Dr. rer. nat. habil. Johann Schumann is a member of the Robust Software Engineering Group RSE at NASA Ames where he is involved in several projects on verification and deductive software synthesis. He obtained his habilitation degree (2000) from the Technische Universität München, Germany on application of automated theorem provers in Software Engineering. His PhD thesis (1991) was on high-performance parallel theorem provers. He is currently working on deductive synthesis of UML statecharts, of avionics-related software and of data-analysis programs from Bayesian nets. His research interests lie in the application of formal methods to improve design and reliability of safety- and security-critical software, and on the validation of adaptive systems (e.g., Neural Networks). He is author of a book on theorem proving in software engineering and numerous articles on automated deduction and its applications.
He is employed by RIACS
J. Schumann and Yan Liu, editors Applications of Neural Networks in High Assurance Systems. Studies in Computational Intelligence, Springer Verlag, 2010.
J. Schumann Automated Theorem Proving in Software Engineering. ISBN 3-540-67989-8. Springer Verlag, 2001.
Intelligent Systems Division
Ames Research Center
Mail Stop 269-3
Moffett Field, CA 94035