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이슬

전공 : 소프트웨어학과

학위 : 박사

이메일 : sael@ajou.ac.kr

연구실 : 산학협력원

연구실번호 : 3839

연구실관심분야 : Machine Learning for Healthcare, Tensor Analysis, and Bioinformatics (연구실 산학원 602호)

홈페이지 : https://leesael.github.io

Education
  • 2010.08 Purdue Univ-West Lafayette 박사
Working experience
  • [2019 ~ ] 아주대학교 소프트웨어학과/인공지능학과 부교수
  • [2012 - 2018] 한국뉴욕주립대 (Stonybrook University) 컴퓨터학과 조교수
  • [2011 - 2012] 삼성종합기술원 Future IT Research Center 전문연구원
  • [2010 - 2011] Purdue University, 박사후연구원
Research activity (Selected papers)
  • 연구활동(주요논문)
  • [논문] 정진홍, 이슬, Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach , MACHINE LEARNING , Vol.12 , pp.2333 -2347 (Oct, 2020)
  • 국제학술논문지
  • [논문] Haeun Lee, 이슬, Chirag R Kharangate, Chris Malone, Kenneth E Goodson, Ki Wook Jung, Madhusudan Iyengar, Mehdi Asheghi, Minsoo Kang, Hyoungsoon Lee, An artificial neural network model for predicting frictional pressure drop in micro-pin fin heat sink , APPLIED THERMAL ENGINEERING , pp.117012 -117012 (Jul, 2021)
  • [논문] Hyun Kyu Shin, 이슬, 이시운, Goo Pyo Hong, Sang Hyo Lee, Ha Young Kim, Defect-Detection Model for Underground Parking Lots Using Image Object-Detection Method , CMC-COMPUTERS MATERIALS & CONTINUA , Vol.3 , pp.2493 -2507 (Dec, 2020)
  • [논문] 이기수, 이슬, 홍구표, 김하영, 이상효, MultiDefectNet: Multi-Class Defect Detection of Building Façade Based on Deep Convolutional Neural Network , SUSTAINABILITY , Vol.22 , pp.1 -14 (Nov, 2020)
  • [논문] 정진홍, 이슬, Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach , MACHINE LEARNING , Vol.12 , pp.2333 -2347 (Oct, 2020)
  • [논문] 오정훈, 최윤진, 이슬, 강성주, 김원지, 김주성, 박용택, 신철민, 안현주, 원성호, 이동호, 이선민, 이세정, 이혜승, 장동남, 한병우, 김나영, Family-based exome sequencing combined with linkage analyses identifies raresusceptibility variants of MUC4 for gastriccancer , PLoS ONE , Vol.7 , pp.1 -17 (Jul, 2020)
  • 국제학술발표
  • [학술회의] 유재민, 이슬, Gaussian Soft Decision Trees for Interpretable Feature-Based Classification , The 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining - PAKDD 2021 (May, 2021)
  • [학술회의] Jun-Gi Jang, Moonjeong Park, 이슬, VeST: Very sparse tucker factorization of large-scale tensors , 2021 IEEE International Conference on Big Data and Smart Computing (BigComp) (Jan, 2021)
  • [학술회의] 유재민, 이슬, EDiT: Interpreting Ensemble Models via Compact Soft Decision Trees , IEEE International Conference on Data Mining (ICDM) (Dec, 2019)
Patent and others
  • 1.[특허] 이슬, 손희수, 이상석, 피로도 예측 모델 학습 장치 및 방법 (출원) (10-2020-0136325) (Oct, 2020)
  • 2.[특허] 이슬, 건물 하자 이미지 생성 장치 및 방법 (출원) (10-2020-0126631) (Sep, 2020)
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