Dr. Jiannan Wang has established himself as an intellectual leader in database systems research. In particular, he has made significant research contributions to crowdsourced data management, data cleaning, and human-in-the-loop data analytics, which won him the prestigious IEEE TCDE Rising Star Award in 2018. His CrowdER project is the pioneering work in crowdsourced entity resolution. The project was highly influential in the database community and the two CrowdER papers have received over 750 citations in total. His SampleClean project proposes several innovative ideas that can significantly reduce the data-cleaning costs for query processing and machine learning. The project was incorporated as an open-source software component in the Berkeley Data Analytics Stack, one of the world’s most popular big data stack at that time. He developed the fastest similarity-join algorithm, which has become an essential operator in data preparation systems. Since joining SFU, Dr. Wang has illustrated his remarkable independence in initiating and executing an ambitious research agenda to speed up data science. He was awarded a large MITACS Accelerate grant of $990K as the sole PI to support this research program, and developed several open-source tools (e.g., DataPrep, Deeper, AQP++), which have already been deployed at several companies or used by tens of thousands of users. He is serving as the Program Director of the Professional Master’s Program in Big Data, Visual Computing, and Cybersecurity at SFU. He helped to design two popular Big Data lab courses for the program and has trained over 300 Big Data master’s students in the past five years. Many of the students are now working as data scientists or data engineers in Canada, helping to close Canada’s Big Data talent gap.