u kang - data miningukang/ukang-cv.pdf · 3 j4. u kang, martial hebert, and soonyong park, fast and...

1

U Kang

Associate Professor

Department of Computer Science and Engineering

Seoul National University Office : (+82).2.880.7254

1 Gwanak-ro, Gwanak-gu, Seoul [email protected]

Republic of Korea 08826 http://datalab.snu.ac.kr/~ukang

RESEARCH INTERESTS

Big Data Mining, Deep Learning, and Machine Learning, with emphasis on models, algorithms,

and systems for scalable data analysis with applications on knowledge discovery, prediction, and

anomaly detection.

EDUCATION

Ph.D. Computer Science, Carnegie Mellon University 2012

Dissertation: Mining Tera-Scale Graphs: Theory, Engineering and Discoveries

Advisor: Professor Christos Faloutsos

M.Sc. Information Technology, Carnegie Mellon University 2009

B.Sc. Computer Science and Engineering, Seoul National University 2003

AWARDS AND HONORS 1. 10-year Highest Impact Paper Award from IEEE International Conference on

Data Mining (ICDM)

2018

2. Young Information Scientist Award from Korean Institute of Information

Scientists and Engineers

2016

3. Ewon Assistant Professor from KAIST 2014

4. 10 Best Research Award from KAIST 2013

5. SIGKDD Doctoral Dissertation Award, Honorable Mention 2013

6. New Faculty Award from Microsoft Research Asia 2013

7. Best Application Paper Award at Pacific-Asia Conference on Knowledge Discovery and

Data Mining

2011

8. Open Source Software Award, Silver, at Open Source Software World Challenge 2010

9. Best Application Paper Award, Runner-up, at IEEE International Conference on Data

Mining

2009

10. 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. 2015

Postdoctoral Fellow, Computer Science Department, Carnegie Mellon University June-Dec. 2012

Research Intern, IBM T.J. Watson Research, Hawthorne, NY May-Aug. 2011

2

Research Intern, IBM T.J. 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

COURSES TAUGHT (at Seoul National University)

1. Data Structure Fall 2015

2. Introduction to Data Mining Spring 2016


4. Computer Engineering Seminar Fall 2016


6. Deep Learning (Topics in Big Data Analytics) Spring 2017


8. Advanced Deep Learning (Topics in Big Data Analytics) Fall 2017


10. Optimization for Machine Learning (Topics in Artificial Intelligence) Spring 2018


12. Advanced Deep Learning (Topics in Big Data Analytics) Fall 2018


14. Reinforcement Learning (Topics in Big Data Analytics) Spring 2019

COURSES TAUGHT (at KAIST)

1. Big Graph Mining (CS760), KAIST Spring 2013

2. Data Mining (CS492), KAIST Fall 2013

3. Advanced Data Mining (CS665), KAIST Spring 2014

4. Data Mining (CS492), KAIST Fall 2014

5. Advanced Data Mining (CS665), KAIST Spring 2015

6. Machine Learning and Data Mining (SEP532), KAIST Spring 2015

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. 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.

3

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

Analysis for Billion-Scale Graphs, IEEE Transactions on Knowledge and Data Engineering

(TKDE), vol. 26, no.2, 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. 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: 10.1002/sam.11267, 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. 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. 20, issue 3, pp 491–514, May

2017.

J14. Kijung Shin, Lee Sael, and U Kang, Fully Scalable Methods for Distributed Tensor

Factorization, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 29, issue

1, pp. 100-113, January 1 2017.

J15. Yongsub Lim, and U Kang, Time-weighted Counting for Recently Frequent Pattern Mining in

Data Streams, Knowledge and Information Systems (KAIS), vol. 53, no. 2, pp. 391-422, Sep.

12 2017.

J16. Yongsub Lim, Minsoo Jung, and U Kang, Memory-efficient and Accurate Sampling for

Counting Local Triangles in Graph Streams: From Simple to Multigraphs, ACM Transactions

on Knowledge Discovery from Data (TKDD), vol. 12, no. 1, pp. 4:1-4:28, Feb. 2018.

J17. Mauro Scanagatta, Giorgio Corani, Marco Zaffalon, Jaemin Yoo, and U Kang, Efficient

Learning of Bounded-Treewidth Bayesian Networks from Complete and Incomplete Data Sets,

International Journal of Approximate Reasoning (IJAR), vol. 95, pp. 152-166, 2018.

J18. Namyong Park, Eunjeong Kang, Minsu Park, Hajeong Lee, Hee-Gyung Kang, Hyung-Jin

Yoon, and U Kang, Predicting acute kidney injury in cancer patients using heterogeneous and

irregular data, PLOS ONE 13(7): e0199839.

J19. Ha-Myung Park, Francesco Silvestri, Rasmus Pagh, Chin-wan Chung, Sung-Hyon Myaeng,

and U Kang, Enumerating Trillion Subgraphs On Distributed Systems, ACM Transactions on

Knowledge Discovery from Data (TKDD), vol. 12, no. 6, pp. 71:1-71:30, Oct. 2018.

J20. Namyong Park, Sejoon Oh, and U Kang, Fast and Scalable Method for Distributed Boolean

Tensor Factorization, VLDB Journal (to appear)

J21. Woojeong Jin, Jinhong Jung, and U Kang, Supervised and extended restart in random walks

for ranking and link prediction in networks, PLOS ONE. (to appear)

J22. Eunjeong Kang, Minsu Park, Peonggang Park, Namyong Park, Younglee Jung, U Kang, Hee

4

Kyung Kang, Dong Ki Kim, Kwon Wook Joo, Yon Su Kim, Hyung Jin Yoon and Hajeong

Lee, Acute kidney injury predicts all-cause mortality in patients with cancer, Cancer Medicine.

(to appear)

J23. Jinhong Jung, Woojung Jin, and U Kang, Random Walk Based Ranking in Signed Social

Networks: Model and Algorithms, Knowledge and Information Systems (KAIS), Springer, (to

appear).

