnig M et al. (2024). Neural Model Checking.. nameOfConference
DOI: doi
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Kroening D, Schrammel P, Tautschnig M (2023). CBMC: The C Bounded Model Checker. nameOfConference
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Beyer D, Dangl M, Dietsch D et al. (2022). Verification Witnesses. nameOfConference
DOI: 10.1145/3477579
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Chong N, Cook B, Eidelman J et al. (2021). Code-level model checking in the software development workflow at Amazon Web Services. nameOfConference
DOI: 10.1002/spe.2949
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Cook B, Döbel B, Kroening D et al. (2020). Using model checking tools to triage the severity of security bugs in the Xen hypervisor. Formal Methods in Computer Aided Design