AI 원천기술연구 | 서울대학교AI연구원(AIIS)

연구

AI 원천기술연구

서울대학교 AI연구원은 AI의 난제를 해결할 수 있는 세계 최고 수준의 AI 원천기술 인력을
대규모로 보유하고 있는 국내 최대의 AI 연구기관입니다.

데이터 지능 (Data Intelligence)

인공지능을 활용해 빅데이터를 효율적으로 확장하고 활용하는 기술을 연구합니다.
데이터 기반 인공지능을 응용한 딥러닝, 추천 시스템, 대용량 언어처리 등을 연구하고 있습니다.

김용대자연과학대학 통계학과

  • 연구실/전공분야지능형자료분석 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Law & Ethics, Data Intelligence
  • 연구분야(X+AI)Commerce, Manufacturing, Finance

대표논문

Ohn, Ilsang, and Yongdai Kim. "Nonconvex sparse regularization for deep neural networks and its optimality." Neural Computation, 2022
Kim, Dongha, and Yongdai Kim. "Understanding Effects of Architecture Design to Invariance and Complexity in Deep Neural Networks." IEEE Access, 2021.
Kim, Yongdai, Ilsang Ohn, and Dongha Kim. "Fast convergence rates of deep neural networks for classification." Neural Networks,  2021.
Kim, Minjin, Young-geun Kim, Dongha Kim, Yongdai Kim & Myunghee Cho Paik. "Kernel-convoluted Deep Neural Networks with Data Augmentation." Association for the Advancement of Artificial Intelligence (AAAI), 2021.
Kim, Dongha, Jaesung Hwang, and Yongdai Kim. "On casting importance weighted autoencoder to an EM algorithm to learn deep generative models." International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
Ohn, Ilsang, and Yongdai Kim. "Smooth function approximation by deep neural networks with general activation functions." Entropy , 2019.
정책 변화를 유연하게 반영하여 준수하는 인공지능 기술 개발, 정보통신기획평가원, 2022.04.01. ~ 2026.12.31.
인공지능 모델과 학습데이터의 편향성 분석-탐지-완화·제거 지원 프레임워크 개발, 정보통신기획평가원, 2021.01.01. ~ 2022.12.31.
기계학습을 위한 성긴 방법론에 대한 연구, 한국연구재단, 2020.03.01. ~ 2025.02.28.

장원철자연과학대학 통계학과

  • 연구실/전공분야고차원대용량분석
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)

대표논문

장정주경영대학 경영학과

  • 연구실/전공분야경영정보
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)

대표논문

문병로공과대학 컴퓨터공학부

  • 연구실/전공분야최적화 및 금융공학 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence, Optimization Algorithms
  • 연구분야(X+AI)Finance, Logistics, Manufacturing

대표논문

쉽게 배우는 알고리즘, 2018, 한빛미디어
Sungjoo Ha, Sangyeop Lee, Byung-Ro Moon, "Investigation of the Latent Space of Stock Market Patterns with Genetic Programming,"  Genetic and Evolutionary Computation Conference, pp. 1254-1261, 2018
Seung-Hyun Moon, Yong-Hyuk Kim, Yong Hee Lee, Byung-Ro Moon, "Application of machine learning to an early warning system for very short-term heavy rainfall," Journal of Hydrology, 2019
Seung-Hyun Oh, Byung-Ro Moon, "Automatic Reproduction of a Genius Algorithm: Strassen's Algorithm Revisited by Genetic Search," IEEE Transactions on Evolutionary Computation, 14, 2, pp. 246-251, 2010
Il-Seok Oh, Jin-Seon Lee, Byung Ro Moon, "Hybrid Genetic Algorithms for Feature Selection," IEEE Transactions on Pattern Analysis and Machine Intelligence, 26, 11, pp. 1424-1437, 2004
게임로그 기반 최적화 매칭 알고리즘 도출, 넷마블, 2018.12~2019.7
팽이버섯 생산 최적화 및 자문, 대흥농산, 2019.3~2019.8
LMS 고반응 요건 선별 및 자문, 현대카드, 2016.7~2017.4

정연석약학대학 제약학과

  • 연구실/전공분야면역학
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)Bio, Pharma

대표논문

Atherogenic dyslipidemia promotes autoimmune follicular helper T cell responses via IL-27.
Nat Immunol. 2018 Jun;19(6):583-593. doi: 10.1038/s41590-018-0102-6
IL-27 confers a protumorigenic activity of regulatory T cells via CD39.
Proc Natl Acad Sci U S A. 2019 Feb 19;116(8):3106-3111.
Fibrinogen cleavage products and Toll-like receptor 4 promote the generation of programmed cell death 1 ligand 2-positive dendritic cells in allergic asthma.
J Allergy Clin Immunol. 2018 Aug;142(2):530-541
Proatherogenic conditions promote autoimmune T helper 17 cell responses in vivo.
Immunity. 2014 Jan 16;40(1):153-65
Follicular regulatory T cells expressing Foxp3 and Bcl-6 suppress germinal center reactions.
Nat Med. 2011 Jul 24;17(8):983-8.

이상학데이터사이언스대학원

  • 연구실/전공분야Causality Lab
  • 연구분야(AI 원천기술)Learning & Reasonin, Data Intelligence
  • 연구분야(X+AI)Humanities/Social Sciences, Medicine

대표논문

Nested Counterfactual Identification from Arbitrary Surrogate Experiments. Juan Correa, Sanghack Lee, Elias Bareinboim. NeurIPS-21. In Proceedings of the 35th Annual Conference on Neural Information Processing Systems,

Causal Identification with Matrix Equations. Sanghack Lee, Elias Bareinboim. NeurIPS-21. In Proceedings of the 35th Annual Conference on Neural Information Processing Systems

Characterizing Optimal Mixed Policies: Where to Intervene, What to Observe. Sanghack Lee, Elias Bareinboim. NeurIPS-20. In Proceedings of the 34th Annual Conference on Neural Information Processing Systems.

General Identifiability with Arbitrary Surrogate Experiments. Sanghack Lee, Juan Correa, Elias Bareinboim. UAI-19. In Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence, 2019.

인과성에 기반한 기계학습 모델 및 알고리즘 개발. 과학기술정보통신부/우수신진연구 2023.04.01 ~ 2028.03.31

박주연생활과학대학 의류학과

  • 연구실/전공분야웨어러블인간공학
  • 연구분야(AI 원천기술)Vision & Perception, Human-AI Interaction, Data Intelligence
  • 연구분야(X+AI)Medicine, Commerce, Manufacturing

대표논문

Park, J. (2018). The effect of virtual body checking on self-image discrepancy, body dissatisfaction and weight regulation intention. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 12(1), Advanced Online Publication
Park, J. (2017). Emotional reactions to the 3D virtual body and future willingness: The effects of self-esteem and social physique anxiety. Virtual Reality, 22(1), 1-11.
Park, J., Ogle, J. P., & Shaver, J. (2019). Virtual avatar experience for the intervention of body image concerns.  Proceedings of the Seventy-sixth Annual Conference of the International Textile and Apparel Association, International Textile and Apparel Association. Retrieved from http://lib.dr.iastate.edu/itaa_proceedings/2019/
Park, J, & Langseth-Schmidt, K. (2016). Anthropometric fit evaluation of firefighters’ uniform pants: A sex comparison. International Journal of Industrial Ergonomics, 56, 1-8.
Conroy, B., & Park, J. (2018). Body armor fit and comfort using 3D body scanning: A collaborative industry project. Proceedings of the Seventy-fifth Annual Conference of the International Textile and Apparel Association, International Textile and Apparel Association. Retrieved from http://lib.dr.iastate.edu/itaa_proceedings/2018/
2D 촬영 정보로 인체 체형 분류 및 검증, 중소기업기술정보진흥원, 2019-06-26 ~ 2021-08-25
인간중심 소프트로봇기술 연구센터, 선도연구센터 (기초연구사업),  2020-01-01 ~ 2022-12-31

장우진공과대학 산업공학과

  • 연구실/전공분야금융리스크 공학 연구실
  • 연구분야(AI 원천기술)Data Intelligence, FinTech Application
  • 연구분야(X+AI)Humanities/Social Sciences, Finance, Manufacturing

대표논문

김정훈의과대학 이비인후과학교실

  • 연구실/전공분야이비인후과학
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)Medicine

대표논문

특허: 수면무호흡증 예측 모델의 생성방법 및 이 모델을 이용한 수면무호흡증 예측방법
Prediction of Apnea-Hypopnea Index Using Sound Data Collected by a Noncontact Device.