J24. Minsoo Jung, Yongsub Lim, Sunmin Lee, and U Kang, FURL: Fixed-memory and

Uncertainty Reducing Local Triangle Counting for Multigraph Streams, Data Mining and

Knowledge Discovery (to appear).

INVITED(UNREFEREED) JOURNALS

1. U Kang and Christos Faloutsos, Big Graph Mining: Algorithms and Discoveries, SIGKDD

Exploration Volume 14 Issue 2, December 2012.

2. Evangelos E. Papalexakis, U Kang, Christos Faloutsos, Nicholas D. Sidiropoulosx, Abhay

Harpale, Large Scale Tensor Decompositions: Algorithmic Developments and Applications,

Bulletin of the Technical Committee on Data Engineering, vol. 36, no. 3, September 2013

REFEREED CONFERENCES

C1. Charalampos E. Tsourakakis, U Kang, Gary Miller, and Christos Faloutsos, DOULION:

Counting Triangles in Massive Graphs with a Coin, ACM SIGKDD International Conference

On Knowledge Discovery and Data Mining (KDD) 2009, Paris, France.

C2. U Kang, Charalampos E. Tsourakakis, and Christos Faloutsos, PEGASUS: A Peta-Scale

Graph Mining System - Implementation and Observations, IEEE International Conference on

Data Mining (ICDM) 2009, Florida, Miami, USA.

Best Application Paper Award (runner-up).

NSF Student Travel Award.

C3. U Kang, Charalampos E. Tsourakakis, Ana Paula Appel, Christos Faloutsos, and Jure

Leskovec, Radius Plots for Mining Tera-byte Scale Graphs: Algorithms, Patterns, and

Observations, SIAM International Conference on Data Mining (SDM) 2010, Columbus, Ohio,

USA.


C4. U Kang, Mary McGlohon, Leman Akoglu, and Christos Faloutsos, Patterns on the Connected

Components of Terabyte-Scale Graphs, IEEE International Conference on Data Mining

(ICDM) 2010, Sydney, Australia.


C5. U Kang, Duen Horng Chau, and Christos Faloutsos, Mining Large Graphs: Algorithms,

Inference, and Discoveries, IEEE International Conference on Data Engineering (ICDE) 2011,

Hannover, Germany.

C6. U Kang, Spiros Papadimitriou, Jimeng Sun, and Hanghang Tong, Centralities in Large

Networks: Algorithms and Observations, SIAM International Conference on Data Mining

(SDM) 2011, Mesa, Arizona, USA.

SDM 2011 Travel Scholarship.

C7. U Kang, Brendan Meeder, and Christos Faloutsos, Spectral Analysis for Billion-Scale Graphs:

Discoveries and Implementation, Pacific-Asia Conference on Knowledge Discovery and Data

Mining (PAKDD) 2011, Shenzhen, China.

Best Application Paper Award. C8. Robson L. F. Cordeiro, Caetano Traina Jr., Agma J. M. Traina, Julio Lopez, U Kang, and

Christos Faloutsos, Clustering Very Large Multi-dimensional Datasets with MapReduce, ACM

SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2011, San Diego,

5

CA, USA.

C9. U Kang, Hanghang Tong, Jimeng Sun, Ching-Yung Lin, and Christos Faloutsos, GBASE: A

Scalable and General Graph Management System, ACM SIGKDD Conference on Knowledge

Discovery and Data Mining (KDD) 2011, San Diego, CA, USA.

C10. Danai Koutra, Tai-You Ke, U Kang, Duen Horng (Polo) Chau, Hsing-Kuo Kenneth Pao, and

Christos Faloutsos, Unifying Guilt-by-Association Approaches: Theorems and Fast

Algorithms, European Conference on Machine Learning and Principles and Practice of

Knowledge Discovery in Databases (ECML PKDD) 2011, Athens, Greece.

C11. U Kang and Christos Faloutsos, Beyond `Caveman Communities': Hubs and Spokes for Graph

Compression and Mining, IEEE International Conference on Data Mining (ICDM) 2011,

Vancouver, Canada.

C12. U Kang, Duen Horng Chau, and Christos Faloutsos, PEGASUS: Mining Billion-Scale Graphs

in the Cloud, IEEE International Conference on Acoustics, Speech, and Signal Processing

(ICASSP) 2012, Kyoto, Japan.

C13. U Kang, Hanghang Tong, and Jimeng Sun, Fast Random Walk Graph Kernel, SIAM

International Conference on Data Mining (SDM) 2012, Anaheim, California, USA.

C14. U Kang, Evangelos Papalexakis, Abhay Harpale, and Christos Faloutsos, GigaTensor: Scaling

Tensor Analysis Up By 100 Times - Algorithms and Discoveries, ACM SIGKDD Conference

on Knowledge Discovery and Data Mining (KDD) 2012, Beijing, China.

C15. Jay Yoon Lee, U Kang, Danai Koutra, and Christos Faloutsos, Fast anomaly detection despite

the duplicates, 22nd International World Wide Web Conference (WWW) 2013, Rio de Janeiro,

Brazil. (poster)

C16. Zhiyuan Lin, Nan Cao, Hanghang Tong, Fei Wang, U Kang, and Duen Horng Chau,

Interactive Multi-resolution Exploration of Million Node Graphs, IEEE VIS 2013, Atlanta,

Georgia, USA. (poster)

C17. Danai Koutra, U Kang, Jilles Vreeken, and Christos Faloutsos, VoG: Summarizing and

Understanding Large Graphs, SIAM International Conference on Data Mining (SDM) 2014,

Philadelphia, PA, USA.

C18. U Kang, Jay-Yoon Lee, Danai Koutra, and Christos Faloutsos, Net-Ray: Visualizing and

Mining Billion-Scale Graphs, Pacific-Asia Conference on Knowledge Discovery and Data

Mining (PAKDD) 2014, Tainan, Taiwan.

