Professor Jiawei Han Joins Select Group With Funai Achievement Award
The Funai Achievement Award is Japan’s highest honor for information science, and before 2018 only three non-Japanese researchers had ever won it.
Illinois Computer Science Professor Jiawei Han last month became the fourth, when he was announced as the 2018 winner.
The Information Processing Society of Japan awarded Han “for his pioneering work on Data Mining, Information Network Analysis, Database Systems, and Data Warehousing.”
Han, who is an Abel Bliss Professor in Engineering, described in understated fashion one of the primary reasons he was honored.
In the 1990s, “A lot of people in the U.S. and Japan were thinking about getting into data mining, and I was kind of an early bird.”
Illinois Computer Science Interim Department Head Vikram Adve noted that, Han’s modesty aside, the award was both a remarkable honor and well deserved.
“This is a highly prestigious award, and extraordinarily few outside Japan have received it,” Adve said. “Professor Han is the perfect choice for this award, because of his outstanding technical contributions in the field of data mining, his long-standing leadership of the community, and his mentoring of numerous leaders in the younger generation of data mining academics and researchers.”
The only other non-Japanese winners of the Funai Achievement Award are ACM Turing Award winners Alan Kay (2002) and Marvin Minsky (2003), as well as William J. Dally (2015), Nvidia Corporation’s chief scientist.
Professor Shojiro Nishio, the president of both Osaka University and the Information Processing Society of Japan, introduced Han at the society’s September conference with a long list of the Illinois CS professor’s accomplishments:
- A founder of the data mining research field, and author of a textbook on the subject which has been widely adopted internationally for two decades.
- One of the most cited authors in computer science (ranked top three among CS researchers, according to Google’s H Index).
- The inventor of a set of influential frequent-pattern mining algorithms.
- Creator of a subfield of mining heterogeneous information networks.
- Recognized with numerous awards, including ACM Fellow, IEEE Fellow, ACM SIGKDD Innovation Award, IEEE Computer Society Technical Achievement Award, and IEEE Computer Society W. Wallace McDowell Award.
- Advised a number of influential PhDs – 35 students have completed PhDs from Illinois CS under Han.
Han said that his “early bird” status in data mining grew out of his PhD work at the University of Wisconsin between 1979 and ’85.
“I was thinking, ‘In the future, the database must be integrated with artificial intelligence,’” Han said. “You have a huge amount of data. You want to make them into patterns and rules. If you really want to make good use of the data, you have to somehow make the data intelligent.”
His first paper on data mining, in 1989, actually predated the term and instead used the term KDD, knowledge discovery in databases.
Now Han leads the Data Mining Group at Illinois Computer Science.
Han also played a key role in creating the ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
The gathering now draws several thousand people a year, but started as a small workshop on the sidelines of the International Joint Conference on AI in 1989.
The first drew 20-30 people, but the interest quickly grew along with the fascination in data mining and what it might make possible. The first KDD conference was held in 1995, and Han co-chaired the second the next year.
“Now, everyone is talking about deep learning,” Han said. “Then, everyone was talking about data mining.”