Kim JW, Kim T, Shin J, Lee K, Choi S, Cho SW.

Otolaryngol Head Neck Surg. 2020 Mar;162(3):392-399. doi: 10.1177/0194599819900014. Epub 2020 Feb 4.

PMID: 32013710
Patient-Level Prediction of Cardio-Cerebrovascular Events in Hypertension Using Nationwide Claims Data.

Park J, Kim JW, Ryu B, Heo E, Jung SY, Yoo S.

J Med Internet Res. 2019 Feb 15;21(2):e11757. doi: 10.2196/11757.

PMID: 30767907
Impact of Personal Health Records and Wearables on Health Outcomes and Patient Response: Three-Arm Randomized Controlled Trial.

Kim JW, Ryu B, Cho S, Heo E, Kim Y, Lee J, Jung SY, Yoo S.

JMIR Mhealth Uhealth. 2019 Jan 4;7(1):e12070. doi: 10.2196/12070.

PMID: 30609978 Free PMC Article
Prediction of Obstructive Sleep Apnea Based on Respiratory Sounds Recorded Between Sleep Onset and Sleep Offset.

Kim JW, Kim T, Shin J, Choe G, Lim HJ, Rhee CS, Lee K, Cho SW.

Clin Exp Otorhinolaryngol. 2019 Feb;12(1):72-78. doi: 10.21053/ceo.2018.00388. Epub 2018 Sep 8.

PMID: 30189718 Free PMC Article
한국연구재단: 수면질환환자의 수면중 신호 빅데이터 분석을 활용한 개인 수면건강 관리용 웨어러블 기기 개발
산업부: 라이프로그-공공데이터를 활용한 PHR 기반 생애 주기별 맞춤형 건강관리 시스템 개발 및 비즈니스 모델 실증

이권상자연과학대학 통계학과

  • 연구실/전공분야인과추론연구실 (Causal Inference Lab.)
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence
  • 연구분야(X+AI)Humanities/Social Sciences, Medicine

대표논문

Fogarty, C. B., Lee, K., Kelz, R. R., and Keele, L. (2021) Biased encouragements and heterogeneous effects in an instrumental variable study of emergency general surgical outcomes. Journal of the American Statistical Association.

Lee, K., Small, D. S., and Dominici, F. (2021) Discovering heterogeneous exposure effects using randomization inference in air pollution studies. Journal of the American Statistical Association.

Lee, K., and Small, D. S. (2019). Estimating the malaria attributable fever fraction accounting for parasites being killed by fever and measurement error. Journal of the American Statistical Association.

Lee, K., Lorch S. A., and Small, D. S. (2019). Sensitivity analyses for average treatment effect when outcome is censored by death in instrumental variable models. Statistics in Medicine.

Lee, K., Small, D. S., and Rosenbaum, P. R. (2018). A powerful approach to the study of moderate effect modification in observational studies. Biometrics. (Statistics in Epidemiology (SIE) Young Investigator Award)

Lee, K., Small, D. S., Hsu, J. Y., Silver, J. H. and Rosenbaum, P. R. (2018). Discovering effect modification in an observational study of surgical mortality at hospitals with superior nursing. Journal of the Royal Statistical Society, Series A.

유병준경영대학 경영학과

  • 연구실/전공분야Electronic Commerce, Digital Economy, Business Analytics, IT Strategy, AI Applications
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence
  • 연구분야(X+AI)Finance, Commerce

대표논문

컨텐츠사용 형태 및 구매데이터 분석, 카카오페이, 2019
생체 건강나이 기반의 심뇌혈관질환 발생 위험 측정모델을 통한 노후필요 자금설계, NIA, 2018

박성호경영대학 경영학과

  • 연구실/전공분야계량마케팅
  • 연구분야(AI 원천기술)AI Platform, Data Intelligence
  • 연구분야(X+AI)Online Advertising, Digital Marketing, Retailing

대표논문

Christopher, Ranjit, Sungho Park, Sang Pil Han, Min Kyu Kim (2022), "Bypassing Performance Optimizers of Real Time Bidding Systems in Display Ad Valuation," Information Systems Research, 33(2), 399-412.

Lee, Mi Hyun, Su Jung Kim, Sang-Hyeak Yoon, Sungho Park (2022), "An Integrative Approach to Determinants of Pre-Roll Ad Acceptance and Their Relative Impact: Evidence from Big Data," Journal of Advertising, 51(1), 76-84.

Son, Yoonseock, Wonseok Oh, San-Pil Han, Sungho Park (2020), “When Loyalty Goes Mobile: Effects of Mobile Loyalty Apps on Purchase, Redemption, and Competition,” Information Systems Research, 31(3), 835-847.

Park, Sungho, Elliot Rabinovich, Christopher Tang, Rui Yin (2020), “The Impact of Disclosing Inventory Scarcity Messages on Sales in Online Retailing,” Journal of Operations Management, 66(5), 534-552.

Han, Sang-Pil, Sungho Park, Wonseok Oh (2016), “Mobile App Analytics: A Multiple Discrete-Continuous Choice Framework,” MIS Quarterly, 40(4).

Park, Sungho and Sachin Gupta (2012), “Handling Endogenous Regressors by Joint Estimation Using Copulas,” Marketing Science, 31(4), 567-586.

염헌영공과대학 컴퓨터공학부

  • 연구실/전공분야분산 시스템 연구실
  • 연구분야(AI 원천기술)AI Platform, Data Intelligence
  • 연구분야(X+AI)Logistics, Manufacturing

대표논문

허성욱법학전문대학원 법학과

  • 연구실/전공분야규제행정법/환경법/에너지법/법경제학/개인정보보호
  • 연구분야(AI 원천기술)AI Platform, Data Intelligence, AI Law & Ethics
  • 연구분야(X+AI)Arts, Humanities/Social Sciences, Energy

대표논문

한국에서 빅데이터를 둘러싼 법적 쟁점과 제도적 과제 경제규제와 법 서울대학교 법학연구소 단독  20141
스마트그리드와 개인정보보호 법정책 개인정보보호의 법과 정책 박영사 단독  201405
공법이론과 공공정책 (II) - 공공선택이론 관점에서 본 행정재판의 역할 - 공법연구 한국공법학회 단독  201812

박진수경영대학 경영학과

  • 연구실/전공분야Intelligent Data Semantics Lab
  • 연구분야(AI 원천기술)Language & Cognition, Human-AI Interaction, Data Intelligence
  • 연구분야(X+AI)Finance, Commerce, Manufacturing

대표논문

“Semantic Conflict Resolution Ontology (SCROL): An Ontology for Detecting and Resolving Data and Schema-Level Semantic Conflicts,” (with S. Ram), IEEE Transactions on Knowledge and Data Engineering, Vol. 16, No. 2. February 2004, pp. 189-202.
“A Novel Approach to Managing the Dynamic Nature of Semantic Relatedness,” (with Y. Choi, and J. Oh), Journal of Database Management, Vol. 27, No. 2, April-June 2016, pp. 1-26. (doi: 10.4018/JDM.2016040101)
“Predicting Movie Success with Machine Learning Techniques: Ways to Improve Accuracy,” (with K. Lee, I. Kim, and Y. Choi), Information Systems Frontiers, Vol. 20, Number 3, June 2018, pp. 577-588. (doi: 10.1007/s10796-016-9689-z) Online-first version on August 2016, pp. 1-12.
“Identifying Semantically Similar Questions in Social Q&A Communities,” (with B. Kim), in Proceedings of the 27th Workshop on Information Technologies and Systems (WITS 2017), Seoul, Korea, December 14-15, 2017.
“A Link-based Ranking Algorithm for Semantic Web Resources: A Class-oriented Approach Independent of Link Direction,” (with H. Park and S. Rho), Journal of Database Management, Vol. 22, No. 1, January-March 2011, pp. 1-25.

