Professor Ihab Ilyas has been awarded the prestigious 2024 C.C. Gotlieb Computer Award in recognition of his contributions to building large-scale machine learning systems for data integration, data cleaning and knowledge construction. Established in 2007 and named in 2012 after Calvin Carl Gotlieb, a founding figure of computing in Canada, the award celebrates outstanding Canadians whose work has significantly advanced computer science and engineering.
“Congratulations to Ihab on receiving this year’s Gotlieb Computer Award,” said Raouf Boutaba, University Professor and Director of the Cheriton School of Computer Science. “This important recognition highlights his groundbreaking research on automatic error detection, data cleaning, and imputation of dirty structured data that has influenced academia and industry alike. His work on developing automated, large-scale data cleaning and integration systems has laid the groundwork for two successful start-ups.”
Professor Ilyas has been widely recognized by peers and professional organizations. His many achievements include being named a Fellow of the Institute of Electrical and Electronics Engineers in 2021, a Fellow of the Association for Computing Machinery in 2020, and a Faculty Affiliate at the Vector Institute in 2020. Since 2018, he has held the Thomson Reuters–NSERC Industrial Research Chair in Data Cleaning.
Professor Ilyas co-founded two companies based on his research — Inductiv, a Waterloo-based start-up, now part of Apple, that uses AI for structured data cleaning, and Tamr, which focuses on large-scale data integration and cleaning. He has also held prominent roles within the academic community, including on the Board of Trustees of the Very Large Data Bases Endowment in 2016 and as Vice Chair of the ACM Special Interest Group on Data Management in 2017. He is currently a Distinguished Engineer, Proactive Intelligence, at Apple Inc., on leave from the University of Waterloo.
More about Professor Ilyas’s research
Professor Ilyas has made many substantial contributions to data management, from his work on pioneering new directions in information retrieval and rank-aware query processing to his more recent achievements in building AI systems for data integration and data quality. He has published many seminal papers at top-tier conferences on rank-aware query processing, data cleaning, generative AI models for data quality, and building large-scale knowledge bases. Many of his results have been commercialized successfully. His HoloClean project, for example, was the basis for the start-up company Inductiv. Acquired by Apple in 2020, Inductiv’s technology now underpins advanced machine learning for Siri and Spotlight, enabling next-generation AI search capabilities.
With respect to data quality, Professor Ilyas’s contributions led to the first system to use generative AI to model structured data for a variety of tasks from missing value imputation to detecting and automatically repairing errors to profiling dependencies in complex data sets. Known as HoloClean, this open-source statistical inference engine has been used by Fortune 500 companies, banks, census bureaus and large international insurance firms. This pioneering work sparked new research directions in the data management community and was among the significant contributions that led to Professor Ilyas’s fellowships in both IEEE and ACM. Professor Ilyas co-authored the leading text on data quality, titled Data Cleaning. This ACM Book serves as a reference for researchers and practitioners interested in data quality and data cleaning as well as a textbook for graduate-level studies.
In data integration, Professor Ilyas’s innovations have been commercialized by Tamr, a successful start-up that has raised more than $70 million in funding and employs more than 100 staff, serving major enterprises worldwide. His contributions in scalable record deduplication and schema mapping are at the core of the company’s technology.
More recently, Professor Ilyas led a large team at Apple to develop Saga, a next-generation knowledge construction and serving platform that powers a multitude of experiences for millions of Apple users globally. One of the most comprehensive knowledge construction and serving platforms today, Saga integrates novel techniques from data integration, semantic knowledge representation, machine learning for structured data, natural language processing, and scalable distributed query processing. The research on Saga has been presented at ACM SIGMOD, the leading international forum for database researchers, practitioners, developers, and users.