Database and Information Systems
The rapid growth of big data creates unprecedented demand and opportunities for developing powerful intelligent information systems that help people manage and extract knowledge from data.
Our faculty work on a wide range of research problems, tackling the many challenges associated with developing such intelligent systems and their applications. Research includes helping people search and find relevant data and information; mining massive amounts of heterogeneous data sets to discover actionable knowledge; optimizing the entire workflow of data access, analytics, and exploration; and analyzing large social networks and to optimize human-computer collaboration centered on data.
Our faculty work closely with industry, and many of our algorithms are used in a wide range of information system applications, especially in database and data analytics systems, data mining systems, search engines, and web information service systems.
CS Faculty, Affiliated Faculty, and Their Research Interests
|Abdussalam Alawini||Data Provenance, Scientific Data Management, Data Citation, Workflow Management, Machine Learning|
|Catherine Blake, School of Information Sciences||Text Mining, Information Synthesis, Collaborative Information Behaviors, Recognizing Textual Entailment, Summarization, Evidence-Based Discovery, Meta-Analysis, Socio-Technical Systems|
|Robert Brunner, Astronomy||Cosmological Data Mining|
|Kevin C. Chang||Data Mining, Database Systems, Information Retrieval, Web Search/Mining, Social Media Analytics|
|Jiawei Han||Data Mining, Text Mining, Information Networks, Database Systems, Data Analytics, Data Science Applications|
|Heng Ji||Natural Language Processing, especially on Information Extraction and Knowledge Base Population, as well as its connections with Computer Vision and Natural Language Generation|
|Daniel S. Katz, NCSA||Resilience and Fault-Tolerance, Many-Task Computing, Parallel and Distributed Computing, Sustainable and Open Science Software|
|Bertram Ludascher, School of Information Sciences||Data and Knowledge Management, Scientific Workflow Systems, Data Curation|
|Yongjoo Park||Database Systems, Big Data Analytics, Approximate Computing, Machine Learning for Systems|
|Bruce Schatz, Medical Information Science||Medical Informatics, Mobile Health|
|Victoria Stodden, School of Information Sciences||Reproducibility in Computational Science, Data Science, Policy Issues Surrounding Open Data/Code Sharing|
|Jimeng Sun (joining Spring 2020)||Deep Learning for Drug Discovery, Clinical Trial Optimization, Computational Phenotyping, Clinical Predictive Modeling, Mobile Health and Health Monitoring, Tensor Factorization, and Graph Mining|
|Hari Sundaram||Network Analysis, Behavioral Modeling, Applications of Game Theory|
|Hanghang Tong||Data Mining, Network and Graph Mining|
|Shaowen Wang, Geography and Geographic Information Science||Computational and Geographic Information Science; CyberGIS; Multi-Scale Geospatial Problem Solving|
|Ouri Wolfson, Department of Computer Science, University of Illinois Chicago||Spatial Databases, Computational Transportation, Location-Based Services, Mobile Data Management, Connectomics|
|ChengXiang Zhai||Intelligent Information Systems, Information Retrieval, Data Mining, Big Data Applications|
|Aditya Parameswaran, University of California, Berkeley||Data Management, Data Mining, Database Theory, Interactive Systems, Crowdsourced Computation|
|Dan Roth, University of Pennsylvania||Knowledge Representation, Natural Language Processing, Machine Learning|
Database and Information Systems Research Efforts and Groups
- Carl R. Woese Institute for Genomic Biology (IGB)
- Comp-Gen Initiative in the Carl R. Woese Institute for Genomic Biology
- Data Analytics Subprogram in the Advanced Digital Sciences Center
- Information Network Academic Research Center (INARC)
- KnowEnG, an NIH Center for Excellence for Big Data to Knowledge (BD2K) in the Carl R. Woese Institute for Genomic Biology
- Midwest Big Data Hub
The Yahoo!-DAIS Seminar is held on Thursdays at 1 PM in 3403 SC. Students who take the DAIS Seminar for credit can miss up to two seminars. Speakers are announced on the DAIS mailing list (as are other items of interest to the DAIS community). It is quick and easy to subscribe to the DAIS mailing list.