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Yoon-Yeong Kim

Ph.D. Candidate

Applied Artificial Intelligence Laboratory

Department of Industrial and Systems Engineering

KAIST, Daejeon, Republic of Korea

Contact: yoonyeong.kim [at] kaist.ac.kr / yoonduck0292 [at] gmail.com

 

 

RESEARCH INTEREST

  • Machine Learning
  • Active Learning
  • Data Augmentation
  • Computer Vision
  • Target Tracking

 

 

EDUCATION

Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea (Sep. 2018 ~ )

  • Course of Doctor's Degree  in Industrial and Systems Engineering
  • Advisor: Prof. Il-Chul Moon

 

Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea (Sep. 2016 ~ Aug. 2018)

  • Course of Master's Degree in Industrial and Systems Engineering
  • Advisor: Prof. Il-Chul Moon
  • Thesis: Black-Box Expectation-Maximization Algorithm for Estimating Latent States of High-Speed Vehicles
             (블랙박스 기댓값-최대화 알고리즘을 통한 초고속 비행체의 정밀 궤적 추정)

 

Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea (Feb. 2012 ~ Aug. 2016)

  • Bachelor of Mathematical Science
  • Bachelor of lndustrial and Systems Engineering (Minor)

 

 

PUBLICATION

International Journal

  • Yoon-Yeong Kim, Hyemi Kim, Wonsung Lee, Han-Lim Choi, and Il-Chul Moon, "Black-Box Expectation-Maximization Algorithm for Estimating Latent States of High-Speed Vehicles", Journal of Aerospace Information Systems, 18.4: 175-1921-5, 2021. [impact factor: 2.02]

 

Domestic Journal

  • 김윤영, 김혜미, 문일철, "초고속 비행체의 발사원점 추정을 위한 다중 IMM 필터 실험", 한국군사과학기술학회지, 제 23권 제 1호, pp. 18-17, 2020.

 

International Conference

  • Yoon-Yeong Kim, Kyungwoo Song, JoonHo Jang, and Il-Chul Moon, "LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning", Neural Information Processing Systems (NeurIPS), 2021. [acceptance rate: 26%]
  • Byeonghu Na, Hyemi Kim, Kyungwoo Song, Weonyoung Joo, Yoon-Yeong Kim, and Il-Chul Moon, "Deep Generative Positive-Unlabeled Learning under Selection Bias", ACM International Conference on Information and Knowledge Management (CIKM), 2020. [acceptance rate: 21%]
  • Mingi Ji, Weonyoung Joo, Kyungwoo Song, Yoon-Yeong Kim, and Il-Chul Moon, "Sequential Recommendation with Relation-Aware Kernelized Self-Attention", AAAI Conference on Artificial Intelligence (AAAI), 2020. [acceptance rate: 20.6%]
  • Yoon-Yeong Kim, Wonsung Lee, and Il-Chul Moon, "Black-Box Expectation-Maximization Algorithm for Estimating Latent States of High-Speed Vehicles", International Conference on Control, Automation and Systems (ICCAS), 2018.

 

Domestic Conference

  • 김윤영, 김혜미, 문일철, "RNN-LSTM을 활용한 초고속 비행체의 궤적 추적'', 한국군사과학기술학회 종합학술대회, 2019.
  • 김윤영, 김혜미, 문일철, "다중 표적 추적을 위한 GMPHD와 IMM 성능 비교'', 한국군사과학기술학회 종합학술대회, 2019.
  • 문일철, 김윤영, 김혜미, "표적 추적 및 특성 탐지를 위한 필터구조 연구'', 한국군사과학기술학회 종합학술대회, 2019.
  • 김윤영, 문일철, "초고속 비행체의 정밀 궤적 추정을 위한 Kalman Smoothing 적용'', 한국항공우주학회 춘계학술대회, 2018.
  • 김윤영, 박준건, 김상현, 문일철, "초고속 비행체의 발사 원점 추정을 위한 다중 IMM 필터 실험'', 한국항공우주학회 춘계학술대회, 2018.
  • 신수진, 박준건, 김윤영, 장준호, 문일철, "Faster R-CNN을 이용한 위성 이미지에서의 교통 수단 객체 탐지'', 한국군사과학기술학회 추계학술대회, 2017.
  • 신수진, 박준건, 김윤영, 장준호, 문일철, "Faster R-CNN의 중심 Convolution Neural Network 모델이 훈련 및 추론에 미치는 영향에 대한 분석", 대한산업공학회 추계학술대회, 2017. 

 

 

LAB

Yoon-Yeong Kim is a member of Applied Artificial Intelligence Laboratory. (2016 ~)