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AI Services Research Lab Wins Best Paper Award and Grand Prize at the ‘2024 KDMS Autumn Conference’

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  • 2025-01-10
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·         [Kwangwoon Hot Issue] AI Services Research Lab Wins Best Paper Award and Grand Prize at the 2024 KDMS Autumn Conference

226 Views | Created 2024.12.18 | Modified 2024.12.18 | Public Relations Team

·         The AI Services Research Lab (Professor Lee Sang-min, School of Information Convergence)

Wins Best Paper Award and Grand Prize at the ‘2024 KDMS Autumn Conference’

 

 

 
Professor Lee Sang-min (School of Information Convergence) and his research team from the AI Services Research Lab, including master's students Baek Seung-jun and Jang Yoo-na, received the Best Paper Award and the Grand Prize respectively at the “2024 KDMS (Korean Data Mining Society) Autumn Conference,” held in Gyeongju from November 22 (Friday) to 23 (Saturday), 2024.
 

 

 

Professor Lee Sang-min (School of Information Convergence) and his research team from the AI Services Research Lab, including master's students Baek Seung-jun and Jang Yoo-na, received the Best Paper Award and the Grand Prize respectively at the “2024 KDMS (Korean Data Mining Society) Autumn Conference,” held in Gyeongju from November 22 (Friday) to 23 (Saturday), 2024.

 

Student Baek Seung-jun presented a forecasting method that incorporates spatiotemporal patterns varying over time to improve the accuracy of online sales demand predictions. He received the Best Paper Award for proposing a robust learning model that performs well despite data distribution shifts and introducing a method to dynamically adjust past data for predicting future data.

 

 

Student Baek Seung-jun presented a forecasting method that incorporates spatiotemporal patterns varying over time to improve the accuracy of online sales demand predictions
 

 

 

 

Student Jang Yoo-na presented the S3D-NAS technique, a neural architecture search method for semantic segmentation of medical images. She was honored with the Grand Prize for proposing a neural architecture search method that applies self-distillation techniques and Dirichlet distribution to construct a network architecture that is over 30% more sparse than existing models while maintaining comparable high performance.

 

Held under the theme "The Era of Collaborative Innovation: Embracing the Future with Data Mining and Artificial Intelligence," this conference featured over 130 poster presentations and 30 seminars covering a wide range of topics, including natural language processing, time series analysis, machine learning, industrial AI, and image/video data mining.

 

Professor Lee Sang-min, who supervised the students, remarked, “Students from our university’s Department of AI Applications actively participated in this conference, submitting around 20 papers. I am proud to see that these awards not only enhance the students’ sense of achievement but also raise the prestige of our department. I will continue to make every effort to support our students in pursuing ongoing research and challenges.”

 

https://www.kw.ac.kr/ko/life/newsletter.jsp?BoardMode=view&DUID=48730&tpage=1?