Wolfgang Faber

Wolfgang Faber is a researcher at Vienna University of Technology (TU Wien) specializing in Knowledge-Based Systems within the Faculty of Informatics. Holding the position of Privatdozent, he has completed his habilitation and is qualified to teach at the university level. His academic work centers on Answer Set Programming (ASP), Logic Programming, and Knowledge Representation, with significant contributions to theoretical foundations in these fields.

Dr. Faber's research spans multiple areas of computational logic:

• Answer Set Programming and its theoretical underpinnings
• Epistemic logic programs and equivalence properties
• Knowledge representation and reasoning systems
• Nonmonotonic reasoning formalisms
• Integration of logic programming with external data sources

His publication history reveals a sustained focus on theoretical aspects of ASP, with particular emphasis on program equivalence concepts (strong equivalence, uniform equivalence), computational complexity analysis, and applications to knowledge representation. Over two decades, his research has evolved from foundational work in disjunctive logic programming to specialized topics in epistemic reasoning within ASP frameworks.

Dr. Faber has led and participated in numerous research projects including START (2014-2022) on Uniform Equivalence of Epistemic Logic Programs, SemDat (2012-2016), and multiple projects related to hybrid knowledge bases and Answer Set Programming from 2005-2015.

His collaborative research extends across European institutions, evident through extensive co-authorship with researchers like Thomas Eiter and Stefan Woltran. While specific awards aren't documented in the available information, his sustained research output and leadership in multiple projects indicate significant recognition within his field.

Dr. Faber has made substantial contributions to major systems in the field, most notably the DLV system for knowledge representation and reasoning, which has influenced both academic research and practical applications of Answer Set Programming.