I am a senior research scientist in the Department of Computational Biology of the Sage Bionetworks.

I was a post-doctoral researcher in the Statistical Machine Learning and Bioinformatics group of the Department of Information and Computer Science of the Aalto University School of Science and the Helsinki Institute for Information Technology.

  • Address: 1100 Fairview Ave North, M1-C108
    Seattle, WA 98109-1024
  • Phone: +1 (206) 667 6641
  • Email: name.surname@sagebase.org

Research Interests

  • machine learning (kernel methods, Bayesian methods)
  • computational biology (cancer biology, personalized medicine)

Publications

Recent Publications

Journal Publications

  1. M. Gönen and S. Kaski. Kernelized Bayesian Matrix Factorization, IEEE Transactions on Pattern Analysis and Machine Intelligence, in press.
  2. J. C. Costello, L. M. Heiser, E. Georgii, M. Gönen, M. P. Menden, N. J. Wang, M. Bansal, M. Ammad-ud-din, P. Hintsanen, S. A. Khan, J.-P. Mpindi, NCI Dream Community, O. Kallioniemi, A. Honkela, T. Aittokallio, K. Wennerberg, J. J. Collins, D. Gallahan, D. Singer, J. Saez-Rodriguez, S. Kaski, J. W. Gray, and G. Stolovitzky. A Community Effort to Assess and Improve Drug Sensitivity Prediction Algorithms, Nature Biotechnology, in press.
  3. M. Kandemir, A. Vetek, M. Gönen, A. Klami, and S. Kaski. Multi-Task and Multi-View Learning of User State, Neurocomputing, in press.
  4. M. Gönen. Coupled Dimensionality Reduction and Classification for Supervised and Semi-Supervised Multilabel Learning, Pattern Recognition Letters, 38:132-141, 2014.
  5. M. Gönen. Bayesian Supervised Dimensionality Reduction, IEEE Transactions on Cybernetics, 43(6):2179-2189, 2013.
  6. M. Gönen. Supervised Multiple Kernel Embedding for Learning Predictive Subspaces, IEEE Transactions on Knowledge and Data Engineering, 25(10):2381-2389, 2013.
  7. M. Gönen and E. Alpaydın. Localized Algorithms for Multiple Kernel Learning, Pattern Recognition, 46(3):795-807, 2013.
  8. M. Gönen. Predicting Drug–Target Interactions from Chemical and Genomic Kernels Using Bayesian Matrix Factorization, Bioinformatics, 28(18):2304-2310, 2012.
  9. G. Bozkurt Gönen, M. Gönen, and F. Gürgen. Probabilistic and Discriminative Group-Wise Feature Selection Methods for Credit Risk Analysis, Expert Systems with Applications, 39(14):11709-11717, 2012.
  10. M. Gönen and E. Alpaydın. Multiple Kernel Learning Algorithms, Journal of Machine Learning Research, 12(Jul):2211-2268, 2011.
  11. M. Gönen and E. Alpaydın. Regularizing Multiple Kernel Learning Using Response Surface Methodology, Pattern Recognition, 44(1):159-171, 2011.
  12. M. Gönen and E. Alpaydın. Supervised Learning of Local Projection Kernels, Neurocomputing, 73(10-12):1694-1703, 2010.
  13. M. Gönen and E. Alpaydın. Cost-Conscious Multiple Kernel Learning, Pattern Recognition Letters, 31(9):959-965, 2010.
  14. A. Özen, M. Gönen, E. Alpaydın, and T. Haliloğlu. Machine Learning Integration for Predicting the Effect of Single Amino Acid Substitutions on Protein Stability, BMC Structural Biology, 9:66, 2009.
  15. M. Gönen, A. G. Tanuğur, and E. Alpaydın. Multiclass Posterior Probability Support Vector Machines, IEEE Transactions on Neural Networks, 19(1):130-139, 2008.

