학과소개

교수소개
 학과소개 교수소개
이름 황상흠
전공 기계학습, 데이터마이닝
 
TEL 02-970-6462
E-mail shwang@seoultech.ac.kr
연구실 프론티어관 915호
 
교수소개 돌아가기

학력

◾ KAIST 산업 및 시스템공학과 박사, 2006.03 - 2012.04
◾ KAIST 산업공학과 학사, 2001.03 - 2005.07

주요 경력

◾ Lunit Inc. Research Lead, 2017.03 - 2018.02
◾ Lunit Inc. Senior Researcher, 2015.01 - 2017.02
◾ 삼성전자 종합기술원 전문연구원, 2012.05 - 2014.12

연구 분야

◾ Deep learning and its applications
◾ Artificial intelligence
◾ Medical image analysis
◾ Machine learning

담당 교과목

◾ (학부) 산업정보시스템전공: 파이썬프로그래밍, 딥러닝
◾ (학부) ITM전공: Artificial Intelligence
◾ (대학원) 데이터사이언스: 데이터분석을 위한 수학, 인공신경망과 딥러닝

저널 논문

◾ M. Veta, [et al. including S. Hwang] (2019), "Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge," Medical Image Analysis, 290(1), 218-228.
◾ J. G. Nam, S. Park, [et al. including S. Hwang] (2019), "Development and validation of deep Learning-based automatic detection algorithm for malignant pulmonary nodules on chest radiographs," Radiology, 290(1), 218-228.
◾ S. Hwang, and D. Kim (2018), "A scalable feature based clustering algorithm for sequences with many distinct items," International Journal of Fuzzy Logic and Intelligent Systems, 18(4), 316-325.
◾ S. Hwang, and M. K. Jeong (2018), "Robust relevance vector machine for classi cation with variational inference," Annals of Operations Research, 263(1-2), 21-43.
◾ S. Hwang, J. Yoo, C. Lee, and S. H. Lee (2016), "Collaborative crystal structure prediction," Expert Systems with Applications, 63, 222-230.
◾ Y.-S. Jeong, S. Hwang, and Y.-D. Ko (2015), "Quantitative analysis for plasma etch modeling using optical emission spectroscopy: prediction of plasma etch responses," Industrial Engineering and Management Systems, 14(4), 392-400.
◾ D. Kim, C. Lee, S. Hwang, and M. K. Jeong (2015), "A robust support vector regression with a linear-log concave loss function," Journal of Operational Research Society, 67(5), 735-742.
◾ S. Hwang, D. Kim, M. K. Jeong, and B.-J. Yum (2015), "Robust kernel based regression with bounded infuence for outliers," Journal of Operational Research Society, 66(8), 1385-1398.
◾ D. Mishra, [et al. including S. Hwang] (2015), "Effect of piezoelectricity on critical thickness for mis fit dislocation formation at InGaN/GaN interface," Computational Materials Science, 97, 254-262.
◾ S. Hwang, M. K. Jeong, and B.-J. Yum (2014), "Robust relevance vector machine with variational inference for improving virtual metrology accuracy," IEEE Transactions on Semiconductor Manufacturing, 27(1), 83-94.
◾ Y.-H. Cho, [et al. including S. Hwang] (2013), "Quantum efficiency affected by localized carrier distribution near the V-defect in GaN based quantum well," Applied Physics Letters, 103, 261101.
◾ S.-H. Park, [et al. including S. Hwang] (2013), "Partial strain relaxation effects on polarization anisotropy of semipolar (1122) InGaN/GaN quantum well structures," Applied Physics Letters, 103, 221108.

학술대회

◾ S. Hwang, and S. Park, "Accurate lung segmentation via network-wise training of convolutional networks," The 3rd International Workshop on Deep Learning in Medical Image Analysis in MICCAI 2017, Sep. 2017.
◾ K. Paeng, S. Hwang, S. Park, and M. Kim, "A uni ed framework for tumor proliferation score prediction in breast histopathology," The 3rd International Workshop on Deep Learning in Medical Image Analysis in MICCAI 2017, Sep. 2017.
◾ S. Hwang, and H.-E. Kim, "Self-transfer learning for weakly supervised lesion localization," The 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 239-246, Oct. 2016.
◾ S. Hwang, H.-E. Kim, J. Jeong, and H.-J. Kim, "A novel approach for tuberculosis screening based on deep convolutional neural networks," in Proceedings of SPIE Medical Imaging, 9785, Mar. 2016.
◾ S. Kim, [et al. including S. Hwang], \Deep convolutional neural network-based mitosis detection in invasive carcinoma of breast by smartphone-based histologic image acquisition," in Modern Pathology (USCAP Annual Meeting), 29, Mar. 2016.

연구프로젝트

◾ 도메인 일반화를 위한 제약 최적화 기반의 딥러닝 알고리즘 개발, 한국연구재단, 2018.11.~2019.10.
◾ LGCNS Deep Learning 기반 비전검사 알고리즘 고도화 자문, (주)엘지씨엔에스, 2018.06.~2018.10.
◾ 깊은 신경망 모형의 불균형 데이터 학습 양상에 대한 고찰, 산학협력단, 2018.04.~2019.03.

수상

◾ Inner Product based Deep Neural Networks, 2018 INFORMS International Conference Poster Competition, The Institute for Operations Research and the Management Sciences (INFORMS), 2018

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