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    [세미나] [GSDS Colloquium] Nov. 26th 16:00 / Room 1122 E2-2 / Prof. MunYong Yi & HyunJung Kim / Medical Image Analysis & Scheduling of Manufacturing Systems with AI
    • 관리자
    • 2024.11.19
    • 44

    GSDS 콜로퀴움이 다음과 같이 진행될 예정입니다.
     

    날짜/시간: 2024년 11월26일 화요일 16:00~17:00

    장소: E2 1122호

    연사:  Prof. MunYong Yi & HyunJung Kim 

    # 제목: Medical Image Analysis & Scheduling of Manufacturing Systems with AI

    - Zoom 링크:  https://kaist.zoom.us/j/82591870965  ID:  825 9187 0965

    Abstract of Medical Image Analysis

    암은 전세계적으로 가장 심각한 사망원인의 하나이며, 많은 경우 조직검사를 통해 채취한 검체를 통해 생성된 이미지에서 정확한 병리적인 특성을 찾아내는 것이 암 진단의 결정적인 역할을 한다. 최근 인공지능 기술의 발전은 그동안 병리사와 병리전문의에게 맡겨진 이러한 암 진단의 부담을 경감시킬 수 있는 가능성을 제공한다. 이 세미나에서는 국내외 의료 이미지 분석 시장의 현황 및 그동안 산학협동 연구로 진행된 효과적인 암 진단을 위한 인공지능 기반의 병리 이미지 분석 연구를 소개한다.

     

    Abstract of Scheduling of Manufacturing Systems with AI 

    This talk will present real-life industrial scheduling problems faced by industries such as semiconductors, steels, and tires with a specific focus on the application of AI. Manufacturing companies have recently shown a growing interest in using AI due to its promising results reported in papers, and they are eager to apply it in scheduling problems. In this talk, I will introduce real projects conducted with manufacturing companies, discuss the challenges of implementing AI or other heuristic algorithms in practical settings, and examine the advantages and limitations of using AI in comparison to optimization or meta-heuristic methods.

    Bio of HyunJung Kim

    Dr. Hyun-Jung Kim is an Associate Professor in the Department of Industrial & Systems Engineering at KAIST, Korea. Before joining KAIST in September 2019, she was an Assistant Professor in the Department of Systems Management Engineering at Sungkyunkwan University from 2015 to 2019. She earned her PhD from the Department of Industrial & Systems Engineering at KAIST in 2013. Her research focuses on the scheduling of manufacturing systems, modeling and analysis of discrete event systems, and smart and green manufacturing. Dr. Kim has received 'Best Semiconductor Manufacturing Automation Paper in Theory' from the IEEE Robotics and Automation Society's Technical Committee of Semiconductor Manufacturing Automation and an Honorable Mention for the IEEE Transactions on Semiconductor Manufacturing Best Paper Award. Additionally, she serves as an Associate Editor for the IEEE Transactions on Automation Science and Engineering and International Journal of Production Research.