U Kang - Data mining

1 1 U Kang Associate Professor Department of Computer Science and Engineering Seoul National University Office : (+82). 1 Gwanak-ro, Gwanak-gu, Seoul Republic of Korea 08826 ~ukang RESEARCH INTERESTS Deep Learning, mining Graphs/Tensors, Recommender System, and Financial AI EDUCATION Computer Science, Carnegie Mellon University 2012 Dissertation: mining Tera-Scale Graphs: Theory, Engineering and Discoveries Advisor: Professor Christos Faloutsos Information Technology, Carnegie Mellon University 2009 Computer Science and Engineering, Seoul National University 2003 AWARDS AND HONORS 1.

2 Best Student Paper Award at Pacific-Asia Conference on Knowledge Discovery and Data mining 2020 2. 10-year Highest Impact Paper Award from IEEE International Conference on Data mining (ICDM) 2018 3. Young Information Scientist Award from Korean Institute of Information Scientists and Engineers 2016 4. Ewon Assistant Professor from KAIST 2014 5. 10 Best Research Award from KAIST 2013 6. SIGKDD Doctoral Dissertation Award, Honorable Mention 2013 7. New Faculty Award from Microsoft Research Asia 2013 8. Best Application Paper Award at Pacific-Asia Conference on Knowledge Discovery and Data mining 2011 9.

3 Open Source Software Award, Silver, at Open Source Software World Challenge 2010 10. Best Application Paper Award, Runner-up, at IEEE International Conference on Data mining 2009 11. JeongSong Foundation Fellowship 2007-2009 RESEARCH EXPERIENCE Associate Professor, Department of Computer Science and Engineering, Seoul National University Sep. 2017- present Assistant Professor, Department of Computer Science and Engineering, Seoul National University Sep. 2015-Aug. 2017 Assistant Professor, Department of Computer Science, KAIST 2013-Aug.

4 2015 Postdoctoral Fellow, Computer Science Department, Carnegie Mellon University June-Dec. 2012 Research Intern, IBM Watson Research, Hawthorne, NY May-Aug. 2011 2 Research Intern, IBM Watson Research, Hawthorne, NY May-Aug. 2010 Research Intern, Microsoft Research, Redmond, WA May-Aug. 2009 Research Intern, Microsoft Research, Redmond, WA May-Aug. 2008 Researcher, Korea Telecom Research Lab, Seoul, Korea 2004-2007 TEACHING EXPERIENCE 1. Data Structure Fall 2015 2. Introduction to Data mining Spring 2016 3. Data Structure Fall 2016 4.

5 Computer Engineering Seminar Fall 2016 5. Introduction to Data mining Spring 2017 6. Deep Learning (Topics in Big Data Analytics) Spring 2017 7. Data Structure Fall 2017 8. Advanced Deep Learning (Topics in Big Data Analytics) Fall 2017 9. Introduction to Data mining Spring 2018 10. Optimization for Machine Learning (Topics in Artificial Intelligence) Spring 2018 11. Data Structure Fall 2018 12. Advanced Deep Learning (Topics in Big Data Analytics) Fall 2018 13. Introduction to Data mining Spring 2019 14. Reinforcement Learning (Topics in Big Data Analytics) Spring 2019 15.

6 Data Structure Fall 2019 16. Advanced Data mining Fall 2019 17. Introduction to Data mining Spring 2020 18. Introduction and Practice of IoT, AI, and Big Data Spring 2020 19. Data Structure Fall 2020 20. Advanced Data mining Fall 2020 PUBLICATIONS BOOK CHAPTER 1. Hanghang Tong and U Kang, Big Data Clustering Algorithms, in Data Clustering: Algorithms and Applications, CRC Press, August 2013. Editors: Chandan Reddy and Charu Aggarwal. 2. U Kang and Christos Faloutsos, mining Tera-scale graphs with Pegasus : algorithms and discoveries, in Large Scale Data Analytics, Springer, January 2014.

7 Editors: Aris Gkoulalas-Divanis and Abdel Labbi. REFEREED JOURNALS J1. U Kang, Charalampos E. Tsourakakis, Ana Paula Appel, Christos Faloutsos, and Jure Leskovec, HADI: mining Radii of Large Graphs, ACM Transactions on Knowledge Discovery from Data (TKDD), February 2011. J2. U Kang, Charalampos E. Tsourakakis, and Christos Faloutsos, PEGASUS: mining Peta-Scale Graphs, Knowledge and Information Systems (KAIS), Springer, May 2011. J3. U Kang, Hanghang Tong, Jimeng Sun, Ching-Yung Lin, and Christos Faloutsos, GBASE: An Efficient Analysis Platform for Large Graphs, VLDB Journal, October 2012.

8 J4. U Kang, Martial Hebert, and Soonyong Park, Fast and Scalable Approximate Spectral Graph Matching for Correspondence Problems, Information Sciences, January 2013. J5. U Kang, Brendan Meeder, Evangelos E. Papalexakis, and Christos Faloutsos, Heigen: Spectral 3 Analysis for Billion-Scale Graphs, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 26, , pp. 350-362, Feb. 2014. J6. Yongsub Lim, U Kang, and Christos Faloutsos, SlashBurn: Graph Compression and mining beyond Caveman Communities, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol.

9 26, no. 12, pp. 3077-3089, April 2014. J7. Lee Sael, Inah Jeon, and U Kang, Scalable Tensor mining , Big Data Research, Feb. 2015. J8. Danai Koutra, U Kang, Jilles Vreeken, and Christos Faloutsos, Summarizing and understanding large graphs, Statistical Analysis and Data mining , doi: , 18 May 2015. J9. Ho Lee, Bin Shao, and U Kang, Fast graph mining with HBase, Information Sciences, vol. 315, pp. 56-66, 10 September 2015. J10. JengHoon Park, Chin-Wan Chung, and U Kang, Reverse Nearest Neighbor Search with a Non-spatial Aspect, Journal of Information Systems, vol.

10 54, pp. 92-112, Dec. 2015. J11. Jinhong Jung, Kijung Shin, Lee Sael, and U Kang, Random Walk with Restart on Large Graphs Using Block Elimination, ACM Transactions on Database Systems, vol. 41, issue 2, pp. 12:1-12:43, June 2016. J12. Inah Jeon, Evangelos E. Papalexakis, Christos Faloutsos, Lee Sael, and U Kang, mining Billion-Scale Tensors: Algorithm and Discoveries, VLDB Journal, vol. 25, issue 4, pp. 519-544, August 2016. J13. Yongsub Lim, Won-Jo Lee, Ho-Jin Choi, and U Kang, MTP: Discovering High Quality Partitions in Real World Graphs, World Wide Web Journal, vol.