C19. Jungeun Kim, Minsoo Choy, Daehoon Kim, and U Kang, Link Prediction Based on

Generalized Cluster Information, 23rd International World Wide Web Conference (WWW)

2014, Seoul, Korea. (poster)

C20. Zhiyuan Lin, Minsuk Kahng, Kaeser Md. Sabrin, Duen Horng (Polo) Chau, Ho Lee, and U

Kang, MMap: Fast Billion-Scale Graph Computation on a PC via Memory Mapping, IEEE

International Conference on Big Data 2014, Washington DC, USA.

C21. Dongyeop Kang, Woosang Lim, Kijung Shin, Lee Sael, and U Kang, Data/Feature

Distributed Stochastic Coordinate Descent for Logistic Regression, 23rd ACM International

Conference on Information and Knowledge Management (CIKM) 2014, Shaghai, China.

C22. Ha-Myung Park, Franceso Silvestri, U Kang, and Rasmus Pagh. MapReduce Triangle

Enumeration With Guarantees, 23rd ACM International Conference on Information and

Knowledge Management (CIKM) 2014, Shaghai, China.

C23. Yongsub Lim, Jihoon Choi, and U Kang, Fast, Accurate, and Space-efficient Tracking of

Time-weighted Frequent Items from Data Streams, 23rd ACM International Conference on

Information and Knowledge Management (CIKM) 2014, Shaghai, China.

C24. Kijung Shin, and U Kang, Distributed Methods for High-dimensional and Large-scale Tensor

Factorization, IEEE International Conference on Data Mining (ICDM) 2014, Shenzhen, China.

C25. Yongsub Lim, Won-Jo Lee, Ho-Jin Choi, and U Kang, Discovering Large Subsets with High

6

Quality Partitions in Real World Graphs, 2nd International Conference on Big Data and Smart

Computing (BigComp) 2015, Jeju Island, Korea.

C26. Won-Jo Lee, Chae-Gyun Lim, U Kang, and Ho-Jin Choi, An Extension of the Automatic

Cross-Association Method with a 3-dimensional Matrix, 2nd International Conference on Big

Data and Smart Computing (BigComp) 2015, Jeju Island, Korea.

C27. Inah Jeon, Evangelos E. Papalexakis, U Kang, and Christos Faloutsos, HaTen2: Billion-scale

Tensor Decompositions, 31st IEEE International Conference on Data Engineering (ICDE)

2015, Seoul, Korea.

C28. Kijung Shin, Jinhong Jung, Lee Sael, and U Kang, BEAR: Block Elimination Approach for

Random Walk with Restart on Large Graphs, ACM International Conference on Management

of Data (SIGMOD) 2015, Melbourne, Australia.

C29. Yongsub Lim and U Kang, MASCOT: Memory-efficient and Accurate Sampling for Counting

Local Triangles in Graph Streams, ACM SIGKDD Conference on Knowledge Discovery and

Data Mining (KDD) 2015, Sydney, Australia.

C30. ByungSoo Jeon, Inah Jeon, Lee Sael, and U Kang, SCouT: Scalable Coupled Matrix-Tensor

Factorization - Algorithm and Discoveries, 32nd IEEE International Conference on Data

Engineering (ICDE) 2016, Helsinki, Finland.

C31. Ha-Myung Park, Sung-Hyon Myaeng, and U Kang, PTE: Enumerating Trillion Triangles On

Distributed System, ACM SIGKDD Conference on Knowledge Discovery and Data Mining

(KDD) 2016, San Francisco, USA.

C32. Hugo Gualdron, Robson Cordeiro, Jose Rodrigues-Jr, Duen Horng Chau, Minsuk Kahng, and

U Kang, M-Flash: Fast Billion-Scale Graph Computation Using a Bimodal Block Processing

Model, European Conference on Machine Learning and Principles and Practice of Knowledge

Discovery in Databases (ECML PKDD) 2016, Riva Del Garda, Italy.

C33. Min-Hee Jang, Christos Faloutsos, Sang-Wook Kim, U Kang, and Jiwoon Ha, PIN-TRUST:

Fast Trust Propagation Exploiting Positive, Implicit, and Negative Information, ACM

International Conference on Information and Knowledge Management (CIKM) 2016,

Indianapolis, Indiana, USA.

C34. Jinhong Jung, Woojung Jin, Lee Sael, and U Kang, Personalized Ranking in Signed Networks

using Signed Random Walk with Restart, IEEE International Conference on Data Mining

(ICDM) 2016, Barcelona, Spain.

C35. Ha-Myung Park, Namyong Park, Sung-Hyon Myaeng, and U Kang, Partition Aware

Connected Component Computation in Distributed Systems, IEEE International Conference on

Data Mining (ICDM) 2016, Barcelona, Spain.

C36. Kyung-Min Kim, Jinhong Jung, Jihee Ryu, Ha-Myung Park, Joseph P.Joohee, Seokwoo Jeong,

U Kang, and Sung-Hyon Myaeng, A New Question Answering Approach with Conceptual

Graphs, Conférence en Recherche d’Information et Applications (CORIA) 2017, Marseille,

France.

C37. Jinhong Jung, Namyong Park, Lee Sael, and U Kang, BePI: Fast and Memory-Efficient

Method for Billion-Scale Random Walk with Restart, ACM International Conference on

Management of Data (SIGMOD) 2017, Chicago, IL, USA.

C38. Namyong Park, Sejoon Oh, and U Kang, Fast and Scalable Distributed Boolean Tensor

Factorization, 33rd IEEE International Conference on Data Engineering (ICDE) 2017, San

Diego, CA, USA.

C39. Jaemin Yoo, Saehan Jo, and U Kang, Supervised Belief Propagation: Scalable Supervised

Inference on Attributed Networks, IEEE International Conference on Data Mining (ICDM)

2017, New Orleans, USA.

C40. Haekyu Park, Jinhong Jung, and U Kang, A Comparative Study of Matrix Factorization and

7

Random Walk with Restart in Recommender Systems, IEEE International Conference on Big

Data 2017, Boston, MA, USA.

C41. Saehan Jo, Jaemin Yoo, and U Kang, Fast and Scalable Distributed Loopy Belief Propagation

on Real-World Graphs, 11th ACM International Conference on Web Search and Data Mining

(WSDM) 2018, Los Angeles, CA, USA.

