Curriculum Vita
Daewon, Lee, Ph.D.
School of Industrial Engineering Tel: +82-52-259-1029 University of Ulsan Fax: +82-52-259-2180
P.O.BOX 18, Ulsan 680-749 E-mail: [email protected]
Republic of Korea Web: http://sites.google.com/site/daewonlee
Research Interests
Theory and Algorithm
- Machine learning: Semi-supervised learning
- Kernel-based learning algorithm: structured output prediction, kernel similarity measure, sparse kernel machine
- Optimization in machine learning: support vector cluster labelling using nonlinear dynamics
Applications
- Biomedical application: medical image segmentation and registration (brain images, whole body images from different scanners)
- Chemometrics: predicting reduction ratio of iron ore using XRD spectra
- Data mining: measuring semantic similarity for XML schema matching, computational finance
Education Pohang University of Science and Technology (POSTECH), Pohang, Korea
Ph.D., Industrial and Management Engineering, February 2007 (Best thesis award)
• Dissertation Title: ”Equilibrium-Based Kernel Machines for Semi-Supervised Learning”
• Advisor: Jaewook Lee
Co-advisors: Chi-Hyuck Jun, Young-Gui Yoon, Sooyoung Kim, Hyun-Bo Cho
• GPA: 3.92/4.3 (Combined degree program)
POSTECH, Pohang, Korea
B.S., Industrial Engineering, February 2002
• GPA: 3.37/4.3
Honors and Awards
Post-doctoral Overseas Grant, Korea Research Foundation, 2008 Max Planck Grant, Max Planck Society, 2007
Geun-Soo Jang Award (It is awarded for the best PhD thesis of engineering at the university level), POSTECH, 2007
Best Session Presentation Award, 2006 World Congress on Computational Intelligence, 2006 SAS Excellent Student Paper Award, Korean Data Mining Society Conference, 2006
Best Paper Award, Korean Data Mining Society Conference, 2005
KOSEF Scholarship, Korea Science and Engineering Foundation (KOSEF), 2004 POSCO Scholarship, POSCO (Pohang Iron and Steel Company) Foundations, 2001 Rotary Club Scholarship, Pohang District, Rotary International, Korea, 2000
Academic Experiences
University of Ulsan, Ulsan, Republic of Korea
Max Planck Institute for Biological Cybernetics, T¨ubingen, Germany
- Research Scientist(Director: Bernhard Sch¨olkopf, Prof. Dr.) December, 2007 - August, 2009
research on medical image registration by using machine learning methods.
POSTECH, Pohang, Republic of Korea
- Postdoctoral researcher February, 2007 - November, 2007
carried out several research/consulting projects.
- Research Assistant March, 2002 - February, 2007
Assisted several projects on developing novel efficient machine learning algorithms by using non-linear global optimization methodologies.
- Teaching Assistant March, 2002 - February, 2007
Undergraduate and graduate teaching assistant
• Undergraduate course: computer applications in industrial engineering, linear engineering
• Graduate course: nonlinear programming, advanced topics in artificial intelligence, linear statistical model
- 2nd Undergraduate Student Research Program January - December, 2001
developed a Management System for Integrating Middle Markets.
- 1st Undergraduate Student Research Program January - December, 2000
developed a Web-based Statistical Analysis Application.
Professional Activities
Teaching
- Lecturer in undergraduate course Production management, Handong University, 2005.
Reviewer, including
- Pattern Recognition Letter, International Journal of Pattern Recognition and Artificial Intelli-gence, IE Interface, International Joint Conference on Neural Networks, International Journal of Management Science, Journal of Zhejiang University-SCIENCE A, Iranian Journal of Electrical and Computer Engineering,
Intern
- Pohang Iron and Steel Company, Pohang, Korea. July - August, 2001
Projects Development of a novel method for rapid determination of concentration ratio in iron ore by using
semi-supervised learning, Graduate Institute of Ferrous Technology (GIFT), POSTECH, Korea.
. January - December, 2007
Development of a new algorithm to separate noise/signal of OES data, POSCO, Korea.
. July - December, 2007
Development of global optimization system in search of transition states and its applications to real-world problems in large-scale, KOSEF, Korea. April, 2005 - present
Development of a trajectory-based kernel machine methodology and its application to feature ex-traction, KRF, Korea. December, 2005 - November, 2006
Development of an Efficient Jump Dynamics Algorithm for Solving Nonlinear Constraint Satisfaction Problems and Its Applications, KRF, Korea. June, 2004 - June, 2005
Effective Applications of Data Mining Techniques in the Steel Industry, Graduate Institute of Ferrous Technology (GIFT), Korea. January - December, 2004
Development of a Novel Efficient Global Optimization Methodology and Its Application to Pattern Analysis, KRF, Korea. December, 2003 - November, 2004
Development of a New Computational Method for Stability Region Estimate in Nonlinear Systems,
KRF, Korea. July, 2002 - June, 2003
Publications 5 Selected Papers
Lee, D., Hofmann, M., Steinke, F., Altun, Y., Cahill, N. and Sch¨olkopf, B. (2009.06), Learning Similarity Measure for Multi-Modal 3D Image Registration. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 09).