안용민의과대학 정신과학교실

  • 연구실/전공분야정신과학
  • 연구분야(AI 원천기술)Learning & Reasoning, Language & Cognition, Data Intelligence
  • 연구분야(X+AI)Bio, Brain, Medicine

대표논문

기계학습 기반의 음성 분석으로 자살 위험 예측

심병효공과대학 전기정보공학부

  • 연구실/전공분야정보시스템 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Platform, Data Intelligence
  • 연구분야(X+AI)Finance, Manufacturing, Wireless Communications

대표논문

W. Kim, Y. Ahn and B. Shim, "Deep Neural Network Based Active User Detection for Grant-free NOMA Systems," IEEE Transactions on Communications, 2020.
W. Kim, H. Ji, H. Lee, Y. Kim, J. Lee and B. Shim, "Sparse Vector Transmission: An Idea Whose Time Has Come," IEEE Vehicular Technology Magazine, 2020.
L. Nguyen, J. Kim and B. Shim, "Low-Rank Matrix Completion: A Contemporary Survey," IEEE Access, vol. 7, no. 1, pp. 94215-94237, Jul. 2019.
H. Ji, S. Park, J. Yeo, Y. Kim, J. Lee and B. Shim, "Ultra Reliable and Low Latency Communications in 5G Downlink: Physical Layer Aspects," IEEE Wireless Communications, vol. 25, no. 3, pp. 124-130 , June. 2018.
J. Choi, B. Shim, Y. Ding, B. Rao and D. Kim, "Compressed sensing for wireless communications: useful tips and tricks," IEEE Communications Surveys and Tutorials, vol. 19, no. 3, pp. 1527-1550, 2017.

김치헌의과대학 신경외과학교실

  • 연구실/전공분야신경외과학
  • 연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Data Intelligence
  • 연구분야(X+AI)Medicine, Manufacturing

대표논문

서종모공과대학 전기정보공학부

  • 연구실/전공분야전기-의학 융합연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Robotics & Action, Human-AI Interaction, Data Intelligence, AI Law & Ethics, Autonomous Driving
  • 연구분야(X+AI)Bio, Brain, Medicine

대표논문

김청택사회과학대학 심리학과

  • 연구실/전공분야계량심리학
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence
  • 연구분야(X+AI)Humanities/Social Sciences

대표논문

김청택 (2019). 빅데이터를 이용한 심리학 연구 방법. 한국심리학회지: 일반, 38(4), 519-548. DOI : 10.22257/kjp.2019.12.38.4.519
Noh, Y., Lee, D. D., Yang, K., Kim, C., & Zhang, B. (2015). Molecular Learning with DNA Kernel Machines, Biosystems, 137, 73-83.
Preacher, K. J., Zhang, G., Kim, C., & Mels, G. (2013). Choosing the optimal number of factors in exploratory factor analysis: A model selection perspective. Multivariate Behavioral Research, 48, 28-56.
Suh, Y. , Yu, J., Mo, J, Song, L, & Kim (2017).A Comparison of Oversampling Methods on Imbalanced Topic Classification of Korean News Articles, Journal of Cognitive Science, 18, 391-437.
김청택, 이태헌(2002). 뇌와 인지모형: 잠재의미분석을 사용한 문서분류. 한국심리학회지:실험 및 인지, 14(4), 309-320.

이성헌인문대학 불어불문학과

  • 연구실/전공분야불어학(통사의미론, 전산언어학)
  • 연구분야(AI 원천기술)Language & Cognition, Data Intelligence
  • 연구분야(X+AI)Humanities/Social Sciences

대표논문

HONG, Chai-song & LEE, Seong Heon, « Representation of Lexico-Syntactic Information for the Description of Predicate Nouns in the Sejong Electronic Dictionary », Korean and/or Corpus Linguistics, 경진문화사, 2003.
이성헌, 「전자사전 구축과 의미부류 - 세종 명사 의미부류 체계의 예」, 『한국사전학』, 한국사전학회, 2005.
이성헌, 임홍빈, 홍재성, 「다국어 연어 대조 연구를 위한 DB 구축과 의미부류의 활용- 한-불 대조를 중심으로」, 『프랑스어문교육』, 한국프랑스어문교육학회, 2009.
LEE, Seong Heon, Le dictionnaire

이용석의과대학 생리학교실

  • 연구실/전공분야신경생리 실험실
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)Medicine

대표논문

이상형의과대학 신경외과학교실

  • 연구실/전공분야뇌종양, 경동맥질환, 퇴행성뇌질환
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Platform, Human-AI Interaction, Data Intelligence
  • 연구분야(X+AI)Brain, Medicine, Pharma

대표논문

정현태의과대학 신경외과학교실

  • 연구실/전공분야실험핵물리학
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)Medicine

대표논문

이상구공과대학 컴퓨터공학부

  • 연구실/전공분야지능형 데이터 시스템 연구실
  • 연구분야(AI 원천기술)Language & Cognition, Data Intelligence
  • 연구분야(X+AI)Commerce

대표논문

Taeuk Kim, Jihun Choi, Daniel Edmiston, Sang-goo Lee, Are Pre-trained Language Models Aware of Phrases? Simple but Strong Baselines for Grammar Induction, International Conference on Learning Representations, 2020.
Jihun Choi, Taeuk Kim, Sang-goo Lee, A Cross-Sentence Latent Variable Model for Semi-Supervised Text Sequence Matching, The 57th Annual Meeting of the Association for Computational Linguistics (ACL), 2019.
Kang Min Yoo, Youhyun Shin, Sang-goo Lee, Data Augmentation for Spoken Language Understanding via Joint Variational Generation, Thirty-Third AAAI Confernce on Artificial Intelligence (AAAI), 2019.
Taeuk Kim, Jihun Choi, Daniel Edmiston, Sanghwan Bae, Sang-goo Lee, Dynamic Compositionality in Recursive Neural Networks with Structure-aware Tag Representations, Thirty-Third AAAI Confernce on Artificial Intelligence (AAAI), 2019.
Jihun Choi, Kang Min Yoo, Sang-goo Lee, Learning to Compose Task-Specific Tree Structures, Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018.
글로벌 인터넷 빅 텍스트 데이터 실시간 모니터링, 과학기술정보통신부, 2016~2021.
지능형 음성인식을 위한 Q&A 기술 선행 연구, 현대엔지비(주), 2017~.

문태섭공과대학 전기정보공학부

  • 연구실/전공분야M.IN.D (Machine INtelligence and Data science) Lab
  • 연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Data Intelligence, Brain & Mind, AI Law & Ethics
  • 연구분야(X+AI)Brain, Bio, Energy

대표논문

Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization. Sangwon Jung, Taeeon Park, Sanghyuk Chun, and Taesup Moon. The 11th International Conference on Learning Representations (ICLR), May 2023

Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. Hongjoon Ahn, Youngyi Yang, Quan Gan, David Wipf, and Taesup Moon. Neural Information Processing Systems (NeurIPS), December 2022

GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training. Jaeseok Byun, Taebaek Hwang, Jianlong Fu, and Taesup Moon. European Conference on Computer Vision (ECCV), October 2022

Learning Fair Classifiers with Partially Annotated Group Labels. Sangwon Jung, Sanghyuk Chun, and Taesup Moon. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2022

SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, and Taesup Moon. Neural Information Processing Systems (NeurIPS), December 2021

SS-IL: Separated Softmax for Incremental Learning. Hongjoon Ahn, Jihwan Kwak, Subin Lim, Hyeonsu Bang, Hyojun Kim, and Taesup Moon. International Conference on Computer Vision (ICCV), October 2021

Fair Feature Distillation for Visual Recognition. Sangwon Jung, Donggyu Lee, Taeeon Park, and Taesup Moon. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2021

FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise. Jaeseok Byun, Sungmin Cha, and Taesup Moon. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2021

Continual Learning with Node-Importance based Adaptive Group Sparse Regularization. Sangwon Jung, Hongjoon Ahn, Sungmin Cha, and Taesup Moon. Neural Information Processing Systems (NeurIPS), December 2020

Uncertainty-based continual learning with adaptive regularization. Hongjoon Ahn, Sungmin Cha, Donggyu Lee and Taesup Moon. Proceedings of Neural Information Processing Systems (NeurIPS), December 2019