C42. Minji Yoon, Woojeong Jin, and U Kang, Fast and Accurate Random Walk with Restart on

Dynamic Graphs with Guarantees, The Web Conference (WWW) 2018, Lyon, France.

C43. Junghwan Kim, Haekyu Park, Ji-Eun Lee, and U Kang, SIDE: Representation Learning in

Signed Directed Networks, The Web Conference (WWW) 2018, Lyon, France.

C44. Minji Yoon, Jinhong Jung, and U Kang, TPA: Fast, Scalable, and Accurate Method for

Approximate Random Walk with Restart on Billion Scale Graphs, 34th IEEE International

Conference on Data Engineering (ICDE) 2018, Paris, France.

C45. Sejoon Oh, Namyong Park, Lee Sael, and U Kang, Scalable Tucker Factorization for Sparse

Tensors - Algorithms and Discoveries, 34th IEEE International Conference on Data

Engineering (ICDE) 2018, Paris, France.

C46. Jun-gi Jang, Dongjin Choi, Jinhong Jung, and U Kang, Zoom-SVD: Fast and Memory Efficient

Method for Extracting Key Patterns in an Arbitrary Time Range, ACM International

Conference on Information and Knowledge Management (CIKM) 2018, Lingotto, Turin, Italy.

OTHER PUBLICATIONS

O1. U Kang, Charalampos Tsourakakis, Ana Paula Appel, Christos Faloutsos, and Jure Leskovec,

HADI: Fast Diameter Estimation and Mining in Massive Graphs with Hadoop, CMU Machine

Learning Tech Report CMU-ML-08-117, December 2008.

O2. U Kang, Duen Horng Chau, and Christos Faloutsos, Inference of Beliefs on Billion-Scale

Graphs, The 2nd Workshop on Large-scale Data Mining: Theory and Applications (LDMTA)

2010, in conjunction with KDD 2010, Washington D.C., USA.

O3. U Kang, Mikhail Bilenko, Dengyong Zhou, and Christos Faloutsos, Axiomatic Analysis of Co-

occurrence Similarity Functions, CMU Computer Science Tech Report CMU-CS-12-102,

February 2012.

O4. Zhiyuan Lin, Duen Horng Chau, and U Kang, Leveraging Memory Mapping for Fast and

Scalable Graph Computation on a PC, First International Workshop on Scalable Machine

Learning: Theory and Applications, in conjunction with IEEE BigData 2013, Santa Clara, CA,

USA.

DEMO

D1. Leman Akoglu*, Duen Horng Chau*, U Kang*, Danai Koutra*, and Christos Faloutsos,

OPAvion: Mining and visualization in large graphs, ACM SIGMOD Conference 2012,

Scottsdale, AZ, USA.

D2. Leman Akoglu*, Duen Horng Chau*, U Kang*, Danai Koutra*, and Christos Faloutsos,

OPAvion: Large Graph Mining System for Patterns, Anomalies & Visualization, Pacific-Asia

Conference on Knowledge Discovery and Data Mining (PAKDD) 2012, Kuala Lumpur,

Malaysia.

D3. Zhiyuan Lin, Nan Cao, Hanghang Tong, Fei Wang, U Kang, and Duen Horng (Polo) Chau,

Demonstrating Interactive Multi-resolution Large Graph Exploration, IEEE International

Conference on Data Mining (ICDM) 2013, Dallas, Texas, USA.

D4. Dongyeop Kang, DongGyun Han, NaHea Park, Sangtae Kim, U Kang, and Soobin Lee,

Eventera: Real-time Event Recommendation System from Massive Heterogeneous Online

Media, IEEE International Conference on Data Mining (ICDM) 2014, Shenzhen, China.

D5. ByungSoo Jeon, Inah Jeon, and U Kang, TeGViz: Distributed Tera-Scale Graph Generation

8

and Visualization, IEEE International Conference on Data Mining (ICDM) 2015, Atlantic City,

USA.

D6. Namyong Park, ByungSoo Jeon, Jungwoo Lee, and U Kang, BIGtensor: Mining Billion-Scale

Tensor Made Easy, 25th ACM International Conference on Information and Knowledge

Management (CIKM) 2016, Indianapolis, USA.

D7. Ha-Myung Park, Chiwan Park, and U Kang, PegasusN: A Scalable and Versatile Graph

Mining System, Thirty-Second AAAI Conference on Artificial Intelligence (AAAI) 2017, New

Orleans, Lousiana, USA.

PATENTS

PCT PATENT

1. U Kang, Minji Yoon, Jinhong Jung, “Method and Apparatus for Efficient Node Proxity

Computation for Large Graphs” (filed on Nov. 18, 2017).

UNITED STATES

1. U Kang, Spiros Papadimitriou, Jimeng Sun, Ching-Yung Lin, “Determining the Importance of

Data Items and Their Characteristics Using Centrality Measures” (registered on August 26,

2014).

2. U Kang, Hanghang Tong, Jimeng Sun, Ching-Yung Lin, “Method and System for Managing and

Querying Large Graphs” (registered on February 4, 2014).

3. U Kang, Hanghang Tong, Jimeng Sun, Ravi Konuru, “Determining a similarity between graphs”

(filed on January 17, 2013).

4. U Kang, Hanghang Tong, Jimeng Sun, Ravi Konuru, “Determining soft graph correspondence”

(filed on January 17, 2013).

KOREA

1. U Kang, “Virtual Web-Server Based Intrusion Enticement System for Early Detection of Internet

Web Attack and Method Thereof”, Korean patent number: 10-2004-0074724 (registered on Oct.

2011).

2. Sang-Kon Kim, Yoon-Ho Choi, Jong-Ho Park, Ho-Kun Moon, Myung-Soo Rhee, U Kang, Jin

Gi Choe and Seung-Woo Seo “Network Security System and Method for Tracing Attacker on the

Encrypted Connection Chain”, Korean patent number: 10-2005-0021125 (filed on Mar. 14,

2005).

