Fachgebietsleiter für KI at Technische Universität Ilmenau, Germany
Rainer Knauf is an apl. Prof. Dr.-Ing. habil., currently serving as the Chair of Artificial Intelligence at the Faculty of Computer Science and Automation, Technical University Ilmenau, Germany. He earned his Diploma Engineer (Dipl.-Ing.) in Electrical and Computer Engineering in 1987, followed by a Doctor of Engineering (Dr.-Ing.) in Computer Engineering in 1990, and a Doctor of Engineering habilitatus (Dr.-Ing. habil.) in Computer Science in 2000, all from Technical University Ilmenau. His research focuses on knowledge acquisition, validation, and refinement of intelligent systems, inductive inference, and machine learning.
🎓 Education:
- Dipl.-Ing. in Electrical and Computer Engineering
Technical University Ilmenau, Germany
📅 February 5, 1987
- Dr.-Ing. in Computer Engineering
Technical University Ilmenau, Germany
📅 September 25, 1990
Dissertation: “Applying Logic Programming to Design Knowledge Based Systems for Diagnostic Problems”
- Dr.-Ing. habil. in Computer Science
Technical University Ilmenau, Germany
📅 November 15, 2000
Habilitation: “Validating Rule Based Systems: A Complete Methodology”
💼 Professional Experience:
- Full Professor (apl. Prof.)
Chair of Artificial Intelligence, Technical University Ilmenau
📅 March 2010 – Present
- Associate Professor (Privatdozent)
Chair of Artificial Intelligence, Technical University Ilmenau
📅 April 2004 – February 2010
- Assistant Professor (Privatdozent)
Technical University Ilmenau
📅 December 2000 – March 2004
- Scientific Assistant
Technical University Ilmenau
📅 September 1991 – November 2000
- Scientific Associate
Ilmenau Institute of Technology
📅 March 1987 – August 1991
🏅 Awards & Recognitions
- Fellowship Awards from the Japan Society for the Promotion of Science 📜 (2008, 2011, 2015)
- Graduate Faculty Scholar at the University of Central Florida 🎓 (2010)
Research Focus: Evolutionary Algorithms 🧬💡
Research Interests:
- Optimization and Search Algorithms: Rainer Knauf’s work in evolutionary algorithms involves developing and improving algorithms for optimization and search problems. These algorithms are inspired by the principles of natural selection and genetics.
- Artificial Intelligence Applications: He applies evolutionary algorithms to various AI challenges, including machine learning, robotics, and automated reasoning.
- Knowledge Acquisition and Refinement: His research integrates evolutionary algorithms with knowledge-based systems to enhance the processes of knowledge acquisition, validation, and refinement.
- Data Mining: Knauf explores the use of evolutionary algorithms in data mining, particularly in extracting meaningful patterns and insights from large datasets.
- Inductive Inference: His work also includes using evolutionary algorithms for inductive inference, aiming to generalize from specific data to broader rules or patterns.
Citation:
Cited by:
- All: 1082 citations
- Since 2019: 253 citations
h-index:
- Overall: 16
- Since 2019: 7
i10-index:
- Overall: 33
- Since 2019: 4
Publication Top Notes:
- “Didactic design through storyboarding: Standard concepts for standard tools”
- Authors: KP Jantke, R Knauf
- Publication: Proceedings of the 4th International Symposium on Information and Communication Technologies
- Citations: 122 (2005)
- Summary: This paper explores the use of storyboarding as a method for didactic design, emphasizing standard concepts to standardize tools for educational purposes.
- “A framework for validation of rule-based systems”
- Authors: R Knauf, AJ Gonzalez, T Abel
- Publication: IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
- Citations: 80 (2002)
- Summary: This paper presents a comprehensive framework for validating rule-based systems, addressing the need for systematic validation processes in artificial intelligence.
- “Validation of human behavior representation”
- Authors: SY Harmon, VB Barr, AJ Gonzalez, DC Hoffmann, R Knauf
- Publication: University Library
- Citations: 45 (2006)
- Summary: The authors discuss methodologies for validating models of human behavior representation, crucial for developing reliable AI systems that simulate human actions.
- “Modeling didactic knowledge by storyboarding”
- Authors: R Knauf, Y Sakurai, S Tsuruta, KP Jantke
- Publication: Journal of Educational Computing Research
- Citations: 39 (2010)
- Summary: This research focuses on the use of storyboarding to model didactic knowledge, enhancing the design and delivery of educational content through structured visual methods.
- “Toward reducing human involvement in validation of knowledge-based systems”
- Authors: R Knauf, S Tsuruta, AJ Gonzalez
- Publication: IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans
- Citations: 25 (2006)
- Summary: This paper proposes methods to minimize human intervention in the validation process of knowledge-based systems, aiming for more autonomous and efficient validation techniques.
- “Tweet credibility analysis evaluation by improving sentiment dictionary”
- Authors: T Kawabe, Y Namihira, K Suzuki, M Nara, Y Sakurai, S Tsuruta, R Knauf
- Publication: 2015 IEEE Congress on Evolutionary Computation (CEC)
- Citations: 24 (2015)
- Summary: This work evaluates the credibility of tweets by enhancing sentiment dictionaries, leveraging evolutionary computation techniques to improve the accuracy of sentiment analysis.
- “A simple optimization method based on backtrack and GA for delivery schedule”
- Authors: Y Sakurai, K Takada, N Tsukamoto, T Onoyama, R Knauf, S Tsuruta
- Publication: 2011 IEEE Congress of Evolutionary Computation (CEC)
- Citations: 22 (2011)
- Summary: The authors present an optimization method combining backtracking and genetic algorithms (GA) to improve delivery scheduling, demonstrating the application of evolutionary algorithms in logistics.
- “Generation of a minimal set of test cases that is functionally equivalent to an exhaustive set, for use in knowledge-based system validation”
- Authors: T Abel, R Knauf, AJ Gonzalez
- Publication: Proceedings of the 9th FLAIRS Conference
- Citations: 22 (1996)
- Summary: This paper discusses a method for generating a minimal set of test cases that maintains functional equivalence to an exhaustive set, enhancing the efficiency of knowledge-based system validation.
- “Modeling academic education processes by dynamic storyboarding”
- Authors: Y Sakurai, S Dohi, S Tsuruta, R Knauf
- Publication: Journal of Educational Technology & Society
- Citations: 21 (2009)
- Summary: The study models academic education processes through dynamic storyboarding, offering a structured approach to designing and implementing educational curricula.
- “Validating Rule-Based Systems: A Complete Methodology”
- Author: R Knauf
- Publication: Shaker
- Citations: 21 (2000)
- Summary: This book provides a comprehensive methodology for the validation of rule-based systems, detailing systematic approaches to ensure the reliability and accuracy of these systems.