Daisy Zhe Wang

Assistant Professor
Director, Data Science Research Lab
Computer and Information Science and Engineering (CISE)
College of Engineering, University of Florida
Gainesville, FL 32611
Office: E456 CSE Building
Phone: (352) 562-8936; Fax: (352) 392-1220
Office Hours: Monday/Wednesday 3:50-4:50pm or by appointment

DSR Lab ShortBio Prospective Students Berkeley Homepage

My research interest is in building systems and designing algorithms to support better data analysis, where better can mean: more efficient/scalable, more advanced (using statistical machine learning), more accurate, more interactive, self-improving, and easier to use. I pursue research topics such as probabilistic databases, large-scale advanced data analysis, and query-driven interactive machine learning. Currently, I am particularly interested in bridging data management systems with statistical and probabilistic models and tools.

If you are an undergrad/graduate student interested in data science research, please refer to Prospective Students.

For more information please visit Data Science Research @ UF. I am also a member of the UFL Database Group.


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Recent News

Current Research Projects


Ph.D. Students


Teaching


Recent Selected Publications

Full List of Publications

Knowledge Expansion over Probabilistic Knowledge Bases
In Proceedings of the ACM SIGMOD International Conference on Management of Data, 2014
Yang Chen, Daisy Zhe Wang

CASTLE: Crowd-Assisted System for Textual Labeling and Extraction
In Proceedings of HCOMP 2013
Sean Goldberg, Daisy Zhe Wang, Tim Kraska

Web-Scale Knowledge Inference Using Markov Logic Networks
Proceedings of ICML workshop on Structured Learning: Inferring Graphs from Structured and Unstructured Inputs, 2013, Atlanta
Yang Chen, Daisy Zhe Wang

Knowledge Extraction and Outcome Prediction using Medical Notes
Proceedings of ICML workshop on Role of Machine Learning in Transforming Healthcare, 2013, Atlanta.
Ryan Cobb, Sahil Puri, Tezcan Ozrazgat Baslanti, Azra Bihorac, Daisy Zhe Wang

GPText: Greenplum Parallel Statistical Text Analysis Framework.
Proceedings of SIGMOD workshop on Data Analytics in the Cloud, 2013, New York.
Kun Li, Christan Grant, Daisy Zhe Wang, Sunny Khatri, George Chitouras

MADden: Query-Driven Statistical Text Analytics
Proceedings of ACM CIKM, 2012
Christan Grant, Jordan Gumbs, Kun Li, Daisy Zhe Wang, George Chitouras

Automatic Knowledge Base Construction using Probabilistic Extraction, Deductive Reasoning, and Human Feedback
Proceedings of NAACL-HLT, 2012, short paper
Daisy Zhe Wang, Yang Chen, Sean Goldberg, Christan Grant, and Kun Li

The MADlib Analytics Library or MAD Skills, the SQL
Proceedings of VLDB, 2012
Joseph M. Hellerstein, Christoper Re, Florian Schoppmann, Daisy Zhe Wang, Eugene Fratkin,
Aleks Gorajek, Kee Siong Ng, Caleb Welton, Xixuan Feng, Kun Li, and Arun Kumar

Hybrid In-Database Inference for Declarative Information Extraction sigmod11 sigmod11slides
Proceedings of ACM SIGMOD International Conference on Management of Data, 2011
Daisy Zhe Wang, Michael J. Franklin, Minos Garofalakis, Joseph M. Hellerstein,
and Michael L. Wick

Selectivity Estimation for Extraction Operators over Text Data icde11 icde11slides
Proceedings of 27th IEEE ICDE International Conference on Data Engineering, 2011
Daisy Zhe Wang, Long Wei, Yunyao Li, Frederick Reiss, and Shivakumar Vaithyanathan

Querying Probabilistic Information Extraction pvldb10 pvldb10slides
Proceedings of 36th VLDB Very Large Data Base Endowment, 2010, PVLDB Vol.3
Daisy Zhe Wang, Michael J. Franklin, Minos Garofalakis, and Joseph M. Hellerstein

Probabilistic Declarative Information Extraction icde10 icde10slides TR-pdb-ie
Proceedings of 26th IEEE ICDE International Conference on Data Engineering, 2010, short paper
Daisy Zhe Wang, Eirinaios Michelakis, Michael J. Franklin, Minos Garofalakis,
and Joseph M. Hellerstein

BayesStore: Managing Large, Uncertain Data Repositories with Probabilistic Graphical Models vldb08a vldb08slides
Proceedings of 34th VLDB Very Large Data Base Endowment, 2008
Daisy Zhe Wang, Eirinaios Michelakis, Minos Garofalakis, and Joseph M. Hellerstein

WebTables: Exploring the Power of Tables on the Web vldb08b
Proceedings of 34th VLDB Very Large Data Base Endowment, 2008
Michael Cafarella, Alon Halevy, Daisy Zhe Wang, Eugene Wu, Yang Zhang


Talks


Related Links

VLDB Endowment
ACM SIGMOD
LaTex Templates and Guides


A Parable of Modern Research

Bob has lost his keys in a room which is dark except for one brightly lit corner.
“Why are you looking under the light, you lost them in the dark!”
“I can only see here.”