3. Yoon-Ho Choi, Jong-Ho Park, Sang-Kon Kim, Ho-Kun Moon, Myung-Soo Rhee, U Kang, Jin

Gi Choe and Seung-Woo Seo, “System and Method of Forensics Evidence Collection at the Time

of Infringement Occurrence”, Korean patent number: 10-2005-0129965 (registered on Dec.

2012).

4. U Kang, Yongsub Lim, and Christos Faloutsos, “Method and Apparatus for Processing Graph

Compression”, Korean patent number: 10-1660584-0000 (registered on Sep. 21, 2016).

5. U Kang, Ha-Myung Park, Rasmus Pagh, Francesco Silvestri, “MapReduce Method for Triangle

Enumeration and Apparatus Thereof”, Koran patent number: 10-1669356-0000 (registered on

Oct. 25, 2016).

6. Dong Min Seo, Seok Jong YU, Min Ho Lee, U Kang, Yong Sub Lim, In Jae Yu, Sael Lee,

“Method and Apparatus for Network Clustering”, Korean patent number: 10-2016-0101611 (filed

on Aug. 10, 2016).

7. Dong Min Seo, Seok Jong YU, Min Ho Lee, U Kang, Ha-Myung Park, “Method and Apparatus

9

for Matching Graphs”, Korean patent number: 10-2016-0139185 (registered on June 9, 2017).

8. U Kang, Jaemin Yoo, “Apparatus and Method for Classifying Nodes”, Korean patent number:

10-2016-0182358 (registered on Nov. 28, 2018).

9. U Kang, Min Soo Jung, Sun Min Lee, Yong Sub Lim, “Triangle Counting Method for Graph

Stream”, Korean patent number: 10-2016-0183070 (filed on Dec. 29, 2016).

10. U Kang, Jinhong Jung, Namyong Park, “Method and Apparatus for Performing Graph Ranking”,

Korean patent number: 10-2016-0183757 (registered on Jan. 31, 2019).

11. U Kang, Jinhong Jung, Woojeong Jin, “Method for Personalized Ranking in Signed Networks,

Recording Medium and Device for Performing the Method”, Korean patent number: 10-2017-

0005485 (registered on June 5, 2018).

12. U Kang, Woojung Jin, Jinhong Jung, “Method and Apparatus for Providing Supervised and

Extended Restart in Random Walks for Ranking and Link Prediction in Networks”, Korean

patent number: 10-2017-0149941 (filed on Nov 10, 2017).

13. U Kang, Junghwan Kim, Haekyu Park, “Apparatus and Method for Representation Learning in

Signed Directed Networks”, Korean patent number: 10-2017-0149948 (filed on Nov. 10, 2017).

14. U Kang, Dongjin Choi, Jun-Gi Jang, “Data Analysis Method and Apparatus for Sparse Data”,

Korean patent number: 10-2017-0158496 (filed on Nov. 24, 2017).

15. U Kang, Sejoon Oh, Namyong Park, “Apparatus for Supporting Multi-dimensional Data

Analysis through Parallel Processing and Method for the Same”, Korean patent number:10-2017-

0158951 (filed on Nov. 24, 2017).

16. U Kang, Haekyu Park, Hyunsik Jeon, Junghwan Kim, “Explainable and Accurate Recommender

Method and System using Social Network Information and Rating Information”, Korean patent

number: 10-2017-0159167 (filed on Nov.27 2017).

17. U Kang, Jun-Gi Jang, Dongjin Choi, Jinhong Jung, “Apparatus and Method For Processing

Data”, Korean patent number: 10-2018-0007389 (filed on Jan. 19, 2018).

18. U Kang, Chiwan Park, Ha-Myung Park, Minji Yoon, “Method and Apparatus for Scalable Graph

Mining Using Graph Pre-partitioning”, Korean patent number: 10-2018-0037373 (filed on Mar.

30, 2018).

19. U Kang, Jinhong Jung, Woojung Jin, “Method and Apparatus For Fast and Personalized Ranking

Using Block Elimination in Signed Social Networks”, Korean patent number: 10-2018-0149677

(filed on Nov. 28, 2018).

20. U Kang, Jinhong Jung, Woojung Jin, Ha-Myung Park, “Method and Apparatus For Measuring

Relevance Between Nodes of Edge-labeled Multigraph”, Korean patent number: 10-2018-

0150180 (filed on Nov. 28, 2018).

21 U Kang, Taebum Kim, Jaemin Yoo, “Method for Compressing Deep Learning Neural Networks

and Apparatus for Performing the Same”, Korean patent number: 10-2018-015181 (filed on Nov.

28, 2018).

22. U Kang, Ha-Myung Park, “Triangle Enumeration Method That Reduces Network Traffic on

Heterogeneous Clusters and Apparatus Thereof”, Korean patent number: 10-2019-0018142 (filed

on Feb. 15, 2019)

TALKS

INVITED CONFERENCE SPEAKER

1. Peta Scale Graph Mining with Pegasus, Invited workshop speaker, Workshop on High

Performance Analytics - Algorithms, Implementations, and Applications, Columbus, OH, Apr.

2010.

10

2. Mining Tera Scale Graphs: Theory, Engineering and Discoveries, Invited workshop speaker,

IBM Workshop on Frontiers in AI and KDD, IBM T.J. Watson Research, Oct. 2012.

3. Mining Tera Scale Graphs, Invited workshop speaker, The 5th Database Specialist Workshop,

Jeju, Korea, Feb. 2013.

4. Big Graph Mining: Patterns and Algorithms, Invited workshop speaker, Workshop on Big Data

Processing, Seoul, Korea, Oct. 2013

5. Big Graph Mining, Invited speaker, Software Convergence Symposium, Seoul, Korea, Jan. 2014.

6. Summarizing Large Graphs, Invited workshop speaker, The 6th Database Specialist Workshop,

Jeju, Korea, Apr. 2014.

7. Big Tensor Mining, Korea-Japan Database Workshop (KJDB) 2014, Gangwon, Korea, Nov. 30,

2014.

