SFU computing scientist Jian Pei recognized as an ACM Fellow
By Allen Tung
The award, from the Association for Computing Machinery (ACM), acknowledges his contributions to the foundation, methodology and applications of data mining.
Pei, a Tier 1 Canada Research Chair in Big Data Science, has developed fundamental algorithms in big data that have been patented, adapted by industry, and used in textbooks.
One area he works on is algorithms for frequent-pattern data mining, which can provide invaluable information to retail marketers for designing sales promotions, and has applications for many other industries as well.
“Just imagine yourself as a retail manager at store, who wants to know what combinations of products customers frequently buy together,” says Pei.
“There are millions of transactions and hundreds of millions of products sold each day so finding that out isn’t very easy. Frequent-pattern mining makes sense of this data.”
Finding out what products customers often buy together can help retailers strategically place items, which may seem unrelated, together in the store to help drive sales. It also gives them insights into which smaller items they can promote to leverage the sales of larger, bigger ticket items.
Pei is also leading a big data research project to improve healthcare delivery, decision-making and outcomes. The project—the Pacific Blue Cross Health Informatics Lab—is a partnership between SFU and Pacific Blue Cross.
This June, ACM will formally recognize Pei and 41 other new fellows at an annual awards banquet in San Francisco. The award is the society’s most prestigious member award. It recognizes the top one per cent of ACM members for their outstanding accomplishments in computing and information technology, and/or outstanding service to ACM and the larger computing community.
“It’s a recognition from the community,” says Pei. “You can’t win this award without having made a significant contribution to the world in computing.”