This year’s coveted Tao Li Award has gone to Jundong Li, an associate professor of electrical and computer engineering and computer science at the University of Virginia. Li, feeling “genuinely grateful and a bit overwhelmed,” accepted the award on Nov. 14 at the IEEE International Conference on Data Mining in Washington, D.C.
“The ICDM Tao Li Award is deeply meaningful to me, and I have long admired the scholars who received it in prior years, all of whom are leaders in the data mining and machine learning community,” Li said, adding that he was both humbled and encouraged.
“Learning that I had been selected reminded me how much credit is due to my students and collaborators, whose hard work has shaped our research over the years.”
The Tao Li Award was established in 2017 to honor the life and accomplishments of Professor Tao Li, a pioneer in data mining and machine learning. It is given annually to one early-career researcher who has received a Ph.D. within the past 10 years and recognizes significant impact in research contributions, leadership and service to the data mining and machine learning community.
Li has a special interest in graph machine learning, a subset of machine learning techniques. His research zeroes in on developing data mining and machine learning models that can help us understand, characterize and extract actionable insights from structured data.
“Much of this structured data comes in the form of graphs, which capture relationships — such as social connections, biological interactions or links between pieces of information,” Li said.
His group is currently pursuing various directions: building “trustworthy” graph models, making them more robust and fair, and devising methods that will translate to new or shifting data environments.
They are also figuring out how to combine large language models with graph-based systems to better address complex real-world scenarios — like understanding how diseases spread through public health networks and making the technology that runs our physical world safer from hacking or malfunction.
Their research is supported by the National Science Foundation, the Department of Education, the Office of Naval Research, the Commonwealth Cyber Initiative, the U.S. Department of Energy’s Jefferson Lab, J.P. Morgan, Cisco, Netflix and Snap.
Before joining UVA in 2019, Li earned his Ph.D. in computer science at Arizona State University under the supervision of Regents professor Huan Liu.
He has published more than 150 papers, with over 18,000 citations, and has won several prestigious awards, including the 2024 SIGKDD Rising Star Award and the 2022 SIGKDD Best Research Paper Award from the Association for Computing Machinery’s Special Interest Group on Knowledge Discovery and Data Mining, the 2024 PAKDD Best Paper Award and 2023 PAKDD Early Career Research Award from the Pacific-Asia Conference on Knowledge Discovery and Data Mining; an NSF CAREER Award; the 2021 and 2022 J.P. Morgan Chase Faculty Research Award and the 2021 Cisco Faculty Research Award, among others.
“Receiving the KDD Rising Star Award last year and now the ICDM Tao Li Award is especially meaningful to me,” Li said. “These recognitions come from a community that has shaped my growth since my early days as a Ph.D. student, and they reflect both research contributions and service over the past five to 10 years.”
This year’s honor also infused a “renewed sense of motivation,” he added.
“Our work has always been driven by curiosity and a desire to address important problems, and knowing that these contributions resonate with the community is deeply encouraging.
“The Tao Li Award reminds me how fortunate I am to be part of such a vibrant research community, and it strengthens my commitment to continue contributing — through research, mentorship and service — to help advance the field in the years ahead.”