8. BEAR: Block Elimination Approach for Random Walk With Restart on Large Graphs, Korea-

Japan Database Workshop (KJDB) 2015, Okinawa, Japan, Dec. 4, 2015.

INVITED DISTINGUISHED LECTURES

1. Mining Tera-Scale Graphs: Theory, Engineering, and Discoveries, Invited Distinguished

Seminar, KT Institute of Convergence Technology, Seoul, Korea, June 2014.

2. Big Graph Mining, Invited Colloquium Lecture, Hanyang University, Seoul, Korea, May 2014.

3. Big Graph Mining: Theory, Engineering, and Discoveries, Invited Colloquium Lecture, Kyung

Hee University, YongIn, Korea, June 2014.

4. Mining Big Data, SKT dev forum, Seoul, Korea, Aug. 2016.

INVITED LECTURES

1. Pegasus: mining peta-scale graph, Dept. of Computer Science and Engineering, Hanyang

University, Seoul, Korea, Nov. 2010.

2. Mining Billion-Scale Graphs: Algorithms and Discoveries, Dept. of Electrical Engineering, Seoul

National University, Korea, May 2011.

3. Mining Billion-Scale Graphs: Algorithms and Discoveries, SAP R&D Center, Korea, May 2011.

4. Mining Tera-Scale Graphs with MapReduce: Theory, Engineering and Discoveries, Dept. of

Computer Science and Engineering, Hanyang University, Seoul, Korea, Dec. 2011.

5. Mining Tera-Scale Graphs with MapReduce: Theory, Engineering and Discoveries, Dept. of

Computer Science, KAIST, Daejeon, Korea, Dec. 2011.

6. Big Graph Mining and Its Applications to QA, Electronics and Telecommunications Research

Institute, Daejeon, Korea, Dec. 2011.

7. Mining Tera-Scale Graphs: Theory, Engineering and Discoveries, Inha University, Incheon,

Korea, March. 2013.

8. Mining Tera-Scale Graphs, National Institute of Mathematical Sciences, Daejeon, Korea, Apr.

2013.

9. Mining Tera-Scale Graphs: Theory, Engineering and Discoveries, SK Telecom, Seoul, Korea,

Apr. 2013.

10. Mining Big Graphs, College of Medicine, Seoul National University, Seoul, Korea, June 2013.

11. Mining Big Graphs, Dept. of Computer Engineering, Postech, Pohang, Korea, Oct. 2013.

12. Mining Big Graphs, Dept. of Electronics and Communication Engineering, Computer and

Information, Chonnam National University, KwangJu, Korea, Nov. 2013.

13. Mining Big Graphs, National Security Research Institute, Daejeon, Korea, Feb. 2014.

14. Scalable Graph Mining, Korea Institute of Science and Technology Information, Daejeon, Korea,

Aug. 2014.

15. Memory-efficient and Accurate Sampling for Counting Local Triangles in Graph Streams, Dept.

of Statistics, Seoul National University, Apr. 2016.

11

16. Fast Random Walk with Restart for Ranking in Large Graphs, Oracle Labs, Redwood City, CA,

USA, Aug. 2016.

17. BigTensor: Mining Billion-Scale Tensor Made Easy, Intel Labs, Santa Clara, CA, USA, Aug.

2016.

TUTORIALS

1. Managing and Mining Large Graphs: Patterns and Algorithms (with Christos Faloutsos),

SIGMOD 2012, Scottsdale, AZ, May 2012.

2. Big Graph Mining: Patterns and Algorithms, KCC 2013, Yeo-su, Korea, July 2013.

3. Mining Big Graphs, EDB 2013, Jeju Island, Korea, August 2013.

4. Big Graph Mining: Algorithms, Anomaly Detection, and Applications (with Leman Akoglu and

Polo Chau), ASONAM 2013, Niagara Falls, Canada, August 2013.

5. Big Graph Mining for the Web and Social Media: Algorithms, Anomaly Detection, and

Applications (with Leman Akoglu and Polo Chau), WSDM 2014, New York, NY, February

2014.

6. Large Scale Tensor Analysis, PAKDD 2017, Jeju, Korea, May 2017.

7. Lightweight Deep Learning with Model Compression, IEEE BigComp 2019, Kyoto, Japan, Feb.

2019.

STUDENTS AND THESES DIRECTED

Ph.D. ADVISING

1. Yongsub Lim (graduated: Aug. 2015)

2. Hamyung Park (graduated: Feb. 2018. co-advisor: Sung-Hyon Myaeng)

3. Jinhong Jung

4. Huiwen Xu

5. Hyunsik Jeon

M.S./Ph.D. ADVISING

1. Minsoo Jung

2. Jaemin Yoo

3. Jun-gi Jang

4. Seungcheol Park

5. Chaeheum Park

M.S. ADVISING

1. Ho Lee (graduated: Feb. 2015)

2. Inah Jeon (graduated: Feb. 2015)

3. Chiwan Park (graduated: Feb. 2018)

4. Hyunsik Jeon (graduated: Feb. 2019)

5. Yang Bai

6. Quan Chun

7. Bonhun Koo

8. Shuyu Wang

9. Junghoon Kim

10. Jaewon Lee

UNDERGRADUATE ADVISING (research)

