Victor Sheng’s work was recognized at the virtual 2020 Special Interest Group on Knowledge Discovery and Data Mining Conference.
In the world of sports, when a player stands out from his or her peers and achieves amazing feats, that person can be rewarded and recognized by being inducted into a hall of fame. For his work, Victor Sheng, an associate professor of computer science in the Edward E. Whitacre Jr. College of Engineering at Texas Tech University, has been inducted into the computer science world's version of a hall of fame.
Sheng received the Test-of-Time Award at the 2020 Association for Computing Machinery's (ACM) Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) Conference. The SIGKDD Test-of-Time Award recognizes outstanding papers from past KDD conferences beyond the last decade that have had an important impact on the data-mining research community.
"This is the biggest award in data science," Sheng said. "It means that, after being published, the paper has been citied many times and still has a high impact and a high value in the data science community."
The paper for which Sheng is being recognized is, "Got Another Label? Improving Data Quality and Data Mining Using Multiple, Noisy Labelers," which he wrote with Foster Provost and Panagiotis Ipeirotis while at New York University and presented at the 2008 KDD Conference. The paper was named the runner-up of the Best-of-the-Best Award from that conference.
"Our paper focused on solving the crowdsourcing problem," Sheng said. "Some companies and data science researchers have used the techniques we developed in our paper. Crowdsourcing can harness the human knowledge for solving real-world problems, especially difficult problems to computer."
Rattikorn Hewett, the Whitacre Chair and department chairwoman in computer science and a professor, expressed her excitement for Sheng.
"In the big data and machine-learning era, ACM SIGKDD is one of the top research communities in data science," Hewett said. "I couldn't be happier for Dr. Sheng to receive this highly prestigious award and for our department to have Dr. Sheng with us. This speaks volumes about Texas Tech's commitment to research and education excellence in data science."
Al Sacco Jr., dean of the College of Engineering, praised Sheng's accomplishment.
"Dr. Sheng is another one of our outstanding computer science faculty members and is well-deserving of the KDD Test-of-Time Award," he said. "We are all very proud of his achievement."
About the SIGKDD
SIGKDD's mission is to provide the premier forum for advancement, education and adoption
of the science of knowledge discovery and data mining from all types of data stored
in computers and networks of computers. SIGKDD promotes basic research and development
in KDD, adoption of standards in the market in terms of terminology, evaluation, methodology
and interdisciplinary education among KDD researchers, practitioners and users.