Fooling neural network interpretations via adversarial model manipulation. Juyeon Heo, Sunghwan Joo, and Taesup Moon. Proceedings of Neural Information Processing Systems (NeurIPS), December 2019

제원호자연과학대학 물리천문학부

  • 연구실/전공분야원자물리 및 광학실험
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Platform, Data Intelligence
  • 연구분야(X+AI)Manufacturing, AI-based instruments

대표논문

Interfacial thermodynamics of spherical nanodroplets: Molecular understanding of surface tension via hydrogen bond network
GCIceNet: A Graph Convolution Network For Deep Learning Of Ice Phases
AI-based atomic force microscopy
리더연구과제 0차원 나노플루이딕스

이유리생활과학대학 의류학과

  • 연구실/전공분야패션 머천다이징 랩
  • 연구분야(AI 원천기술)Learning & Reasoning, Human-AI Interaction, Data Intelligence
  • 연구분야(X+AI)Humanities/Social Sciences

대표논문

윤형진의과대학 의공학교실

  • 연구실/전공분야의공학(보건의료정보)/내과학(신장학)
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence
  • 연구분야(X+AI)Medicine

대표논문

Predicting acute kidney injury in cancer patients using heterogenous and irregular data/PLoS One, 2018,13:e0199839/Park N, Kang E, Park M, Lee H, Kang HG, Yoon HJ, Kang U/JMIR mHealth uHealth, 2019,7:e13327/Kwon SB, Ahn JW, Lee SM, Lee J, Lee D, Hong J, Kim HC, Yoon HJ
Unobtrusive estimation of cardiopulmonary fitness with daily activity in healthy young men/J Korean Med Sci, 2017, 32:1947-1952/Ahn JW, Hwang SH, Yoon C, Lee J, Kim HC, Yoon HJ
Predicting acute kidney injury in cancer patients using heterogenous and irregular data/PLoS One, 2018,13:e0199839/Park N, Kang E, Park M, Lee H, Kang HG, Yoon HJ, Kang U
개인정보보호 강화 DisTIL 알고리즘 개발/보건산업진흥원/2019~2021
암흑데이터 극한활용 연구센터/연구재단/2018~2025

서교국제농업기술대학원 그린에코시스템공학전공

  • 연구실/전공분야Green Resources Engineering Center
  • 연구분야(AI 원천기술)AI Platform, Data Intelligence
  • 연구분야(X+AI)Humanities/Social Sciences, Logistics, agriculture

대표논문

A Comparative Analysis of the Environmental Benefits of Drone-Based Delivery Services in Urban and Rural Areas
Leveraging Socially Networked Mobile ICT Platforms for the Last-Mile Delivery Problem
공간빅데이터 기반의 농산물 스마트 로지스틱스 파일럿 시스템 구축

서진욱공과대학 컴퓨터공학부

  • 연구실/전공분야휴먼-컴퓨터 인터액션 연구실
  • 연구분야(AI 원천기술)Vision & Perception, Human-AI Interaction, Data Intelligence
  • 연구분야(X+AI)Humanities/Social Sciences, Medicine, Manufacturing

대표논문

Jaemin Jo and Jinwook Seo, "Disentangled Representation of Data Distributions in Scatterplots," 2019 IEEE Visualization Conference (VIS), Vancouver, BC, Canada, 2019, pp. 136-140.
Daekyoung Jung, Wonjae Kim, Hyunjoo Song, Jeong-in Hwang, Bongshin Lee, Bohyoung Kim, and Jinwook Seo, ChartSense: Interactive Data Extraction from Chart Images, In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '17), pp. 6706-6717, 2017.

이원종자연과학대학 물리천문학부

  • 연구실/전공분야Lattice Gauge Theory Research Center
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence, AI and data analysis
  • 연구분야(X+AI)Physics

대표논문

  • 연구실/전공분야생명정보 및 생물정보 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Platform, Data Intelligence
  • 연구분야(X+AI)Bio, Medicine, Pharma

대표논문

PRISM: Methylation Pattern-based, Reference-free Inference of Subclonal Makeup (ISMB 2019, Bioinformatics)
mirTime: Identifying Condition-Specific Targets of MicroRNA in Time-series Transcript Data using Gaussian Process Model and Spherical Vector Clustering (Bioinformatics 2019)
GABA-stimulated adipose-derived stem cells suppress subcutaneous adipose inflammation in obesity (PNAS, 2019)
DeepFam: Deep learning based alignment-free method for protein family modeling and prediction (ISMB 2018, Bioinformatics)
Hybrid Approach of Relation Network and Localized Graph Convolutional Filtering for Breast Cancer Subtype Classification (IJCAI 2017)
과제명: 멀티오믹스 분석 알고리즘 및 플랫폼 개발
연구비 지원기관: 한국연구재단 (과학기술정보통신부)
연구수행 기간: 2014.11.01 - 2022.10.31 (96개월)
과제명: 실험 및 문헌정보 거대 복잡형 데이터 통합분석추론 연구
연구비 지원기관: 한국연구재단 (과학기술정보통신부)
연구기간: 2017.9.1 - 2020.12.31 (40개월)

이해영의과대학 내과학교실

  • 연구실/전공분야고혈압, 이상지질혈증, 심부전, 심장이식, 당뇨 심혈관병증
  • 연구분야(AI 원천기술)Human-AI Interaction, Data Intelligence
  • 연구분야(X+AI)Bio, Medicine

대표논문

Artificial intelligence utilized cholesterol profile calculation
Common data modeling

윤성로공과대학 전기정보공학부

  • 연구실/전공분야인공지능 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Language & Cognition, AI Platform, AI Chip, Data Intelligence, AI Security
  • 연구분야(X+AI)Bio, Medicine, Pharma, Finance, Manufacturing, Energy

대표논문

안우영사회과학대학 심리학과

  • 연구실/전공분야Computational Clinical Science Laboratory
  • 연구분야(AI 원천기술)Learning & Reasoning, Language & Cognition, Data Intelligence, Computational neuroscience
  • 연구분야(X+AI)Bio, Humanities/Social Sciences, Brain

대표논문

Ahn, W.-Y., Kishida, K. T., Gu, X., Lohrenz, T., Harvey, A. H., Alford, J. R., Smith, K. B., Yaffe, G., Hibbing, J. R., Dayan, P., & Montague, P. R. (2014) Nonpolitical images evoke neural predictors of political ideology. Current Biology, 24, 1-7.
Ahn, W.-Y., Haines, N., & Zhang, L. (2017) Revealing neuro-computational mechanisms of reinforcement learning and decision-making with the hBayesDM package. Computational Psychiatry, 1:1.
Ahn, W.-Y. & Vassileva, J. (2016) Machine learning identifies substance-specific behavioral markers for heroin and amphetamine dependence. Drug and Alcohol Dependence, 161, 247-257.
Aylward, J., Valton, V., Ahn, W. Y., Bond, R. L., Dayan, P., Roiser, J. P., & Robinson, O. J. (2019). Altered learning under uncertainty in unmedicated mood and anxiety disorders. Nature Human Behaviour, 3(10), 1116-1123.
Yang, J., Pitt, M. A., Ahn, W. Y., & Myung, J. I. (in press) ADOpy: A Python Package for Adaptive Design Optimization. Behavior Research Methods.
  기계학습을 이용한 빠르고 높은 신뢰도의 멀티모달 금연 표지 개발, 한국연구재단 (연구책임자), 2017-2022년
작업기억-의사결정 상호작용의 뇌신경망에 관한 통합적 연구, 한국연구재단 (공동연구자), 2018-2020년
뇌영상기법과 기계학습을 이용한 비정상적 의사결정의 신경계산학적 기전 연구, 서울대학교 창의선도 신진 연구자 지원사업 (연구책임자), 2019-2022년

이덕주공과대학 산업공학과

  • 연구실/전공분야경제성 분석 연구실
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)Finance, Commerce, Energy

대표논문

정진호의과대학 피부과학교실

  • 연구실/전공분야피부면역학, 피부노화학, 광생물학, 노인피부과
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Platform, Data Intelligence
  • 연구분야(X+AI)Bio, Humanities/Social Sciences, Medicine