12

1. Dang Hai Nguyen (Independent Study, Fall 2013) – CS, KAIST

2. Ga-Young Lee (URP program, Winter 2013 - Spring 2014) – CS, KAIST

3. Kijung Shin (Jan. – Aug. 2014) – CSE, SNU

4. Sungjae Hong (URP program, Summer 2014 – Summer 2015 ) – CS, KAIST

5. ByungSoo Jeon (Jan. 2015 – June 2016) – CS, KAIST

6. Injae Yoo (Mar. 2015 – Aug. 2015 ) – Math, KAIST

7. Minjoo Kim (Mar. 2015 – Aug. 2015) – Math, KAIST

8. Jungwoo Lee (Jan. 2016 – Dec. 2017) – ME, SNU

9. Junghwan Kim (Jan. 2016 – May 2018) – IE, SNU

10. Woojung Jin (Jan. 2016 – Apr. 2018) – EE, SNU

11. Haekyu Park (June 2016 – May 2018) – CSE, SNU

12. Minkyung Lee (June 2016 – Dec. 2016) – CSE, SNU

13. Hyeokhwa Seong (June 2016 – Oct. 2016) – CSE, SNU

14. Sunmin Lee (June 2016 – Feb. 2017) – CSE, SNU

15. Sejoon Oh (July 2016 – May 2018) – CSE, SNU

16. Dongjin Choi (Aug. 2016 – Jan. 2018) – EE, SNU

17. Ji-Eun Lee (Oct. 2016 – Aug. 2017) – Econ., SNU

18. Saehan Jo (Oct. 2016 – July 2017) – CSE, SNU

19. Junseok Gye (Jan. 2017 – July 2017) – CSE, SNU

20. Inhye Yeom (Jan. 2017 – June 2017) – Vocational Education and Workforce Development, SNU

21. Taebum Kim (Jan. 2018 – Dec. 2018) – Physics, SNU

22. Junhyun Koh (Apr. 2018 - ) – Psychology, Seoul National University

23. Moonjeong Park (July. 2018 – Jan. 2019) – B.S., DGIST

24. SeungCheol Park (Sep. 2018 – Feb. 2019) – Naval Architecture and Ocean Engineering, SNU

25. Dawon Ahn (Jan. 2019 - ) – Math, Chonnam National Univ.

26. BumJoon Park (Jan. 2019 - ) – CSE, SNU

UNDERGRADUATE ADVISING (thesis)

