Kevin Chen-Chuan Chang

Electrical and Computer Engineering
Kevin Chen-Chuan Chang
Professor
  • Computer Science
2134 Siebel Center for Comp Sci
201 N. Goodwin Ave.
Urbana Illinois 61801

For more information

Profile

Education

  • Ph.D. Electrial Engineering, Stanford University, 2001

Biography

Kevin C. Chang is a Professor in Computer Science, University of Illinois at Urbana-Champaign. He received a BS from National Taiwan University and PhD from Stanford University, in Electrical Engineering. His research addresses large scale information access, for search, mining, and integration across structured and unstructured big data, with current focuses on "entity-centric" Web search/mining and social media analytics. He received two Best Paper Selections in VLDB 2000 and 2013, an NSF CAREER Award in 2002, an NCSA Faculty Fellow Award in 2003, IBM Faculty Awards in 2004 and 2005, Academy for Entrepreneurial Leadership Faculty Fellow Award in 2008, and the Incomplete List of Excellent Teachers at University of Illinois in 2001, 2004, 2005, 2006, 2010, and 2011. He is passionate to bring research results to the real world and, with his students, co-founded Cazoodle, a startup from the University of Illinois, for deepening vertical "data-aware" search over the web.

Professional Highlights

  • PC for SIGMOD, VLDB, ICDE, KDD, ICDM, WWW, SIGIR, WISDM, AAAI in recent years.
  • Co-chair, Track “Bringing Unstructured and Structured Data”, 22nd International World Wide Web Conference (WWW 2013), August 2012 – April 2013.
  • Co-chair, Workshop Program, 22rd International World Wide Web Conference (WWW 2014), August 2013 – April 2014.
  • Co-chair, Workshop Program, 31st IEEE International Conference on Data Engineering (ICDE 2015), May 2014 – April 2015.
  • Associate Editor, IEEE Transactions on Knowledge and Data Engineering (TKDE), January 2013 – present.
  • Associate Editor, Proceedings of the VLDB Endowment (PVLDB), April 2014 – present.

Research Statement

I lead the FORWARD Group, which is part of the larger Data and Information Systems Laboratories, at the CS department of UIUC. Our research overall aims at bridging structured and unstructured big data--- to bring structured/semantic-rich access to the myriad and massive unstructured data which accounts for most of the world's information. Therefore, our research spans across data mining, data management/databasesinformation retrieval, machine learning, with current efforts focusing on interactive data management, entity-centric Web search and mining, social media analytics, and social network mining. As our objectives, we aim at developing novel systems, principled algorithms, and formal theories that ultimately deliver real world applications. As our approaches, we seek to be inspired by and learn from the data we are tackling-- i.e., we believe the key to tame big data is to learn the wisdom hidden in the large scale of the data.

Graduate Research Opportunities

I am looking for PhD/MS students to join the research project at the FORWARD Lab. Our current projects studies theories and algorithms as well as build systems for real world data management applications for Web search/mining and social media analytics. Take a look at our recent publications to see what we work on.

Undergraduate Research Opportunities

Our FORWARD Lab welcome undergraduate students to participate in research with us. You will join our projects to work with graduate students for design algorithms and implement systems in data management, data mining, and social media/network analytics. 

Research Interests

  • data mining, database systems, machine learning, information retrieval, web search/mining, social media analytics

Articles in Conference Proceedings

  • Mobile User Verification/Identification using Statistical Mobility Profile. M. Lin, H. Cao, V. Zheng, K. C.-C. Chang, and S. Krishnaswamy. In International Conference on Big Data and Smart Computing (BigComp 2015), pages 15-18, 2015.
  • Mobility Profiling for User Verification with Anonymized Location Data. M. Lin, H. Cao, V. Zheng, K. C.-C. Chang, and S. Krishnaswamy. In International Joint Conference on Artificial Intelligence (IJCAI 2015), 2015.
  • Unifying Learning to Rank and Domain Adaptation: Enabling Cross-Task Document Scoring. M. Zhou and K. C.-C. Chang. In KDD 2014, 2014.
  • Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically. Y. Fang, K. C.-C. Chang, and H. W. Lauw. In ICML 2014, 2014.
  • User Profiling in an Ego Network: Co-profiling Attributes and Relationships. R. Li, C. Wang, and K. C.-C. Chang. In WWW 2014, pages 819-830, April 2014.
  • Privacy Risk in Anonymized Heterogeneous Information Networks. A. Zhang, X. Xie, K. Chang, C. Gunter, J. Han, and X. Wang. In EDBT 2014, pages 595-606, March 2014.
  • Towards a Social Media Analytics Platform: Event Detection and User Profiling for Twitter. M. Gupta, R. Li, and K. C.-C. Chang. In WWW 2014, pages 193-194, April 2014. Tutorial description.
  • Enabling Entity-Centric Document Filtering by Meta-Feature-based Feature Mapping. M. Zhou and K. C.-C. Chang. In CIKM 2013, pages 119-128, 2013.
  • RoundTripRank: Graph-based Proximity with Importance and Specificity. Y. Fang, K. C.-C. Chang, and H. W. Lauw. In ICDE 2013, pages 613-624, 2013.
  • Learning to Rank from Distant Supervision: Exploiting Noisy Redundancy for Relational Entity Search. M. Zhou, H. Wang, and K. C.-C. Chang. In ICDE 2013, pages 829-840, 2013.

Journal Editorships

  • Associate Editor, Proceedings of the VLDB Endowment (PVLDB), April 2014 – present.
  • Associate Editor, IEEE Transactions on Knowledge and Data Engineering (TKDE), January 2013 – present.

Conferences Organized or Chaired

  • Co-chair, Workshop Program, 22rd International World Wide Web Conference (WWW 2014), August 2013 – April 2014. 
  • Co-chair, Workshop Program, 31st IEEE International Conference on Data Engineering (ICDE 2015), May 2014 – April 2015.
  • Co-chair, Track “Bringing Unstructured and Structured Data”, 22nd International World Wide Web Conference (WWW 2013), August 2012 – April 2013.

Teaching Honors

  • UIUC List of Teachers Ranked as Excellent by Their Students, Fall 2001, Spring 2004, Fall 2005, Spring 2006, Fall 2010, Fall 2011.

Research Honors

  • Academy of Entrepreneurial Leadership Faculty Fellow Award, 2008.
  • IBM Faculty Award, 2005.
  • IBM Faculty Award, 2004.
  • NCSA (National Center for Supercomputing Applications) Faculty Fellows Award, 2003.
  • National Science Foundation CAREER Award 2002.
  • Best-Papers Selections of VLDB 2000 and VLDB 2013

Courses Taught

  • CS 411 - Database Systems
  • CS 412 - Introduction to Data Mining
  • CS 511 - Advanced Data Management
  • CS 591 - Advanced Seminar