Ihab F. Ilyas

My research focuses on data quality, data cleaning, and data integration, with a particular interest in applying machine learning to large-scale structured data problems. I have been fortunate to work with outstanding students and collaborators, and to translate research ideas into industrial systems and startups.

Career Highlights

2024	Fellow of the Royal Society of Canada
2022	IEEE Fellow
2020	ACM Fellow
2019	CEO & Co-founder, Inductiv (AI for structured data cleaning) — acquired by Apple
2018	NSERC–Thomson Reuters Chair of Data Quality
2017	ACM SIGMOD vice-chair
2016	VLDB Endowment Board of Trustees
2015	ACM SIGMOD Best Demo Award
2014	Google Faculty Award · ACM Distinguished Scientist · NSERC Discovery Accelerator
2013	Co-founder, Tamr (ML for large-scale data integration) · Cheriton Faculty Fellowship
2008	Ontario Early Researcher Award
2006	IBM CAS Faculty Fellow (through 2010)

Books

Data Cleaning — ACM Books.
Ihab F. Ilyas and Xu Chu.

Startups & Software

Hiddenweights — An AI startup with a bold idea to fully automate AI training, founded 2024.

Inductiv — Waterloo-based startup on using AI for structured data cleaning, 2019. Acquired by Apple.

Tamr — A leading startup applying machine learning to large-scale data integration, founded 2013.

HoloClean (holoclean.io) — Open-source platform for ML-based error detection and repair.

Surveys & Long Papers

Probabilistic Ranking Techniques in Relational Databases. Synthesis Lectures on Data Management, March 2011, 71 pp. Ihab F. Ilyas and Mohamed A. Soliman.
Trends in Cleaning Relational Data: Consistency and Deduplication [PDF]. Foundations and Trends in Databases, Vol. 5, No. 4, pp. 281–393, November 2015. Ihab F. Ilyas and Xu Chu.

Writing

AI Should Not Leave Structured Data Behind! — Towards Data Science
The Quest for High Quality Data — O'Reilly Media
How to Clean Noisy and Erroneous Big Data Using Machine Learning — Tamr Blog
Data Cleaning is a Machine Learning Problem that Needs Data Systems Help! — ACM SIGMOD Blog
Three Enablers for ML in Data Unification: Trust, Legacy and Scale — O'Reilly Media
HoloClean: A Machine Learning Approach to Data Cleaning

Students & Postdoctoral Fellows

PhD Alumni

Chang Ge (2022) — Asst. Prof., U. Minnesota
Alireza Heydari (2021)
Hemant Saxena (2021) — SAP
Mina Farid (2020) — Inductiv (Apple)
Xu Chu (2017) — Asst. Prof., Georgia Tech
Jeffrey Pound (2013) — SAP
George Beskales (2012) — Tamr Inc.
Amr El-Helw (2012) — Greenplum
Mohamed A. Soliman (2010) — Greenplum

Postdoctoral Fellows

Aoqian Zhang (2020)
Shrinu Kushagra (2020)
Lanjun Wang (2017)
Alexandra Roatis (2016)

Masters Alumni

Sobhan Niknamian (2021)
Omar Attia (2021) — Inductiv (Apple)
Michael Azmy (2019)
Jian Li (2018) — Google
Anam Shadab (2018)
John Morcos (2015) — Microsoft
Hella Hoffmann (2015) — Thomson Reuters
Artur Galiullin (2013)
Mina Farid (2012)
Mina Saleeb (2012) — Oracle
Hiren Patel (2010) — Microsoft
Nan Jiang (2009)

Ihab Francis Ilyas