1/10/2023 11:29:54 AM
When Illinois CS professor Hanghang Tong won ICDM’s award he thought back on his early work with the IBM T.J. Watson Research Center. He also thought of those project collaborators, who influenced his career choices and return to academia.
Ten years ago, when Illinois Computer Science professor Hanghang Tong collaboratively published a paper on bipartite graph alignment, he admitted there was no way he could have known the future implications of the work then.
In his first year out of academia, as a researcher with the IBM T.J. Watson Research Center, what Tong did know was that the three-month project proved the reason he chose an industry position. The paper’s significant outcome proved that his work in data mining could result in important real-world applications.
Tong collaborated with intern Danai Koutra and their manager, David Lubensky, to work on the ways graph alignment could address a couple important social media questions. First, how could systems find the “virtual twin” on separate social outlets, like LinkedIn and Facebook? And how could it effectively link an information network with a social network to support cross-network search?
The resulting paper – entitled “BIG-ALIGN: Fast Bipartite Graph Alignment” – introduced a “new optimization formulation and propose(d) an effective and fast algorithm to solve it.” Their results produced a method that was 10 times more accurate and 174 times faster than previous methods.
Published at the IEEE International Conference on Data Mining (ICDM), a top conference in the field, this work made enough of an impact to earn ICDM’s 10-year Highest Impact Paper Award in late November.
“I was chatting with Danai recently, and neither of us could believe that 10 years have passed now. It felt like it was just yesterday,” Tong said. “We knew at the time the paper was interesting amongst those in the field, but to be honored with the 10-year Highest Impact Paper Award now is very meaningful to us.
“I think of one thing maybe I can quote from the notification letter that struck me is that the basis of the award stems from the committee’s belief that your paper has had ‘the most substantial impact on the data mining community over the last decade.’”
Not only did this paper result in a significant technical result honored 10 years later, but it also set new career trajectories for both Tong and Koutra – the younger investigators on the project.
At that point in his career, Tong had a Ph.D. in Machine Learning from Carnegie Mellon University – where he had met Koutra, who was a Ph.D. student at that time.
While he believed his work in the field could be impactful in academia, Tong wanted to see how much it could find direct relevance to real-world applications through work directly tied to industry.
The paper they produced had an impact both in terms of e-commerce and the financial sector.
It was immediately valued highly at IBM, through a review board the company used to estimate a project’s IP value. In fact, the project received IBM’s highest rating, marking it for an extremely high potential business value.
The company review board recommended to file not one, but seven patents off the work.
“I benefitted from working alongside Danai – who I knew from CMU. We both really liked each other’s work. Then we thrived under David’s leadership. He challenged us to investigate the most meaningful questions, but he also provided a very nourishing environment that freed us up to find our own path forward,” Tong said.
“Thinking back, what I’m really proud of is the effect that this project had on the long-term success of both my career and Danai’s. She is now a professor at the University of Michigan, and continues to work with students on network alignment. And I have two recent Ph.D. graduates whose entire Ph.D. theses were on this topic of network alignment.”
Working for almost three years total in research with IBM, Tong believes his successful stint there also helped him find his way back into academia.
He has been on faculty at Illinois CS since 2019, but it was this project experience with Koutra that partly helped him realize how the energy of learning alongside students impacts his own work.
“It was a great experience for me at IBM, and it also taught me that I missed the university setting. I genuinely enjoy the collaborative environment with other researchers and students,” Tong said.