대표논문

서봉원융합과학기술대학원 지능정보융합학과

  • 연구실/전공분야Human-Centered Computing Laboratory
  • 연구분야(AI 원천기술)Human-AI Interaction, Data Intelligence
  • 연구분야(X+AI)Humanities/Social Sciences, Medicine, Finance

대표논문

I lead, you help but only with enough details: Understanding user experience of co-creation with artificial intelligence, CHI 2018
Us vs. them: Understanding artificial intelligence technophobia over the google deepmind challenge match, CHI 2017
Enhancing VAEs for collaborative filtering: flexible priors & gating mechanisms, RecSys 2019
Bot in the Bunch: Facilitating Group Chat Discussion by Improving Efficiency and Participation with a Chatbot, CHI 2020
Understanding User Perception of Automated News Generation System, CHI 2002
심전도 데이터를 활용한 부정맥 진단 알고리즘 모델 공동 개발, LG전자, 2019-11-20 ~ 2020-06-30
AI기반 문자인식(OCR) 알고리즘, 교보생명주식회사, 2019-10-21 ~ 2020-03-20
로봇 저널리즘 기반의 방송 뉴스 콘텐츠 제작 기술 개발, 과기정통부, 2017-04-01 ~ 2019-12-31

권태경공과대학 컴퓨터공학부

  • 연구실/전공분야인터넷 융합 및 보안 연구실
  • 연구분야(AI 원천기술)Vision & Perception, Data Intelligence, AI Security
  • 연구분야(X+AI)Humanities/Social Sciences, Commerce

대표논문

"Magnetic Field based Indoor Localization System: A Crowdsourcing Approach",  International Conference on Indoor Positioning and Indoor Navigation (IPIN 2019), Pisa, Italy, September 2019
"Unveiling a Socio-Economic System in a Virtual World: A Case Study of an MMORPG", World Wide Web Conference (WWW) 2018 (Industry track), Lyon, France, April. 2018.
"Privacy Leakage in Event-based Social Networks: A Meetup Case Study", In Proceedings of ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW`18), Jersey City, United States, November 2018

장혜식자연과학대학 생명과학부

  • 연구실/전공분야High-Throughput Biology
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)Bio, Medicine

대표논문

H. Chang, J. Yeo, J.-g. Kim, H. Kim, J. Lim, M. Lee, H. H. Kim, J. Ohk, H.-Y. Jeon, H. Lee, H. Jung, K.-W. Kim and V. N. Kim (2018) “Terminal Uridylyltransferases Execute Programmed Clearance of Maternal Transcriptome in Vertebrate Embryos” Molecular Cell, 70(1):72-82.e7.
H. Chang, J. Lim, M. Ha, and V. N. Kim (2014) “TAIL-seq: Genome-wide Determination of Poly(A) Tail Length and 3′ End Modifications” Molecular Cell, 53(6):1044-1052.
J. Lim, M. Ha, H. Chang, S. C. Kwon, D. K. Simanshu, D. J. Patel, and V. N. Kim (2014) “Uridylation by TUT4 and TUT7 marks mRNA for degradation” Cell, 159(6):1365-1376.
J. Cho, H. Chang, S. C. Kwon, B. Kim, Y. Kim, J. Choe, M. Ha, Y. K. Kim and V. N. Kim (2012) “LIN28A is a suppressor of ER-associated translation in embryonic stem cells” Cell, 151: 765-777.
J. Lim, D. Kim, Y. Lee, M. Ha, M. Lee, J. Yeo, H. Chang, J. Song, K. Ahn, V. N. Kim (2018) “Mixed tailing by TENT4A and TENT4B shields mRNA from rapid deadenylation” Science, eaam5794.

김형주공과대학 컴퓨터공학부

  • 연구실/전공분야인터넷 데이터베이스 연구실
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)Data Preprocessing

대표논문

Hye-Won Lim; Hyoung-Joo Kim, "Tensor-based tag emotion aware recommendation with probabilistic ranking", KSII Transactions on Internet and Information Systems, vol. 13, no. 12, pp. 5826-5841, 2019
Hye-Won Lim; Hyoung-Joo Kim, "Item recommendation using tag emotion in social cataloging services", Expert Systems with Applications 89, pp.179-187, 2017
Hee-Gook Jun; Dong-Hyuk Im; Hyoung-Joo Kim, "An RDF Metadata-based Weighted Semantic Pagerank Algorithm", International Journal of Web & Semantic Technology, vol. 7 no. 2 pp. 11-24, Apr. 2016
Woo-Hyun Lee, Hee-Gook Jun, and Hyoung-Joo Kim, "Hadoop Mapreduce Performance Enhancement Using In-Node Combiners", International Journal of Computer Science & Information Technology, vol. 7 no. 5 pp. 1-18, Oct. 2015
Hyunwoo Kim, Taewhi Lee, and Hyoung-Joo Kim, "A Parallel Tag Affinity Computation for Social Tagging Systems using MapReduce", International Journal of Big Data Intelligence, vol. 1 no. 3 pp. 141-150, 2014
삼성전자 반도체부문을 위한 Data Scientist 교육,  2018년 ~ 현재

나종연생활과학대학 소비자학과

  • 연구실/전공분야Consumer Information & Retailing Lab.
  • 연구분야(AI 원천기술)Human-AI Interaction, Data Intelligence, AI Law & Ethics
  • 연구분야(X+AI)Humanities/Social Sciences, Commerce

대표논문

"Personalization-privacy paradox and consumer conflict with the use of location based commerce", Computers in Human Behavior, 63, 453-462
"Consumer ambivalence towards personlized technology and intention to use mobile commerce: The moderating role of gender", International Journal of Electrononic Commerce Studies, 8(2), 158-179
"온라인트래킹에 대한 소비자 인식과 정책적 시사점",  소비자학연구,  29(2), 171-198
온라인 환경에서 아동에 특화된 개인정보보호 연구, 한국인터넷진흥원, 2019.7-12.
패션이미지의 속성 분석을 통한 Fad Detection,  민간과제, 2019.

김홍기치의학대학원 치의학과

  • 연구실/전공분야의료정보학
  • 연구분야(AI 원천기술)Language & Cognition, AI Platform, Data Intelligence
  • 연구분야(X+AI)Bio, Humanities/Social Sciences, Medicine

대표논문

Multi-channel PINN: investigating scalable and transferable neural networks for drug discovery. Journal of Chemical Informatics 11.1 (2019): 46
Cognitive Profiling Related to Cerebral Amyloid Beta Burden Using Machine Learning Approaches. Frontiers in Aging Neuroscience. 10.3389 (2019)
The Disturbance in Dynamic Property in the Reconstructed State Space during Nitrous Oxide Administration. Neuroreport 30.3(2019):162–68
Differential Diagnosis of Jaw Pain using Informatics Technology. Journal of Oral Rehabilitation (2018)
A dynamic and parallel approach for repetitive prime labeling of XML with MapReduce, The Journal of Supercomputing, 73:2 (2017)

민경복의과대학 예방의학교실

  • 연구실/전공분야환경보건학
  • 연구분야(AI 원천기술)Language & Cognition, Data Intelligence, Data Mining
  • 연구분야(X+AI)Humanities/Social Sciences, Medicine, Environmental Health

대표논문

Min JY, Song SH, Kim H, Min KB. Mining Hidden Knowledge About Illegal Compensation for Occupational Injury: Topic Model Approach. JMIR Med Inform. 2019;7(3):e14763.
Kim HJ, Min JY, Min KB. Successful Aging and Mortality Risk: The Korean Longitudinal Study of Aging (2006-2014). J Am Med Dir Assoc. 2019;20(8):1013-1020.
Min JY, Min KB. Cumulative exposure to nighttime environmental noise and the incidence of peptic ulcer. Environ Int. 2018;121(Pt2):1172-1178
Min JY, Kim HJ, Yoon C, Lee K, Yeo M, Min KB. Tuberculosis infection via the emergency department among inpatients in South Korea: a propensity score matched analysis of the National Inpatient Sample. J Hosp Infect. 2018;100(1):92-98.
Min JY, Min KB. Exposure to ambient PM10 and NO2 and the incidence of attention-deficit hyperactivity disorder in childhood. Environ Int. 2017;99:221-227.
모바일 헬스 기반 미세먼지 노출에 의한 이상징후 예측 및 질환 발생 기전 연구: Life log data 구축과 머신러닝 분석 기법 활용(한국연구재단, 과학기술정보통신부, 2019.3-2022.2)
취약계층 맞춤형 한파피해 위험 진단기술 개발(국립재난안전연구원, 행정안전부, 2019.6-2020.1)