Conference Publications

  1. M. Gönen and A. A. Margolin. Kernelized Bayesian Transfer Learning, In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI 2014), Québec City, Québec, Canada, 2014.
  2. H. Zhang, Z. Yang, M. Gönen, M. Koskela, J. Laaksonen, T. Honkela, and E. Oja. Affective Abstract Image Classification and Retrieval Using Multiple Kernel Learning, In Proceedings of the 20th International Conference on Neural Information Processing (ICONIP 2013), Daegu, Korea, 2013.
  3. H. Zhang, M. Gönen, Z. Yang, and E. Oja. Predicting Emotional States of Images Using Bayesian Multiple Kernel Learning, In Proceedings of the 20th International Conference on Neural Information Processing (ICONIP 2013), Daegu, Korea, 2013.
  4. M. Gönen, S. A. Khan, and S. Kaski. Kernelized Bayesian Matrix Factorization, In Proceedings of the 30th International Conference on Machine Learning (ICML 2013), Atlanta, Georgia, USA, 2013.
  5. M. Gönen. A Bayesian Multiple Kernel Learning Framework for Single and Multiple Output Regression, In Proceedings of the 20th European Conference on Artificial Intelligence (ECAI 2012), Montpellier, France, 2012.
  6. M. Gönen. Bayesian Efficient Multiple Kernel Learning, In Proceedings of the 29th International Conference on Machine Learning (ICML 2012), Edinburgh, Scotland, UK, 2012.
  7. M. Gönen. Bayesian Supervised Multilabel Learning with Coupled Embedding and Classification, In Proceedings of the 12th SIAM International Conference on Data Mining (SDM 2012), Anaheim, California, USA, 2012.
  8. M. Gönen, M. Kandemir, and S. Kaski. Multitask Learning Using Regularized Multiple Kernel Learning, In Proceedings of the 18th International Conference on Neural Information Processing (ICONIP 2011), Shanghai, China, 2011.
  9. M. Gönen and E. Alpaydın. Localized Multiple Kernel Regression, In Proceedings of the 20th IAPR International Conference on Pattern Recognition (ICPR 2010), İstanbul, Turkey, 2010.
  10. M. Gönen and E. Alpaydın. Multiple Kernel Machines Using Localized Kernels, In Supplementary Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2009), Sheffield, England, 2009.
  11. M. Gönen and E. Alpaydın. Localized Multiple Kernel Learning, In Proceedings of the 25th International Conference on Machine Learning (ICML 2008), Helsinki, Finland, 2008.
  12. Ü. Bilge, A. Polat, Y. Tunç, and M. Gönen. Real-Time Shop Floor Control Implementations in BUFAIM Model Factory, In Proceedings of the 15th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2005), Bilbao, Spain, 2005.

Workshop Publications

  1. M. Gönen, M. Ammad-ud-din, S. A. Khan, and S. Kaski. Kernelized Bayesian Matrix Factorization, NIPS Workshop on Machine Learning in Computational Biology, Lake Tahoe, Nevada, USA, 2013.
  2. A. Ulaş, M. Gönen, U. Castellani, V. Murino, M. Bellani, M. Tansella, and P. Brambilla. A Localized MKL Method for Brain Classification with Known Intra-Class Variability, In Proceedings of the 3rd International Workshop on Machine Learning in Medical Imaging, Nice, France, 2012.
  3. M. Gönen, A. Ulaş, P. J. Schüffler, U. Castellani, and V. Murino. Combining Data Sources Nonlinearly for Cell Nucleus Classification of Renal Cell Carcinoma, In Proceedings of the 1st International Workshop on Similarity-Based Pattern Analysis and Recognition, Venice, Italy, 2011.
  4. M. Gönen and E. Alpaydın. Supervised and Localized Dimensionality Reduction from Multiple Feature Representations or Kernels, NIPS Workshop on New Directions in Multiple Kernel Learning, Whistler, British Columbia, Canada, 2010.
  5. M. Gönen and E. Alpaydın. Localized Multiple Kernel Machines for Image Recognition, NIPS Workshop on Understanding Multiple Kernel Learning Methods, Whistler, British Columbia, Canada, 2009.

Technical Reports

  1. M. Gönen and E. Alpaydın. Multiple Kernel Learning Algorithms, Boğaziçi University Technical Report, FBE-CMPE-05/2009-02, İstanbul, Turkey, 2009.

Education

Ph.D. in Computer Engineering - Boğaziçi University (2005-2010)

M.Sc. in Computer Engineering - Boğaziçi University (2003-2005)

B.Sc. in Industrial Engineering - Boğaziçi University (1998-2003)

  • Senior Project: Design of a Distance-Based Computer Integrated Manufacturing Course
  • Supervisor: Prof. Ümit Bilge

Teaching

Lectured Courses in Aalto University

  • T-61.6040 Machine Learning with Kernels (Fall'11) (This course has been awarded by the Aalto University School of Science according to student feedbacks.)
  • T-61.9910 Predicting Structured Data with Kernel Methods (Spring'12)

Assisted Courses in Boğaziçi University

  • CmpE150 Introduction to Computing (Summer'07, Spring'08, Spring'09)
  • CmpE160 Introduction to Object Oriented Programming (Spring'07)
  • CmpE210 Fundamentals of Object Oriented Programming (Spring'09)
  • CmpE343 Introduction to Probability and Statistics for Computer Engineers (Fall'07, Fall'08, Fall'09, Spring'10)
  • CmpE463 Data Mining (Spring'07)
  • IE201 Intermediate Programming (Fall'04, Fall'05, Fall'06)
  • IE312 Facilities Design and Planning (Spring'06)
  • IE414 Computer Integrated Manufacturing System (Spring'04, Spring'06)
  • IE486 Flexible Manufacturing (Fall'05)