Photo credit: Hector Garcia-Molina

 

Theodoros (Theo) Rekatsinas

I am an assistant professor at the University of Wisconsin-Madison. I am a member of the UW-Madison Database Group.

Before that I was a Postdoc at Stanford with Chris Ré. I received my Ph.D. in Computer Science from the University of Maryland. My advisors were Amol Deshpande and Lise Getoor.

My research interests lie in the field of databases, with a focus on data integration and uncertain data management. During the past years, I have been working on the problem of data source selection, which studies how one can identify valuable data sources for integration.

Email  /  Google Scholar  /  LinkedIn



News

  • HoloClean: Scalable data cleaning driven by probabilistic inference. Combine all your signals from integrity constraints to outliers and clean your data! Read our blog post.
  • SLiMFast: Our formal framework for data fusion and data quality was accepted at SIGMOD 2017. Want to find how SLiMFast can help with fake news? Read our blog post.
  • My thesis on Quality-Aware Data Source Management was awarded the Larry S. Davis Dissertation Award



Publications

NEW! Fonduer: Knowledge Base Construction from Richly Formatted Data
Sen Wu, Luke Hsiao, Xiao Cheng, Braden Hancock, Theodoros Rekatsinas, Philip Levis and Christopher Ré
Submitted

HoloClean: Holistic Data Repairs with Probabilistic Inference
Theodoros Rekatsinas, Xu Chu, Ihab F. Ilyas and Christopher Ré
VLDB 2017

SLiMFast: Guaranteed Results for Data Fusion and Source Reliability
Theodoros Rekatsinas, Manas Jogklekar, Hector Garcia-Molina, Aditya Parameswaran and Christopher Ré
ACM SIGMOD 2017

Forecasting Rare Disease Outbreaks from Open Source Indicators
Theodoros Rekatsinas, Saurav Ghosh, Sumiko Mekaru, Elaine Nsoesie, John Brownstein, Lise Getoor and Naren Ramakrishnan
Journal of Statistical Analysis and Data Mining, Best of SDM Special Issue, 2016

SourceSight: Enabling Effective Source Selection
Theodoros Rekatsinas, Amol Deshpande, Xin Luna Dong, Lise Getoor and Divesh Srivastava
ACM SIGMOD, 2016

HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades
Xinran He, Theodoros Rekatsinas, James Foulds, Lise Getoor, and Yan Liu
International Conference on Machine Learning (ICML), 2015

StoryPivot: Comparing and Contrasting Story Evolution
Anja Gruenheid, Donald Kossmann, Theodoros Rekatsinas, and Divesh Srivastava
ACM SIGMOD, 2015

SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources Best Paper Award
Theodoros Rekatsinas, Saurav Ghosh, Sumiko Mekaru, Elaine Nsoesie, John Brownstein, Lise Getoor and Naren Ramakrishnan
SIAM International Conference on Data Mining (SDM), 2015

Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration
Theodoros Rekatsinas, Xin Luna Dong, Lise Getoor and Divesh Srivastava
7th Biennial Conference on Innovative Data Systems Research (CIDR), 2015

Characterizing and selecting fresh data sources
Theodoros Rekatsinas, Xin Luna Dong and Divesh Srivastava
ACM SIGMOD, 2014

SPARSI: partitioning sensitive data amongst multiple adversaries
Theodoros Rekatsinas, Amol Deshpande and Ashwin Machanavajjhala
Proceedings of the VLDB Endowment Volume 6 Issue 13, 2013

Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss
Ben London, Theodoros Rekatsinas, Bert Huang and Lise Getoor
NIPS 2012 Workshop on Spectral Algorithms for Latent Variable Models

Local structure and determinism in probabilistic databases
Theodoros Rekatsinas, Amol Deshpande and Lise Getoor
ACM SIGMOD 2012

Fuzzy rule based neuro-dynamic programming for mobile robot skill acquisition on the basis of a nested multi-agent architecture Best Of Conference
John Karigiannis, Theodoros Rekatsinas and Costas S. Tzafestas
IEEE International Conference on Robotics and Biomimetics (ROBIO), 2010



Manuscripts

Adaptive Querying Strategies for Efficient Crowdsourced Data Extraction
Theodoros Rekatsinas, Amol Deshpande and Aditya Parameswaran, 2016

Quality-Aware Data Source Management
Theodoros Rekatsinas, Doctoral Dissertation, 2015



Teaching

Database Management Systems
(CS564, Computer Sciences Department, University of Wisconsin-Madison)
Fall 2017



Service

PC-Member: SIGMOD 2017-2018, VLDB 2017, NIPS 2015-2017, IJCAI 2016, CIKM 2017

Reviewer: ICML, SIGMOD, VLDB, WSDM, WWW, TKDE, TSAS, SIGMOD Record