User profile

Ulrich Bodenhofer

Ulrich Bodenhofer

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Member since: March 14, 2006

Associate professor at Institute of Bioinformatics, Johannes Kepler University, Linz, Austria

Current address

Institute of Bioinformatics, Johannes Kepler University Linz
Altenbergerstr. 69
4040 LinzAustria

Education

MSc in Applied Mathematics
Johannes Kepler University Linz
1994 — 1996
PhD in Applied Mathematics
Johannes Kepler University Linz
1996 — 1998
Habilitation (venia docendi) in Mathematics of Knowledge-Based Systems
PhD in Applied Mathematics
1998 — 2003

Experience

Associate Professor
Institute of Bioinformatics, Johannes Kepler University Linz
2006
Associate Professor and Deputy Head of Dept.
Dept. of Knowledge-Based Math. Systems, Johannes Kepler University Linz
2003 — 2006
Scientific Director
Software Competence Center Hagenberg
2002 — 2006

Activities

  • Current president of the European Society for Fuzzy Logic and Technology
  • Member of IEEE (plus CIS and SMC sub-societies)
  • Member of editorial board of Fuzzy Sets and Systems
  • Member of program committees of numerous international conferences
  • Two best paper awards and two other scientific awards

Interests

  • Machine learning in bioinformatics
  • Fuzzy logic and fuzzy systems
  • Knowledge-based methods in image processing

References

U. Bodenhofer. A similarity-based generalization of fuzzy orderings preserving the classical axioms. Internat. J. Uncertain. Fuzziness Knowledge-Based Systems, 8(5):593-610, 2000

U. Bodenhofer and F. Klawonn. A formal study of linearity axioms for fuzzy orderings. Fuzzy Sets and Systems, 145(3):323-354, 2004

U. Bodenhofer and P. Bauer. Interpretability of linguistic variables: a formal account. Kybernetika, 41(2):227-248, 2005

M. Drobics, U. Bodenhofer, and W. Winiwarter. Mining clusters and corresponding interpretable descriptions - a three-stage approach. Expert Systems, 19(4):224-234, 2002

U. Bodenhofer, M. De Cock, and E. E. Kerre. Openings and closures of fuzzy preorderings: Theoretical basics and applications to fuzzy rule-based systems. Int. J. General Systems, 32(4):343-360, 2003

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