Tong's Elevation to IEEE Fellow Connected to Overarching Research Philosophy

12/7/2021 10:56:02 AM Aaron Seidlitz, Illinois CS

For nearly 10 years, Illinois CS professor Hanghang Tong has learned from others to keep his data mining research rooted in a simple notion about asking the right questions to produce worthwhile results.

Written by Aaron Seidlitz, Illinois CS

Quick to point to others before himself – primarily, influences in his own career that have spurred his interest and effectiveness in research focused on large scale data mining and machine learning – Illinois CS professor Hanghang Tong couldn’t help but feel honored when he was recently elevated to Fellow within the Institute of Electrical and Electronics Engineers (IEEE).

Hanghang Tong
Hanghang Tong

Acknowledging that an IEEE Fellow represents a “distinction reserved for select IEEE members whose extraordinary accomplishments in any of the IEEE fields of interest are deemed fitting of this prestigious grade elevation,” as the IEEE website states, Tong said this moment represents a “major milestone in my career.”

“It’s always amazing when you learn of receiving a great recognition and becoming an IEEE Fellow is definitely a great honor. However, this is also representative of all the people who I’ve worked with over the years,” Tong said. “This goes back to the work I did during my PhD studies, which was a long time ago now. It also is indicative of the high level of students I am privileged to work with here at Illinois CS.”

This kind of recognition doesn’t occur by chance, though.

Tong credits lessons he learned early in his academic journey for providing the correct guide to his career ambitions. While earning his PhD at Carnegie Mellon University, Tong said it was his PhD adviser, Christos Faloutsos, who provided the inspiration that has fueled his nearly 10-year academic career thus far.

Tong’s philosophy to produce great research revolves around asking the difficult questions to find research results that produce the most meaning.

One example of this philosophy forming a great result is his 2006 paper entitled “Fast Random Walk with Restart and Its Application.”

Tong’s idea came from his PhD studies and represented a model designed to “measure the proximity between different users on social networks.” In the abstract, Tong wrote: “Random walk with restart (RWR) provides a good relevance score between two nodes in a weighted graph, and it has been successfully used in numerous settings, like automatic captioning of images, generalizations to the ‘connection subgraphs,’ personalized PageRank, and many more.”

By asking the right question, and finding solutions for it, Tong encountered a research topic with lasting impact. It earned a Best Research Paper Award at that year's IEEE International Conference on Data Mining (ICDM).

“Ten years later we also received the 10-Year Highest-Impact Paper Award from ICDM on the same topic,” Tong said. “I actually emphasized the path that project took recently to students in Robin Kravets’ CS591 course. I explained to the students that research success, while seemingly complicated, does come to a simple notion: pick interesting problems that really excite you. As you work on that topic and find solutions to those problems, you will likely come upon something that has lasting value.”

Tong’s methodology has now proven itself time and again.

Not only did that 2006 paper gain recognition on two different instances, but Tong has won prizes for 12 other papers. Additionally, Tong earned:

  • A Distinguished Member position with the Association for Computing Machinery (ACM) last year
  • The IEEE ICDM Tao Li Award in 2019
  • The SDM/IBM Early Career Data Mining Research Award in 2018
  • And a National Science Foundation (NSF) CAREER Award in 2017

At this point in his career, Tong finds the recognitions worthwhile, but values more the relationships these successes honor.

He believes being at Illinois CS since 2019 puts him in the best position to succeed as a researcher, because of the influences and collaborators around him. One of the people he looks up to the most in computing, a person whose writings on data mining inspired him to join the field, is fellow Illinois CS professor Jiawei Han.

Together with co-author Jian Pei, this group is now completing a fourth edition to Han’s textbook, entitled “Data Mining: Concepts and Techniques.” Tong said he read this book in Chinese as a student before he even came to the US.

“This means so much to me and is actually a little surreal, because I became co-author of a book that drew me into this field in the first place,” Tong said.

Tong also maintains relationships with other influences, with former colleagues at Arizona State or from his experience with IBM as a research staff member.

In fact, those same connections informed Tong he earned elevation to IEEE Fellow.

“This actually turned out to be one of my biggest surprises, because I was in the parking lot waiting to pick up my daughter from ballet rehearsal,” Tong said. “I turned to my phone for social media while I waited, and I saw all of these texts from colleagues and friends congratulating me. It was an amazing moment.”

Share this story

This story was published December 7, 2021.