1. Jaemin Yoo (graduated: Feb. 2016)

2. Danny Youm (graduated: Feb. 2016)

3. Junki Jang (graduated: Feb. 2017)

4. Minkyung Lee (graduated: Feb. 2017)

5. Jinho Suh (graduated: Aug. 2017)

6. Wonryong Ryou (graduated: Aug. 2018)

RESEARCH INTERNS

1. Namyong Park (Jan. 2016 – July 2017) – M.S. in Computer Science and Engineering, Seoul

National University

2. Minji Yoon (Apr. 2017 – June 2018) – M.S. in Computer Science and Engineering, Seoul

National University

3. Minyong Cho (Mar. 2018 - ) – B.S. in Mathematics, Kyung Hee University

4. Junghoon Kim (June 2018 – Feb. 2019) – B.A. in Economics, New York University

5. Sumin Hong (June 2018 – Feb. 2019) – B.S. in Software Engineering, Korea Aerospace

University

Ph.D. COMMITTEES

1. Jae-Pil Heo (defense: 11/2014) – CS, KAIST (Advisor: Sung Eui Yoon)

13

2. Min-Joong Lee (proposal: 5/2/2014) – CS, KAIST (Advisor: Chin-Wan Chung)

3. Jong-Ryul Lee (defense: 5/2014) – CS, KAIST (Advisor: Chin-Wan Chung)

4. Jun-Sung Kim (defense: 12/2014) – CS, KAIST (Advisor: Kyu-Young Whang)

5. Chong Sok Lim (defense: 11/2014) – CS, KAIST (Advisor: Soon Joo Hyun)

6. Soo Hyung Kim (proposal: 11/2014) – CS, KAIST (Advisor: Yoon Joon Lee)

7. Woo Lam Kang (proposal: 11/2014) – CS, KAIST (Advisor: Yoon Joon Lee)

8. Seungbum Jo (defense: 2/2016) – CSE, SNU (Advisor: Srinivasa Rao Satti)

9. Byoung-Hee Kim (defense: 7/2017) – CSE, SNU (Advisor: Byoung-Tak Zhang)

10. Myoungji Han (defense: 12/2017) – CSE, SNU (Advisor: Kunsoo Park)

11. Boyeon Jang (proposal: 11/2018) – CSE, SNU (Advisor: Chong-kwon Kim)

12. Sihyun Jung (proposal: 5/2018) – CSE, SNU (Advisor: Chong-kwon Kim)

13. Jaehoon Lee (proposal: 11/2018) – CSE, SNU (Advisor: Chong-kwon Kim)

M.S. COMMITTEES

1. Seunghyeon Moon (defense: 6/2013) – KSE, KAIST (Advisor: Jae-Gil Lee)

2. Soo-Ho Lee (defense: 6/2013) – CS, KAIST (Advisor: Yoon Joon Lee)

3. Ha-Myung Park (defense: 6/2013) – CS, KAIST (Advisor: Chin-Wan Chung)

4. Dae Joong Kim (defense: 12/2013) – CS, KAIST (Advisor: Kee-Eung Kim)

5. Dae Han Choi (defense: 12/2013) – CS, KAIST (Advisor: Yoon Joon Lee)

6. Seonggyu Lee (defense: 6/2014) – WebST, KAIST (Advisor: Sung-Hyon Myaeng)

7. Hyeoneun Kim (defense: 6/2014) – CS, KAIST (Advisor: Kee-Eung Kim)

8. JungHoon Kim (defense: 12/2014) – KSE, KAIST (Advisor: Jae-Gil Lee)

9. Kyu Hyeon Cho (defense: 12/2014) – CS, KAIST (Advisor: Kyu-Young Whang)

10. Yoon Kyung Kim (defense: 12/2014) – CS, KAIST (Advisor: Yoon Joon Lee)

11. Ji Wan Chung (defense: 12/2014) – CS, KAIST (Advisor: Sue Moon)

12. Hee Sung Jin (defense: 12/2014) – CS, KAIST (Advisor: Myung Ho Kim)

13. Jin Ho Kim (defense: 6/2015) – CS, KAIST (Advisor: Sung-Hyon Myaeng)

14. Pablo Estrada – Computational Science and Technology, SNU (Advisor: Kyomin Jung)

15. Seongho Son (defense: 12/2017) – CSE, SNU (Advisor: Byoung-Tak Zhang)

16. Ceyda Cinarel (defense: 12/2017) – CSE, SNU (Advisor: Byoung-Tak Zhang)

17. Juyong Kim (defense: 12/2017) – CSE, SNU (Advisor: Gunhee Kim)

18. Yunseok Jang (defense: 12/2017) – CSE, SNU (Advisor: Gunhee Kim)

PROFESSIONAL SERVICE

EDITORSHIPS AND BOARDS

1. Member of the Board of Directors, KIISE Database Society of Korea, Aug. 2013 – current

2. Member of the Editorial Board of KIISE Journal of Database, Mar. 2014 – current

3. Associate Editor, Communications of the Korean Institute of Information Scientists and

Engineers, 2016

4. Member of the Board of Directors, Korean Institute of Information Scientists and Engineers

(KIISE), 2016

CONFERENCE ORGANIZATION

1. Co-chair, 1st International Workshop on Big Graph Mining, 2014, in conjunction with WWW

2014

2. Tutorial Co-Chair, 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining

14

(PAKDD), 2015

3. Workshop Co-Chair, 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining

(PAKDD), 2017

4. PC Co-Chair, Korea-Japan Database Workshop (KJDB), 2018

PROGRAM COMMITTEE MEMBER (CONFERENCE)

1. 22nd International Conference on World Wide Web (WWW), 2013

2. European Conference on Machine Learning and Principles of Knowledge Discovery in Databases

(ECML/PKDD), 2013

3. 40th International Conference on Very Large Data Bases (VLDB), 2014

4. 23rd International Conference on World Wide Web (WWW), 2014

5. 8th International AAAI Conference on Weblogs and Social Media (ICWSM), 2014

6. 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2014

7. 25th International Conference on Computational Linguistics (COLING), 2014


(ECML/PKDD), 2014

9. IEEE International Conference on Data Mining (ICDM), 2014

10. 31st IEEE International Conference on Data Engineering (ICDE), 2015

11. 18th International Conference on Extending Database Technology (EDBT), 2015

12. 8th ACM International Conference on Web Search and Data Mining (WSDM), 2015

13. 2nd International Conference on Big Data and Smart Computing (BigComp), 2015

14. 9th International AAAI Conference on Web and Social Media (ICWSM), 2015

15. 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015

16. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

(ASONAM), 2015


(ECML/PKDD), 2015

18. IEEE International Conference on Big Data (BigData), 2015


20. 31st ACM/SIGAPP Symposium on Applied Computing (SAC), SONAMA Track, 2016

21. 3rd International Conference on Big Data and Smart Computing (BigComp), 2016

22. 25th International Conference on World Wide Web (WWW), 2016

23. 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016


(ECML/PKDD), 2016

25. 25th ACM International Conference on Information and Knowledge Management (CIKM), 2016

26. 6th International Conference on Emerging Databases - Technologies, Applications, and Theory

(EDB), 2016

27. 3rd IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2016

28. 4th International Conference on Big Data and Smart Computing (BigComp), 2017

29. 32nd ACM/SIGAPP Symposium on Applied Computing (SAC), SONAMA Track, 2017

30. 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2017


(ECML/PKDD), 2017

32. 7th International Conference on Emerging Databases - Technologies, Applications, and Theory

(EDB), 2017


34. 5th International Conference on Big Data and Smart Computing (BigComp), 2018


15

36. 33rd ACM/SIGAPP Symposium on Applied Computing (SAC), SONAMA Track, 2018

37. The Web Conference (WWW), 2018

38. Korean Database Conference (KDBC), 2017

39. The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018

(Senior PC member)



42. IEEE International Conference on Data Mining (ICDM), 2018

43. 12nd ACM International Conference on Web Search and Data Mining (WSDM), 2019

44. The Web Conference (WWW), 2019

45. Korean Database Conference (KDBC), 2018

46. 34th ACM/SIGAPP Symposium on Applied Computing (SAC), SONAMA Track, 2019


48. IEEE International Conference on Data Mining (ICDM), 2019, Area Chair

PROGRAM COMMITTEE MEMBER (WORKSHOP)

1. International Workshop on Finding Patterns of User Behaviors in NEtwork and MObility Data,

2011, in conjunction with ECML/PKDD 2011

2. ICDM 2011 Workshop on Data Mining Technologies for Computational Creative Intelligence,

2011

3. 10th Workshop on Mining and Learning With Graphs (MLG), 2012, in conjunction with ICML

2012

4. 1st Dynamic Networks Management and Mining (DyNetMM), 2013, in conjunction with

SIGMOD/PODS 2013

5. 2nd International Workshop on Large Scale Network Analysis (LSNA), 2013, in conjunction

with WWW 2013

6. 11th Workshop on Mining and Learning With Graphs (MLG), 2013, in conjunction with KDD

2013

7. 1st International Workshop on Mining Social Data at Work (MSDW), 2013, in conjunction with

ICDM 2013

8. Big Data Workshop, organized by KAIST-Microsoft Research Collaboration Center, 2014

9. Workshop on Interactive Data Exploration and Analytics (IDEA), 2014, in conjunction with

KDD 2014


KDD 2015


KDD 2016

JOURNAL REVIEWS

1. IEEE Transactions on Knowledge and Data Engineering (TKDE): 2013 – 2016, 2019

2. ACM Transactions on Knowledge Discovery from Data (TKDD): 2011 - 2017

3. The VLDB Journal: 2015

4. Data Mining and Knowledge Discovery (DAMI): 2012, 2013

5. Data & Knowledge Engineering (DKE): 2013, 2016

6. Machine Learning: 2018

7. ACM Journal on Experimental Algorithmics (JEA): 2011

8. Journal of Computer Science and Engineering (JCSE): 2013, 2015

9. Journal of Zhejiang University Science C (ZUSC): 2012

16

CONFERENCE REVIEWS

1. ACM SIGMOD International Conference on Management of Data, 2010

2. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2010


(ECML/PKDD), 2010

4. 21st International Conference on World Wide Web (WWW), 2012

u kang - data miningukang/ukang-cv.pdf · 3 j4. u kang, martial hebert, and soonyong park, fast and...

Documents