황승원공과대학 컴퓨터공학부

  • 연구실/전공분야언어 데이터 지능 연구실
  • 연구분야(AI 원천기술)Language & Cognition,Data Intelligence
  • 연구분야(X+AI)검색, 언어, 지식그래프

박기완경영대학 경영학과

  • 연구실/전공분야Strategic Brand Management, Consumer Behavior, Consumer Insight
  • 연구분야(AI 원천기술)Learning & Reasoning, Human-AI Interaction, Data Intelligence
  • 연구분야(X+AI)Arts, Humanities/Social Sciences, Commerce

대표논문

Kim, Hakkyun, Kyoungmi Lee, and Kiwan Park (2015), “Balancing Out Feelings of Risk by Playing It Safe: The Effect of Social Networking on Subsequent Risk Judgment,” Organizational Behavior and Human Decision Processes, 131(November), 121-131.
Kim, Hakkyun, Kiwan Park, and Norbert Schwarz (2010), “Will This Trip Really Be Exciting? The Role of Incidental Emotions in Product Evaluation,” Journal of Consumer Research, 36 (April), 983-991.
Priester, Joseph R., Richard E. Petty, and Kiwan Park (2007), “Whence Univalent Ambivalence? From the Anticipation of Conflicting Reactions,” Journal of Consumer Research, 34(June), 11-21.
4차산업 혁명 시대의 서비스 사용 촉진 및 저해 요인에 대한 분석, 한국연구재단 중견연자지원(2019S1A5A2A01050564), 2019.07-2022.06, 연구책임자

임재현경영대학 경영학과

  • 연구실/전공분야Sustainable Operations Management, Supply Chain and Logistics Management, Data Analytics
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Platform, Data Intelligence
  • 연구분야(X+AI)Commerce, Energy, Manufacturing, Logistics

대표논문

Optimal Ratcheting in Executive Compensation. Decision Analysis, accepted. with I. Hwang, Y. Kim.

Got Organic Milk? Joint Inventory Model with Supply Uncertainties and Partial Substitution. Operations Research Letters, 49(5), 2021. with D. Jeon, Z. Peng, Y. Rong.

Why Have Voluntary Time-of-Use Tariffs Fallen Short in the Residential Sector? Production & Operations Management, 29(3), 2020. with D.G. Choi, K. Murali, V. Thomas

Money Well Spent? Operations, Mainstreaming, and Fairness of Fair Trade. Production & Operations Management, 28(12), 2019. with H.Y. Mak, S.J. Park

The Effects of Ecolabels and Environmental Regulation on Green Product Development. Manufacturing & Service Operations Management, 21(3), 2019. with K. Murali, N.C. Petruzzi

Promoting Clean Technology Products: To Subsidize Products or Service Infrastructure? Service Science, 11(2), 2019. with G. Ma, H.Y. Mak, Z. Wan

Beyond the Speed-Price Tradeoff. MIT Sloan Management Review, 59(4), Summer, 2018. with J. Acimovic, H.Y. Mak

권준수자연과학대학 뇌인지과학과

  • 연구실/전공분야임상인지신경과학센터
  • 연구분야(AI 원천기술)Language & Cognition, Data Intelligence
  • 연구분야(X+AI)Medicine

대표논문

강박증 환자에서 machine learning을 이용한 치료반응 차이의 비교
The effects of pharmacological treatment on functional brain connectome in obsessive-compulsive disorder. Biol Psychiatry 2014;75(8):606-614

윤용태공과대학 전기정보공학부

  • 연구실/전공분야전력시스템 및 경제 연구실
  • 연구분야(AI 원천기술)Data Intelligence, Energy AI
  • 연구분야(X+AI)Energy

대표논문

SH Oh, SW Kim, YT Yoon, Real-time Reconfiguration Strategy of Self-adequate Distribution Network based on Deep Reinforcement Learning, CIGRE Symposium 2019, Aalborg, Denmark, 4-7 June 2019.

조성준공과대학 산업공학과

  • 연구실/전공분야빅데이터 AI 센터
  • 연구분야(AI 원천기술)Learning & Reasoning, Language & Cognition, Data Intelligence
  • 연구분야(X+AI)Finance, Logistics, Manufacturing

대표논문

세상을 읽는 새로운 언어, 빅데이터, 조성준, 21세기북스, 2019.08.28, ISBN 9788950982737
Fault Detection and Diagnosis Using Self-Attentive Convolutional Neural Networks for Variable-length Sensor Data in Semiconductor Manufacturing, Eunji kim, Sungzoon Cho, Byeong eon Lee, Myoungsu Cho, IEEE Transactions on Semiconductor Manufacturing, Volume: 32 , Issue: 3 , Aug. 2019, Page(s): 302 - 309
Champion-challenger analysis for credit card fraud detection: hybrid ensemble and deep learning, Eunji Kim, Jehyuk Lee, Hunsik Shin, Hoseong Yang, Sungzoon Cho, Seung-kwan Nam, Youngmi Song, Jeong-a Yoon, Jong-il Kim, Wooho Chung, Kyungmo La, Kangshin Ko, Expert Systems with Applications, Volume 128, 15 August 2019, Pages 214-224
Stock Price Prediction through Sentiment Analysis of Corporate Disclosures Using Distributed Representation, Misuk Kim, Eunjeong Lucy Park, and Sungzoon Cho, Intelligent Data Analysis Journal, Vol. 22(6) pp. 1395-1413 December, 2018
"Machine learning-based anomaly detection via integration of manufacturing, inspection and after-sales service data", Taehoon Ko, Je Hyuk Lee, Hyunchang Cho, Sungzoon Cho, Wounjoo Lee, Miji Lee, Industrial Management & Data Systems, Vol. 117 Issue: 5, 2017, pp.927-945
기업 공시 데이터를 활용한 기업 네트워크 구축, 연구재단, 2018~2021
기계학습을 활용한 데이터 기반 진단, 고장예지 및 내구성 평가, 삼성전자, 2016~2021
예방품질능력 강화 위한 컨버터 지능형 진단 기술 개발, 현대차, 2018~2019

국웅자연과학대학 수리과학부

  • 연구실/전공분야조합론, 대수적위상수학
  • 연구분야(AI 원천기술)Vision & Perception, Data Intelligence
  • 연구분야(X+AI)Medicine, Manufacturing

대표논문

Simplicial networks and effective resistance (co-author: K. Lee),
Advances in Applied Mathematics, Volume 100 (September 2018) 71-86
Can knowledge be more accessible in a virtual network?: Collective dynamics of knowledge transfer in a virtual knowledge organization network (coauthor: S. Shin),
Decision Support Systems (March 2014),
Combinatorial Green’s function of a graph and applications to networks,
Advances in Applied Mathematics, Volume 46 (Jan. 2011) 417-423
Topological data analysis can extract subgroups with high rates of Type 2 diabetes
(co-authors: H. Kim, C. Yi, Y. Kim, U. Park, B. Oh, H. Kim, T. Park),
International Journal of Data Mining and Bioinformatics 22(1):61-74 (20 April 2019 online)
Harmonic cycles for graphs, (co-author: Y. Kim)   
Linear and Multilinear Algebra (online February 2018)
위상수학적 조합론과 데이터 과학, 과학기술정보통신부, 2018-09-01 ~ 2022-08-31
심장질환판단서비스를 위한 딥러닝 알고리즘의 개발, 정보통신산업진흥원,
2019-09-01 ~ 2019-12-31

Myunghee Cho Paik (조명희)자연과학대학 통계학과

  • 연구실/전공분야생물통계 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Data Intelligence
  • 연구분야(X+AI)Medicine, Commerce, Manufacturing

