Daisy Zhe Wang – Data Science Research

Professor
Director, Data Science Research Lab
Computer and Information Science and Engineering (CISE)
College of Engineering, University of Florida
Gainesville, FL 32611
Office: Malachowsky Hall 6109
Phone: (352) 294-6677; Fax: (352) 392-1220
Office Hours: TBA

Daisy Zhe Wang is a Professor in the CISE department at the University of Florida. She is the Director of the Data Science Research Lab at UF. She obtained her Ph.D. degree from the EECS Department at the University of California, Berkeley in 2011 and her Bachelor’s degree from the ECE Department at the University of Toronto in 2005. At Berkeley, she was a member of the Database Group and the AMP/RAD Lab. She is particularly interested in bridging scalable data management and processing systems with probabilistic models and statistical methods. She currently pursues research topics such as probabilistic databases, probabilistic knowledge bases, large-scale inference engines, query-driven interactive machine learning, and crowd assisted machine learning. She received Google Faculty Award in 2014. Along with other co-authors, she received “10-Years Test-of-Time” Award for the 2018 VLDB paper on WebTables. She received Arno and Lisa Goldberg Rising Star Associate Professorship in 2019. She is inducted into the Senior Members of ACM in 2022. Her research is externally funded by NSF, NIH, DARPA, NIST, Google, Amazon, Pivotal, Greenplum/EMC, Adobe, DTCC, Sandia National Labs and Harris Corporation.

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.

News Projects Students Talks Publications Teaching Short-Bio Other

Recent News

[Oct 2025] Our paper by Michael Perez et. al.: CReLeRI: Explainable, Concept-centric, Representation, Learning, Reasoning, and Interaction Video Analysis System get accepted by ACM MM 2025.
[Aug 2025] Our paper by Reza Shahriari et. al.: MuCHEx: A Multimodal Conversational Debugging Tool for Interactive Visual Exploration of Hierarchical Object Classification get accepted by IEEE Computer Graphics and Applications 2025.
[May 2025] Our paper by Haodi Ma and Yifan Wang et. al.: LaPuda: LLM-Enabled Policy-Based Query Optimizer for Multi-modal get accepted by PAKDD 2025.
[May 2025] Our paper by Bushi Xiao et. al.: From Text to Multi-Modal: Advancing Low-Resource-Language Translation through Synthetic Data Generation and Cross-Modal Alignments get accepted by Eighth Workshop on Technologies for Machine Translation, 2025.
[Nov 2024] Our paper by Ira Harmon et. al.: A Neuro-Symbolic Framework for Tree Crown Delineation and Tree Species Classification get accepted by MDPI Remote Sensing 2024.
[Feb 2024] Our paper by Yang Bai et. al.: M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence Retrieval get accepted by COLING 2024.
[Oct 2023] Our paper by Anthony Colas and Haodi Ma et. al.: Can Knowledge Graphs Simplify Text? is published in CIKM 2023.
[Oct 2023] Our paper by Yifan Wang et. al.: LIDER: An Efficient High-dimensional Learned Index for Large-scale Dense Passage Retrieval is published in VLDM 2023.
[Jul 2023] Our research was funded ($4.4M) by DARPA about Concept-centric Representation, Learning, Reasoning, and Interaction (CReLeRI) (PI: Zhiting Hu (UCSD) Co-PIs: Jaime Ruiz (UF), Daisy Wang (UF), Eric Xing (CMU), Jun-Yan Zhu (CMU)).
[Jul 2023] Our paper by Yang Bai et. al.: MythQA: Query-Based Large-Scale Check-Worthy Claim Detection through Multi-Answer Open-Domain Question Answering is published in SIGIR 2023.
[May 2023] Our paper by Ira Harmon et. al.: Improving Rare Tree Species Classification Using Domain Knowledge is published in IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 20, 2023.
[Mar 2023] Our paper by Yifan Wang et. al.: Learned Accelerator Framework for Angular-Distance-Based High-Dimensional DBSCAN is published in EDBT 2023.

