Kevin Chenchuan Chang
For more information
- Ph.D. Electrial Engineering, Stanford University, 2001
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.
- PC Members, SIGMOD, VLDB, ICDE, KDD, EDBT, ICDM, WWW, ASONAM, SIGIR, WSDM, CIKM, AAAI, Recent years.
- Associate Editor, Proceedings of the VLDB Endowment (PVLDB), 2014 - 2015.
- Area Editor, Encyclopedia of Database Systems, 2014 - 2016.
- Workshop Co-chair, 31st IEEE International Conference on Data Engineering (ICDE 2015), 2014 - 2015.
- Associate Editor, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2013 - 2017.
- Workshop Co-chair, 22rd International World Wide Web Conference (WWW 2014), 2013 - 2014.
- PC Co-chair, Track “Bringing Unstructured and Structured Data”, 2012 - 2013.
- Best Paper Award Committee, ACM International Conference on Web Search and Data Mining, 2012.
- Senior PC, ACM International Conference on Web Search and Data Mining, 2011.
- Co-chair, Demonstration Track, ICDE 2011, 2011.
- Senior PC, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2010.
- Area Editor, Encyclopedia of Database Systems, 2007 - 2009.
- Workshop Chair, APWeb 2007, 2007.
- Steering Committee, International Workshop on Information Integration on the Web (IIWeb 2007) at AAAI, 2007.
- Workshop Chair, ACM SIGMOD 2006 Conference, 2006.
- Co-chair, International Workshop on Information Integration on the Web (IIWeb 2006) at WWW, 2006.
- Co-chair, International Workshop on Challenges in Web Information Retrieval and Integration (WIRI 2006) at ICDE, 2006.
- Guest Editor, SIGKDD Explorations 6(2) Special Issue on Web Content Mining, 2004.
- Chair, NSF DIMACS Center Tutorial/Summer School on Social Choice and Computer Science, 2004.
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/databases, information 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.
- data mining, database systems, machine learning, information retrieval, web search/mining, social media analytics
- Autonomous Systems and Artificial Intelligence
- Cognitive computing
- Data science and analytics
- Data/Information Science and Systems
- Decision science
- Machine learning
- Network science and engineering
- Socio-technical systems and networking
Articles in Conference Proceedings
- 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.
- 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.
- Learning with Smoothness: Pointwise, Graph-based, Probabilistic. Y. Fang, K. C.-C. Chang, and H. W. Lauw. In ICML 2014.
- Unifying Learning to Rank and Domain Adaptation: Enabling Cross-Task Document Scoring. M. Zhou and K. C.-C. Chang. In KDD 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.
- UIUC List of Teachers Ranked as Excellent by Their Students, Fall 2001, Spring 2004, Fall 2005, Spring 2006, Fall 2010, Fall 2011, Fall 2019
- 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 Very Large Data Bases (VLDB) 2000 and 2013
- CS 411 - Database Systems
- CS 412 - Introduction to Data Mining
- CS 511 - Advanced Data Management
- CS 598 - Listening to Social Universe