대표논문

Contextual multi-armed bandit algorithm for semiparametric reward model. presented at ICML 2019
Doubly Robust Lasso Bandit. presented at NeurIPs 2019
Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric.  presented at ACML 2019 and published at Machine Learning
Lipschitz continuous autoencoders in application to anomaly detection.  accepted for AISTAT 2020
Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation. published at CSDA
딥러닝의 통계적 접근: 의료영상자료를 위한 합성곱 신경망 모형의 새로운 통계적 추론 방법 연구 (연구재단 중견연구, 2017-03-01 - 2020-02-29)

한상진환경대학원 환경계획학과

  • 연구실/전공분야교통안전공학랩
  • 연구분야(AI 원천기술)Autonomous Driving, Data Intelligence
  • 연구분야(X+AI)Transportation, Big Data

대표논문

Han, S., & Chang, J. S. (2021). Identifying Priority Crosswalk Locations in Urban Road Networks. Journal of Urban Planning and Development, 147(2), 04021014.
Chang, J. S., Han, S., & Jo, S. (2020). Road safety performance across local governments: a data envelopment analysis approach. International journal of injury control and safety promotion, 27(4), 447-457.
Han, S., & Lee, H. (2020). Comparison of road safety management systems of local governments using indicators. Transportation research record, 2674(12), 435-446.
Persia, L., Usami, D. S., De Simone, F., De La Beaumelle, V. F., Yannis, G., Laiou, A., ... & Salathè, M. (2016). Management of road infrastructure safety. Transportation research procedia, 14, 3436-3445.
Han, S. (2016). Note on evaluating safety performance of road infrastructure to motivate safety competition. International journal of injury control and safety promotion, 23(1), 85-92.
Chang, J. S., Han, S., Jung, D., & Kim, D. (2014). Benefits of rerouting railways to tunnels in urban areas: a case study of the Yongsan line in Seoul. International Journal of Urban Sciences, 18(3), 404-415.
Lee, D., Han, S. J., & Kim, D. G. (2011). Evaluating prioritization of ASEAN highway network development using a fuzzy multiple attribute decision making method. Journal of advanced transportation, 45(2), 129-142.
Han, S. (2007). A route-based solution algorithm for dynamic user equilibrium assignments. Transportation Research Part B: Methodological, 41(10), 1094-1113.
Han, S., & Heydecker, B. G. (2006). Consistent objectives and solution of dynamic user equilibrium models. Transportation Research Part B: Methodological, 40(1), 16-34.
Han, S. (2003). Dynamic traffic modelling and dynamic stochastic user equilibrium assignment for general road networks. Transportation Research Part B: Methodological, 37(3), 225-249.
한상진, 김은우, 장효석, & 주종완. (2023). 자동긴급제동장치의 고령운전자 추돌사고 감소 효과 추정. 한국 ITS 학회논문지, 22(1), 161-171.
김혜원·한상진 2022. 교통안전성과지표 도입에 따른 지자체 교통안전 관리체계 개선 효과 분석, 대한교통학회
한상진 2022. 단독주택지구 도로의 소방자동차 진입 가능성 지표 개발 및 활용방안, 교통연구 제29권 제2호, pp37-46.
한상진·장효석·조준한·오주석·윤일수 2020. 고령운전자를 위한 조건부 운전면허제도 개선방향 연구, 한국ITS학회논문지 19(5), pp29-39.
이선영·한상진·정연식 2020. 순서형 프로빗모형을 이용한 강우시 고속도로 교통사고 심각도 분석, 교통연구 제27권 제1호, pp1-11. (교신)

공동저서
한상진, 장수은, 진장원 2019. 보행교통의 이해-걷기좋은도시 만들기의 첫걸음, 키네마인.
한상진 2020. 녹색교통을 위한 도시 가로의 재구성, in「감염병 시대 도시변화의 방향을 묻다」, 서울연구원 pp 75-97.
안전속도 5030 설계·운영매뉴얼 2019. 한상진(편), 경찰청·국토교통부

신영기융합과학기술대학원 분자의학및바이오제약학과

  • 연구실/전공분야분자병리학 연구실
  • 연구분야(AI 원천기술)Data Intelligence
  • 연구분야(X+AI)Bio, Medicine, Pharma

대표논문

Mi Jeong Kwon, Sae Byul Lee, Jinil Han, Jeong Eon Lee, Jong Won Lee, Gyungyub Gong, Peter D. Beitsch, Seok Jin Nam, Sei Hyun Ahn, Byung-Ho Nam, Young Kee Shin. BCT score predicts chemotherapy benefit in Asian patients with mone receptor-positive, HER2-negative, lymph node-negative breast cancer. PLoS One. 2018 Nov 21;13(11):e0207155. doi: 10.1371/journal.pone.0207155. eCollection 2018
Han J, Choi YL, Kim H, Choi JY, Lee SK, Lee JE, Choi JS, Park S, Choi JS, Kim YD, Nam SJ, Nam BH, Kwon MJ, Shin YK. MMP11 and CD2 as Novel Prognostic Factors in Hormone Receptor-Negative, HER2-Positive Breast Cancer. Breast Cancer Res Treat. 2017 Apr 13. doi: 10.1007/s10549-017-4234-4. [Epub ahead of print]
Gong G, Kwon MJ, Han J, Lee HJ, Lee SK, Lee JE, Lee SH, Park S, Choi JS, Cho SY, Ahn SH, Lee JW, Cho SR, Moon Y, Nam BH, Nam SJ, Choi YL, Shin YK. A new molecular prognostic score for predicting the risk of distant metastasis in patients with HR+/HER2- early breast cancer. Scientific Reports. 2017 Mar 28;7:45554. doi: 10.1038/srep45554.
Oh E, Choi Y-L, Park T, Lee S, Nam SJ, Shin YK. A prognostic model for lymph node-negative breast cancer patients based on the integration of proliferation and immunity. Breast Cancer Res Treat. 2012 Apr;132(2):499-509. doi: 10.1007/s10549-011-1626-8

윤명환공과대학 산업공학과

  • 연구실/전공분야휴먼 인터페이스 시스템 연구실
  • 연구분야(AI 원천기술)Human-AI Interaction, Data Intelligence, Autonomous Driving, User Interface User Experience
  • 연구분야(X+AI)Humanities/Social Sciences, Human Factors Cognitive Engineering

대표논문

A Systematic Review of a Virtual Reality System from the Perspective of User Experience Yong Min Kim, Ilsun Rhiu, Myung Hwan Yun 2019
International Journal of Human–Computer Interaction 1-18
Mining affective experience for a kansei design study on a recliner Wonjoon Kim, Taehoon Ko, Ilsun Rhiu, Myung Hwan Yun
2019/1/1 Applied ergonomics 74 145-153
Queueing Network Based Driver Model for Varying Levels of Information Processing
Ye Lim Rhie, Ji Hyoun Lim, Myung Hwan Yun 2018/10/31 IEEE Transactions on Human-Machine Systems 49 6 508-517
Classification of children’s sitting postures using machine learning algorithms Yong Min Kim, Youngdoo Son, Wonjoon Kim, Byungki Jin, Myung Hwan Yun
2018/8 Applied Sciences 8 8 1280
Exploring User Experience of Smartphones in Social Media: A Mixed-Method Analysis
Ilsun Rhiu, Myung Hwan Yun 2018/5/14
International Journal of Human–Computer Interaction
AI 를 이용한 스마트 체어 시스템. 산업부/DBK 2017-2019

이종섭경영대학 경영학과

  • 연구실/전공분야International Corporate Finance, Corporate Governance, Credit Risk
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence, AI Law & Ethics
  • 연구분야(X+AI)Humanities/Social Sciences, Finance, Commerce

대표논문

박순애행정대학원 행정학과

  • 연구실/전공분야성과관리, 위험관리, 환경정책, 정책평가
  • 연구분야(AI 원천기술)Human-AI Interaction, Data Intelligence, AI Security
  • 연구분야(X+AI)Humanities/Social Sciences, Finance, Energy

