Frank Eichinger

Dr. Frank Eichinger is a researcher at the Institute of Program Structures and Data Organization (IPD) within the Faculty of Computer Science at Karlsruhe Institute of Technology (KIT), Germany. He works under the Chair of Prof. Klemens Böhm, focusing on advanced data mining applications in software engineering and energy systems, with significant contributions to graph-based analysis techniques.

Education:

• PhD in Computer Science, Karlsruhe Institute of Technology (KIT), 2011

Research Interests: Eichinger's work centers on graph mining for software defect localization, particularly through call-graph analysis in multicore and multithreaded environments. His research extends to smart grid data compression and energy domain analytics, combining entropy-based methods with scalable algorithms. Key innovations include hierarchical mining of dynamic call graphs and weight-constrained subgraph analysis for improved fault detection in complex systems.

Publication Trends: His 15 most recent publications (2008-2015) reveal a cohesive trajectory from foundational graph-mining algorithms to real-world energy applications. Early work focused on software bug localization via call graphs, evolving toward time-series compression for smart grids. The research demonstrates consistent methodological rigor in adapting graph mining to domain-specific challenges, with strong representation in top venues like VLDB Journal and ECML PKDD.

Scientific Awards:

• No awards documented in source material

Advising and Grants: While specific student supervision details are absent, his dissertation role and collaborative publications indicate mentorship activities. Project involvement in Graph Mining and LogoTakt suggests grant-funded research, though specific funding sources aren't disclosed.

Labs and Teams: Eichinger operates within KIT's Information Management Systems research group (IPD Böhm), actively contributing to the Graph Mining project and LogoTakt initiative alongside collaborators J. Mülle and M. Bracht. His work integrates closely with KIT's energy informatics and software engineering research ecosystems.