Mustafa Bilgic PhD candidate in Computer Science, University of Maryland at College Park. M.S. in Computer Science, University of Maryland at College Park, 2006 B.S. in Computer Sciences, University of Texas at Austin, 2004

Research Interests

My main research interests are in the broad areas of machine learning, data mining, social network analysis, and information acquisition. Specifically, I am interested statistical relational learning, probabilistic graphical models, collective classification, active feature-value acquisition, active learning, active inference, decision theory, decision support, and visualization. More detailed information is iavailable in my CV (in pdf).

Publications

• Patents

  • Lise Getoor, Mustafa Bilgic, Louis Licamele, and Ben Shneiderman. D-Dupe: A Visual Interface for Relational DeDuplication. Provisional Patent submitted by University of Maryland.

• Journal Articles

  • Mustafa Bilgic and Lise Getoor. Reflect and Correct: A Misclassification Prediction Approach to Active Inference. ACM Transactions and Knowledge Discovery from Data (TKDD), vol.3, no.4, November 2009.

  • Hyunmo Kang, Lise Getoor, Ben Shneiderman, Mustafa Bilgic, and Louis Licamele. Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation. IEEE Transactions on Visualization and Computer Graphics (TVCG), vol.14, no.5, pp.999-1014, 2008.

• Refereed Magazine Articles

  • Prithviraj Sen, Galileo Mark Namata, Mustafa Bilgic, Lise Getoor, Brian Gallagher, and Tina Eliassi-Rad. Collective Classification in Network Data. AI Magazine, vol.29, no.3, 2008.

• Book Chapters

  • Galileo Mark Namata, Prithviraj Sen, Mustafa Bilgic, and Lise Getoor. Collective Classification for Text Classification. Text Mining: Classification, Clustering, and Applications. Ashok Srivastava and Mehran Sahami (eds.), 2009.

• Conference Papers

  • Mustafa Bilgic, Lise Getoor. Effective Label Acquisition for Collective Classification. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008. Best Student Paper Award Winner. VideoLectures Link

  • Mustafa Bilgic, Lise Getoor. VOILA: Efficient Feature-value Acquisition for Classification. Twenty-Second Conference on Artificial Intelligence (AAAI), 2007.

  • Mustafa Bilgic, Louis Licamele, Lise Getoor, and Ben Shneiderman. D-Dupe: An Interactive Tool for Entity Resolution in Social Networks. In Visual Analytics Science and Technology (VAST), 2006.

  • Mustafa Bilgic, Louis Licamele, Lise Getoor, and Ben Shneiderman. D-Dupe: An Interactive Tool for Entity Resolution in Social Networks. In International Symposium on Graph Drawing (GD), 2005.

• Workshop Papers

  • Mustafa Bilgic and Lise Getoor. Link-based Active Learning. In NIPS Workshop on Analyzing Networks and Learning with Graphs, 2009.

  • Daozheng Chen, Mustafa Bilgic, Lise Getoor, and David Jacobs. Efficient Resource-constrained Retrospective Analysis of Long Video Sequences. In NIPS Workshop on Adaptive Sensing, Active Learning and Experimental Design: Theory, Methods and Applications, 2009.

  • Mustafa Bilgic, Galileo Mark Namata, and Lise Getoor. Combining Collective Classification and Link Prediction. In IEEE ICDM Workshop on Mining Graphs and Complex Structures (MGCS), 2007.

  • Louis Licamele, Mustafa Bilgic, Lise Getoor, and Nick Roussopoulos. Capital and Benefit in Social Networks. In ACM SIGKDD Workshop on Link Analysis and Group Detection (LinkKDD), 2005.

  • Mustafa Bilgic and Raymond J Mooney. Explaining Recommendations: Satisfaction vs Promotion. In Proceedings of Beyond Personalization: A Workshop on the Next Stage of Recommender Systems Research at the International Conference on Intelligent User Interfaces, 2005.

• Technical Reports

  • Prithviraj Sen, Galileo Mark Namata, Mustafa Bilgic, Lise Getoor, Brian Gallagher, and Tina Eliassi-Rad. Collective Classification in Network Data. Technical Report, University of Maryland, College Park, 2008.

• Undergraduate Honor Thesis

  • Mustafa Bilgic. Explanation for Recommender Systems: Satisfaction vs Promotion. Undergraduate Honor Thesis, Department of Computer Sciences, University of Texas at Austin, 2004.

• Under Review

  • Dynamic Processing Allocation in Video. Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI).

Courses

• Machine Learning (Lise Getoor)
• Statistical Relational Learning (Lise Getoor)
• Link Mining (Lise Getoor)
• Natural Language Processing (Philip Resnik)
• Pattern Recognition (Rama Chellappa)
• Knowledge Discovery and Data Mining (Joseph JaJa)
• Database Management Systems (Nick Roussopoulos)
• Information Visualization (Ben Shneiderman)
• Image Segmentation (David Jacobs)
• Approximation Algorithms (Samir Khuller)
• Computers and Games (Clyde Kruskal)
• How to Do Reseach (Clyde Kruskal)

Contact

3228 AV Williams Building
University of Maryland
College Park, MD 20742

mbilgic AT cs.umd.edu

Links

Lise Getoor

LINQS Research Group

Last updated on Nov 16, 2009.