Prof. Dr. Christian Bauckhage

Christian Bauckhage is professor of Computer Science at the Bonn-Aachen International Center for Information Technology (b-it) and also a scientist researching multimedia pattern recognition at the Fraunhofer IAIS. In 1998 he graduated in Computer Science following his studies in Bielefeld and Grenoble; in 2002 he obtained his doctorate (Dr.-Ing.) in Bielefeld where he subsequently coordinated a successful EU research project on Cognitive Vision. From 2004 to 2008 Christian Bauckhage was involved in research at the Center for Vision Research at York University in Toronto and in the Deutsche Telekom Laboratories in Berlin. He is the author of a number of published scientific papers in Computer Vision, Pattern Recognition, Advanced HCI and Behavior Analysis and regularly acts as an assessor for conferences and journals as well as for the European Union’s IST program.

  • efficient, real-time image and video analysis 
  • user modeling and behavior recognition
  • online communities and social media
  • web science and web mining
  • game AI and game mining

Web Science / Web Mining

C. Ojeda, K. Cvejoski, R. Sifa, C. Bauckhage. Inverse Dynamical Inheritance in Stack Exchange Taxonomies. Proc. AAAI Int. Conf. on Web and Social media, 2017

C. Bauckhage, F. Hadiji, and K. Kersting. How Viral Are Viral Videos?. Proc. AAAI Int. Conf. on Weblogs and Social Media, 2015

C. Bauckhage, K. Kersting, and B. Rastegarpanah. Collective Attention to Social Media Evolves According to Diffusion Models. Proc. ACM Int. World Wide Web Conf., 2014

C. Bauckhage and K. Manshaei. Kernel Archetypal Analysis for Clustering Web Search Frequency Time Series. Proc. IAPR Int. Conf. on Pattern Recognition, IEEE, 2014

C. Bauckhage, K. Kersting, and F. Hadiji. Mathematical Models of Fads Explain the Temporal Dynamics of Internet Memes. Proc. AAAI Int. Conf. on Weblogs and Social Media, 2013

C. Bauckhage and K. Kersting. Can Computers Learn from the Aesthetic Wisdom of the Crowd? KI - Künstliche Intelligenz, 27(1), 2013

C. Bauckhage. Insights into Internet Memes. Proc. AAAI Int. Conf. on Weblogs and Social Media, 2011

R. Wetzker, C. Zimmermann, C. Bauckhage, and S. Albayrak. I Tag, You Tag: Translating Tags for Advanced User Models. Proc. ACM Int. Conf. on Web Search and Data Mining, 2010

J. Kunegis, A. Lommatzsch, and C. Bauckhage. The Slashdot Zoo: Mining a Social Network with Negative Edges. Proc. ACM Int. World Wide Web Conf., 2009

Machine Learning / Applied AI

R. Sifa and C. Bauckhage. Online k-Maxoids Clustering. Proc. IEEE Int. Conf.  on  Data Science and Advanced Analytics,  2017

C. Bauckhage. A Neural Network Implementation of Frank-Wolfe Optimization. Proc. Int. Conf on Artificial Neural Networks, 2017

R. Ramamurthy, C. Bauckhage, K. Buza, and S. Wrobel. Using Echo State Networks for Cryptography. Proc. Int. Conf on Artificial Neural Networks, 2017

C. Bauckhage and K. Kersting. Data Mining and Pattern Recognition in Agriculture. KI - Künstliche Intelligenz, 27(4), 2013

C. Bauckhage, K. Kersting, and A. Schmit. Agriculture's Technological Makeover. IEEE Pervasive Computing, 11(2), 2012

C. Thurau, K. Kersting, M. Wahabzada, and C. Bauckhage. Descriptive Matrix Factorization for Sustainability: Adopting the Principle of Opposites. Data Mining and Knowledge Discovery, 24(2), 2012

C. Thurau, K. Kersting, M. Wahabzada, and C. Bauckhage. Convex Non-negative Matrix Factorization for Massive Datasets. Knowledge and Information Systems, 29(2), 2011

C. Thurau, K. Kersting, and C. Bauckhage. Yes We Can: Simplex Volume Maximization for Descriptive Web-scale Matrix Factorization. Proc. ACM Conf. on Information and Knowledge Management, 2010

C. Bauckhage and C. Thurau. Making Archetypal Analysis Practical, Proc. DAGM Symposium, 2009

Computer Vision

S. Zhang, D.A. Klein, C. Bauckhage, and A.B. Cremers. Fast Moving Pedestrian Detection Based on Motion Segmentation and New Motion Features. Multimedia Tools and Applications, 2015

S. Zhang, C. Bauckhage, and A.B. Cremers. Efficient Pedestrian Detection via Rectangular Features Based on a Statistical Shape Model. IEEE Trans. Intelligent Transportation Systems, 16(2), 2015

G. Evangelidis and C. Bauckhage. Efficient Subframe Video Alignment using Short Descriptors. IEEE Trans. Pattern Analysis and Machine Intelligence, 35(10), 2013

B. Krausz and C. Bauckhage. Loveparade 2010: Automatic video analysis of a crowd disaster. Computer Vision and Image Understanding, 116(3), 2012

C. Bauckhage, J.K. Tsotsos, and F.E. Bunn. Automatic Detection of Abnormal Gait. Image and Vision Computing, 27(1-2), 2009