At UW-Madison


  • NSF CISE Small Award, 2019
  • NSF CISE CRII Award, 2018
  • Amazon Research Award, 2018
  • Hilldale Faculty/Undergraduate Research Fellowship, UW-Madison 2018
  • Moore Postdoctoral Fellow, Stanford CS 2015
  • Larry S. Davis Doctoral Dissertation Award, University of Maryland, College Park 2015
  • SIAM International Conference on Data Mining, Best Resarch Paper Award 2015
  • Microsoft Research Ph.D. Fellowship Finalist, 2013
  • Finalist for the T.J. Tarn Best Paper Award in Robotics, IEEE ROBIO 2010

Recent Service

  • Associate Editor for the ACM Journal of Data and Information Quality
  • Leadership Team, American Family Data Science Institute at UW-Madison, 2019 - 2020
  • Member of Organizing Committee: MLSys 2019, MLSys 2020, MLSys 2021, VLDB 2021
  • PC-Area Chair: SIGMOD 2019
  • PC-Member: NeuRIPS 2015 – 2019, IJCAI 2016, ICML 2018 – 2019, VLDB 2017, 2020,SIGMOD 2017–2020, 2022, CIKM 2017–2018,

Bio (for talks)

Theo Rekatsinas is a Research Engineer at Apple and a lead in the Apple Knowledge Graph team. Theo co-founded Inductiv (now part of Apple), a company that developed AI solutions for identifying and correcting errors in data. Theo was also a Professor of Computer Science at ETH Zürich and the University of Wisconsin-Madison. Theo’s research focuses on scalable machine learning over billion-scale relational and graph-structured data. His research focuses on exploring the fundamental connections between data preparation, data integration, and knowledge management with statistical machine learning and probabilistic inference. Theo holds PhD and Masters Degrees in Computer Science from the University of Maryland - College Park. He also holds a Bachelors and Masters Degree in Electrical Engineering from the National Technical University of Greece.