(One of the top conferences in machine learning and computer vision field. Acceptance rate: 4.1% for oral, 22.1% for poster.)
Lee, D., Jung, K.-H. and Lee, J. (2009.04) Constructing Sparse Kernel Machines Using Attractors.
IEEE Trans. on Neural Networks 20(4):721-729.
(IF=2.769 (JCR07), Ranking 7/227 in engineering, electrical & electronic category)
Lee, D. and Lee, J. (2007.03) Equilibrium-Based Support Vector Machine for Semi-Supervised Classification. IEEE Trans. on Neural Networks 18(2):578-583.
(IF=2.769 (JCR07), Ranking 7/227 in engineering, electrical & electronic category)
Lee, J. and Lee, D. (2006.11) Dynamic Characterization of Cluster Structures for Robust and Inductive Support Vector Clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence
28(11):1869-1874.
(IF=3.579 (JCR07), Ranking 2/227 in engineering, electrical & electronic category)
Lee, J. andLee, D.(2005.03) An Improved Cluster Labeling Method for Support Vector Clustering.
IEEE Trans. on Pattern Analysis and Machine Intelligence 27(3):461-464.
(IF=3.579 (JCR07), Ranking 2/227 in engineering, electrical & electronic category)
Refereed Journals
Jung, K.,Lee, D., and Lee, J. (2010) Fast Support Vector-based Clustering for Large-scale Appli-cations. Accepted toPattern Recognition.
Lee, D.and Lee, J. (2009.04) Dynamic Dissimilarity Measure for Support-based Clustering.
Accepted toIEEE Trans. on Knowledge and Data Engineering.
Lee, D., Jung, K.-H. and Lee, J. (2009.04) Constructing Sparse Kernel Machines Using Attractors.
IEEE Trans. on Neural Networks 20(4):721-729.
Jeong, B., Lee, D., Cho, H., and Lee, J. (2008.04) A Novel Method for Measuring Semantic Similarity for XML Schema Matching. Expert Systems With Applications 34(3): 1651-1658.
Lee, D., Lee, H., Jun, C.-H., and Chang, C.-H. (2007.12) A Variable Selection Procedure for X-ray Diffraction Phase Analysis. Applied Spectroscopy 61(12): 1398-1403.
Lee, D., Lee, J., and Yoon, Y.-G. (2007.07) A quadratic string adapted barrier exploring method for locating transition states. Computer Physics Communications 177(1-2): 218.
Lee, D. and Lee, J. (2007.03) Equilibrium-Based Support Vector Machine for Semi-Supervised Classification. IEEE Trans. on Neural Networks 18(2):578-583.
Lee, D. and Lee, J. (2007.01) Domain described support vector classifier for multi-classification problems. Pattern Recognition 40(1):41-51.
Jeong, B., Lee, D., Cho, H., and Kulvatunyou, B. (2007.07) A Kernel Method for Measuring Structural Similarity between XML Documents. Lecture Notes in Computer Science 4570(1): 572-581.
Lee, J. and Lee, D. (2006.11) Dynamic Characterization of Cluster Structures for Robust and Inductive Support Vector Clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence
28(11):1869-1874.
Kim, B.-H.,Lee, D., and Lee, J. (2006.05) Local Volatility Function Approximation Using Recon-structed Radial Basis Function Networks. Lecture Notes in Computer Science 3973:524-530.
Cho, C., Kim, S., Lee, J., and Lee, D. (2006.03) A Tandem Clustering Process for Multimodal Datasets. European Journal of Operational Research 168(3):998-1008.
Lee, J. andLee, D.(2005.03) An Improved Cluster Labeling Method for Support Vector Clustering.
IEEE Trans. on Pattern Analysis and Machine Intelligence 27(3):461-464.
Lee, D. and Lee, J. (2005.05) Trajectory-Based Support Vector Multicategory Classifier. Lecture Notes in Computer Science 3496:857-861.
Han, G.-S., Lee, D., and Lee, J. (2005.05) Estimating the Yield Curve Using Calibrated Radial Basis Function Networks. Lecture Notes in Computer Science 3497:885-890.
