Professor Sangmin Lee's Research Team

(Department of Information Convergence) Receives the Awards at the Korean Data Mining Society Summer Conference

The research team of Professor Sangmin Lee (students Yujin Lee and Jaewon Lee) from the Department of Information Convergence in the School of Software Convergence, won the Best Paper Award and the Encouraging Paper Award at the '2023 Korean Data Mining Society (KDMS2023) SAS Student Paper Competition,' organized by the Korean Society for Information Science, held in the first half of the year 2023.

(From left) Yujin Lee and Jaewon Lee from Department of Artificial Intelligence Applications

At the academic conference, Yujin Lee presented on 'Semantic Segmentation and Interpretation Methods Applicable to Pathology Images' and received the award for proposing a methodology that improves the performance of accurately detecting malignant tumors in pathology images, along with providing interpretation functions for the results.

Moreover, Jaewon Lee proposed a graph neural network-based anomaly detection model for establishing a tail-biting traffic congestion monitoring system for autonomous vehicle systems within semiconductor factories. He received the award for his model's performance improvement compared to existing anomaly detection techniques and its capability to analyze and interpret factors related to congestion timing and areas.

Meanwhile, the conference, held under the theme 'The Role of Data Mining in the Era of Chat GPT AI,' featured various papers covering topics such as healthcare, anomaly detection, and reinforcement learning.