More News

Current Research Projects

ProbKB: Large-scale Probabilistic Reasoning over Uncertain Knowledge Bases
HypoGator: Distinct Hypotheses and Claims Retrieval with Stance Detection on Controversial topics
DBlytics/MADLib: Textual Retrieval/Analytics in distributed MPP frameworks over hybrid hardware
Archer: Query-Driven Machine Learning
CAMeL: Leverage Crowd Support in Probabilistic Databases
SigmaKB: Knowledge fusion, cleaning and knowledge base integration
VITA: Multimodal Knowledge Extraction and Fusion
SMARTeR: Smarter information retrieval system
Rose: Knowledge Extraction and Exchange over Electronic Health Records

Current Ph.D. Students

Haodi Ma
Jayetri Bardhan
Bai (Tony) Yang
Yifan Wang
Ira Harmon
Anthony Colas
Sean Goldberg (at Microsoft)

Ph.D. Alumni

Christan Grant (2015) University of Oklahoma
Kun Li (2015) Google Inc
Morteza Shahriari Nia (2016) Twitter Inc
Yang Chen (2016) Google Inc
Yang Peng (2017) Walmart Labs
Xiaofeng Zhou (2018) Google Inc
Dihong Gong (2019) Tencent Research
Miguel Rodriguez (2020) Google Inc
Ali Sadeghian (2021) Startup

Teaching

CAP4770, Introduction to Data Science, Spring 2022
CAP4770, Introduction to Data Science, Spring 2020
CAP4770/CAP5771, Introduction to Data Science, Fall 2019
CAP4773/CAP6779, Project In Data Science, Spring 2018
CAP4770/CAP5771, Introduction to Data Science, Fall 2017
CAP4773/CAP6779, Project In Data Science, Spring 2017
CAP4770/CAP5771, Introduction to Data Science, Fall 2016
CAP4773/CAP6779, Project In Data Science, Spring 2016
CAP4770/CAP5771, Introduction to Data Science, Fall 2015
CIS4301, Information and Data Management Systems, Spring 2015
CA4773/CIS6930, Projects in Data Science, Fall 2014
CIS6930, Introduction to Data Science/Data Intensive Computing, Spring 2014
COP5725, Data Management Systems, Fall 2013
CIS6930, Data Science: Large-scale Advanced Data Analysis, Spring 2013
COP5725, Data Management Systems, Fall 2012
CIS4301, Information and Data Management Systems, Spring 2012
CIS6930, Data Science: Large-scale Advanced Data Analysis, Fall 2011

Selected Publications

Publications Since 2012

DBLP

Google Scholar

Publications Prior to 2012

Talks

“Hypogator Hypotheses Generator”
- DARPA AIDA PI meeting, October 2021
- DARPA AIDA PI meeting, Feb 2021
- GAIA Site Visit, December 2020
- DARPA AIDA PI meeting, June 2020
- DARPA AIDA PI meeting, November 2019
- DARPA AIDA PI meeting, June 2019
- DARPA AIDA PI meeting, Jan 2019,
- DARPA AIDA PI meeting, August 2018
“HypoGator: TAC SM-KBP and DARPA AIDA Hypotheses Generation TA3 Evaluation”
- TAC SM-KBP, Feb 2021
- TAC SM-KBP, November 2019
- TAC SM-KBP, August 2018
“Neural-Symbolic models for Knowledge Graph Extraction and Reasoning”
- “When Deep Learning meets Logic” Workshop, Samsung Research at Cambridge, Feb 2021
“Rose: Virtual Health Navigator From SCD to SDoH”
- - UF Learning Health Systems and AI Symposium, Jan 2021
“Inference, Learning and Question Answering over Knowledge Graphs”
- Amazon Alexa, June 2020
“Measuring Impact of Climate Change on Tree Species”
- “Tackling Climate Change with Machine Learning” Workshop, NeurIPS 2019
“Drum: End-to-end Differentiable Rule Mining on Knowledge Graphs”
- Paper poster presentation, NeurIPS 2019
“QA with Alternative Hypotheses over Probabilistic Knowledge graph”
- DARPA AIDA PI meeting, August 2018
“Weathering the (Technology) Hypes”
- New Researcher Symposium, SIGMOD, May 2017
“Archimedes: A Probabilistic Master Knowledge Base System”
- Florida HLT Cofab, Feb 2017
“Deep Learning over Large-scale Databases and Knowledge Graphs”
- NSF IUCRC for Big Learning Planning meeting, Jan 2017
“Archimedes: A Probabilistic Knowledge Base to Combine Information Extraction from Diverse Sources”
- University of South California/Information Sciences Institute, Feb 2016

More Talks

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.”