Lee, D., Choi, H.-J., and Lee, J. (2004.08) A Regularized Line Search Tunneling for Efficient Neural Network Learning. Lecture Notes in Computer Science3173:239-243.
Lee, D. and Lee, J. (2004.08) A Novel Three-Phase Algorithm for RBF Neural Network Center Selection. Lecture Notes in Computer Science 3173:350-355.
Lee, H.-S.,Lee, D., and Lee, J. (2004.07) Multi-stage Neural Networks for Channel Assignment in Cellular Radio Networks. Lecture Notes in Computer Science3174:287-292.
Lee, D. and Lee, J. (2003.06) Determining the Number and the Locations of RBF Centers Using Enhanced K-Medoids Clustering and Bi-Section Search Method. Journal of Korean Institute of Industrial Engineers 29(2):172-178.
Lee, D., Hofmann, M., Steinke, F., Altun, Y., Cahill, N. and Sch¨olkopf, B. (2009.06), Learning Similarity Measure for Multi-Modal 3D Image Registration. Accepted toIEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 09).
Jeong, B.,Lee, D., Lee, J., and Cho, H. (2006) Towards XML Mining: The Role of Kernel Methods.
Proceedings of the 2006 Fall Korean Data Mining Conference. Seoul, Korea. (SAS Excellent Student Paper Award)
Lee, D. and Lee, J. (2006) Support Vector Classifier Using Basin-Based Sampling for Security Assessment of Nonlinear Power and Control Systems. IEEE International Joint Conference on Neural Networks. (Best Session Presentation Award)
Lee, D. and Lee, J. (2006) A Novel Semi-Supervised Learning Methods Using Support Vector Domain Description. IEEE International Joint Conference on Neural Networks.
Lee, D., Lee, H.-S., Yun, H.-K., and Lee, J. (2004) A Novel Two-Phase Algorithm for Efficient Channel Assignment in Cellular Mobile Networks. 33rd International Conference on Computers and Industrial Engineering.
Chang, C.-H., Seo, J.-H., Lee, H., Lee, D., and Jun, C.-H. (2006) Quantitative XRD Analysis of Iron Ore by Using Partial Least Squares. Korean Society of Analytical Sciences.
Jun, C.-H., Lee, H., Lee, D., and Chang, C.-H. (2006) Prediction of Reduction Ratio of Iron Ore by Using Partial Least Squares. Korean Statistical Society.
Lee, D.and Lee, J. (2005) Trajectory-Based Support Vector Machine for Multi-Classification Prob-lems. Proceedings of the 2005 Fall Korean Data Mining Conference. Seoul, Korea. (SAS Excellent Student Paper Award)
Kim, B.-H., Jung, K.-H., Lee, D., and Lee, J. (2005) Comparative study of surface estimation method for volatility approximation. Korean Institute of Industrial Engineers.
Jung, K.-H., Lee, J., Lee, D., and Kim, B.-H. (2005) TV Audience Forecast Modeling and Study for Its Strategic Use Using Korean TV Market Data. Korean Operations Research and Management Science Society.
Lee, D., Kim, S.-H., Kim, K.-J., and Lee, J. (2004) The Study of Adjusting the Cost Matrix in Loss Function Approach for Multiresponse Optimization. Korean Operations Research and Management Science Society.
Han, G.-S., Lee, D., and Lee, J. (2004) A Homotopy Method for Solving Nonlinear Optimiza-tion Problems. Korean Operations Research and Management Science Society/Korean Institute of Industrial Engineers.
Lee, D. and Lee, J. (2003) Two-Phase Algorithm for Determining the Number and the Location of RBF Centers. Korean Operations Research and Management Science Society/Korean Institute of Industrial Engineers.
Lee, D. and Lee, J. (2002) A Systematic Search Method for Determining the Number of RBF Network Centers. Korean Institute of Industrial Engineers.
Lee, D., and Lee, J. Method and apparatus for multi-class classification using support vector domain description, and computer-readable storage medium used thereto, Korean Patent 10-0842215-0000, June 24, 2008.
References Jaewook Lee(Advisor of Ph.D. thesis) Associate Professor, Ph.D.
Department of Industrial and Management Engineering, POSTECH E-mail: [email protected]
Phone: +82-54-279-2209
Chi-Hyuck Jun (Co-advisor of Ph.D. thesis) Professor, Ph.D.
Department of Industrial and Management Engineering, POSTECH E-mail: [email protected]
Phone: +82-54-279-2197
Bernhard Sch¨olkopf(Director at the dept Empirical Inference, MPI for Biological Cybernetics) Professor, Dr.
Department of Empirical Inference, Max Planck Institute for Biological Cybernetics E-mail: [email protected]