대표논문

Public Choice in Transit Organization and Finance: The Structure of Support. Transportation Research Record (SCI) 1669:87-95.
Regional Model of EKC for Air Pollution: Evidence from the Republic of Korea. Energy Policy (SSCI). 39, 2011
The Environmental Effects of the CNG Bus Program on Metropolitan Air Quality in Korea, The Annals of Regional Science (SSCI). 49 (1) 2012
Imperfect Information and Labor Market Bias against Small and Medium-sized Enterprises: A Korean Case, Small Business Economics: An Entrepreneurship Journal (SSCI). 2014. 10
Public Management in Korea: Performance Evaluation and Public Institutions (Ed). Routledge, 2018

김주한의과대학 의과학과

  • 연구실/전공분야의료정보학
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence
  • 연구분야(X+AI)Bio, Medicine

대표논문

강유공과대학 컴퓨터공학부

  • 연구실/전공분야데이터 마이닝 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Platform, Data Intelligence
  • 연구분야(X+AI)Finance, Commerce, Manufacturing

대표논문

Jaemin Yoo, Minyong Cho, Taebum Kim, and U Kang, Knowledge Extraction with No Observable Data, NeurIPS 2019, Vancouver, Canada.
Jaemin Yoo, Hyunsik Jeon, and U Kang, Belief Propagation Network for Hard Inductive Semi-supervised Learning, 28th International Joint Conference on Artificial Intelligence (IJCAI) 2019, Macao, China.
Junghwan Kim, Haekyu Park, Ji-Eun Lee, and U Kang, SIDE: Representation Learning in Signed Directed Networks, The Web Conference (WWW) 2018, Lyon, France.
Minji Yoon, Woojeong Jin, and U Kang, Fast and Accurate Random Walk with Restart on Dynamic Graphs with Guarantees, The Web Conference (WWW) 2018, Lyon, France.
Jun-gi Jang, Dongjin Choi, Jinhong Jung, and U Kang, Zoom-SVD: Fast and Memory Efficient Method for Extracting Key Patterns in an Arbitrary Time Range, ACM International Conference on Information and Knowledge Management (CIKM) 2018, Lingotto, Turin, Italy.
초고속 텐서 스트림 분석을 통한 실시간 경량 다차원 데이터 마이닝, 과학기술정보통신부, 2019 - 2022
시청이력기반 콘텐츠 추천 기술, SK Telecom, 2018
Real-time Anomaly Detection in High-Speed Time-evolving Graphs, AOARD, 2017 - 2018

김동규공과대학 건설환경공학부

  • 연구실/전공분야교통계획·물류연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence, Autonomous Driving
  • 연구분야(X+AI)Humanities/Social Sciences, Logistics, Smart mobility

대표논문

Ham, S., H. Park, E. Kim, S. Kho, and D. Kim. “Investigating the Influential Factors for Practical Application of Multiclass Vehicle Detection for Images from Unmanned Aerial Vehicle Using Deep Learning Models.” Proceedings of the 99th Annual Meeting of the Transportation Research Board, Washington, D. C., U.S.A., January 12-16, 2020.
Kim, E., H. Park, S. Kho, and D. Kim*. (2019.12) “A Hybrid Approach Based on Variational Mode Decomposition for Analyzing and Predicting Urban Travel Speed.” Journal of Advanced Transportation, Vol. 2019, Article ID 3958127. https://doi.org/10.1155/2019/3958127.
Kim, E., H. Park, S. Ham, S. Kho, and D. Kim*. (2019.04) “Extracting Vehicle Trajectories Using Unmanned Aerial Vehicles in Congested Traffic Conditions.” Journal of Advanced Transportation, Vol. 2019, Article ID 9060797. https://doi.org/10.1155/2019/9060797.
Park, H., D. Kim*, and S. Kho. (2018.12) “Bayesian Network for Freeway Traffic State Prediction.” Transportation Research Record: Journal of the Transportation Research Board, Vol. 2672, No. 45, pp. 124-135. DOI: 10.1177/0361198118786824.
영상 기반 딥 생성 모델을 활용한 차로별 미시교통정보 생성, 과학기술정보통신부, 2019.09-2020.08
무인항공기와 루프검지기 기반의 통합차량검지시스템을 이용한 교통혼잡 관리전략 개발, 과학기술정통부, 2016.06-2019.05

박건수공과대학 산업공학과

  • 연구실/전공분야Operations Management, Inventory control, Global supply chain
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Platform, Data Intelligence
  • 연구분야(X+AI)Finance, Logistics, Manufacturing

대표논문

서경원경영대학 경영학과

  • 연구실/전공분야Asset Pricing, Derivatives, Machine Learning, Data Science
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence
  • 연구분야(X+AI)Finance, Commerce

대표논문

고길곤행정대학원 행정학과

  • 연구실/전공분야계량분석 및 연구방법론, 정책분석, 의사결정이론, 중국행정개혁
  • 연구분야(AI 원천기술)Data Intelligence, Public Data Analytics and Visualization
  • 연구분야(X+AI)Humanities/Social Sciences

대표논문

Kilkon Ko (2020), Multivariate Analysis, Munwoo Publisher, forthcoming
Kilkon Ko (2019), Categorical Data Analysis, Munwoo Publisher
Kilkon Ko (2019), Data Analysis and Visualization, Parkyoung Publisher
질문기반 미세먼지 빅데이터분석, 한국환경정책평가원, 2019.3~2019.12.
질문기반 기후변화 빅데이터분석, 한국환경정책평가원, 2020.3~2020.12.
텍스트 분석을 통한 고용정책 프레임 분석, 서울대학교 빅데이터연구소, 2019.1~2019.12

유재준자연과학대학 물리천문학부

  • 연구실/전공분야응집물질물리이론
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence
  • 연구분야(X+AI)Energy, Physics

대표논문

"Passivated co-doping approach to bandgap narrowing of titanium dioxide with enhanced photocatalytic activity”, Applied Catalysis B: Environmental 200, 1 (2017)
"Novel J eff= 1/2 Mott state induced by relativistic spin-orbit coupling in Sr2IrO4”, Physical Review Letters 101, 076402 (2008)
"O(N) LDA+U electronic structure calculation method based on the nonorthogonal pseudoatomic orbital basis”, Physical Review B 73, 045110 (2006)
"Magnetic ordering at the edges of graphitic fragments: Magnetic tail interactions between the edge-localized states”, Physical Review B 72, 174431 (2005)
"Electronically Driven Instabilities and Superconductivity in the Layered La2-xMxCuO4 Perovskites", Physical Review Letters 58, 1035 (1987)
"Center for Strongly Correlated Materials Research (SRC)", 한국연구재단, 1999-2008

조정효사범대학 물리교육과

  • 연구실/전공분야통계물리, 데이터사이언스, 기계학습, 계산생물학, 융합과학과 교육
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence
  • 연구분야(X+AI)Bio, Brain, Medicine

대표논문

Hoang DT, Song J, Periwal V, and Jo J. Network inference in stochastic systems from neurons to currencies: Improved performance at small sample size, Phys Rev E, 99:023311 (2019)
Song J, Marsili M, and Jo J. Resolution and relevance trade-offs in deep learning, Journal of Statistical Mechanics, 12:123406 (2018)
Hoang DT, Jo J and Periwal V. Data-driven inference of hidden nodes in networks, Phys Rev E, 99:042114 (2019)
Cubero RJ, Jo J, Marsili M, Roudi Y and Song J. Statistical criticality arises in most informative representations, Journal of Statistical Mechanics, 6:063402 (2019)
Xu J and Jo J. Immunological recognition by articial neural networks, Journal of Korean Physical Society, 73:1908-1917 (2018)
Dynamics Inference from Time Series Data, NRF, 2019.06.01 - 2022.02.28

정성규자연과학대학 통계학과

  • 연구실/전공분야통계적학습이론 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, Data Intelligence
  • 연구분야(X+AI)Bio, Humanities/Social Sciences, Brain, Medicine

대표논문

Sungkyu Jung, Myung Hee Lee and Jeongyoun Ahn (2018). “On the number of principal components in high dimensions,” Biometrika 105(2), 389-402.
Sungkyu Jung, Jeongyoun Ahn, and Yongho Jeon (2019). “Penalized Orthogonal Iteration for Sparse Estimation of Generalized Eigenvalue Problem” Journal of Computational and Graphical Statistics. 28(3) 710-721.
Gen Li and Sungkyu Jung (2017). “Incorporating Covariates into Integrated Factor Analysis of Multi-View Data,” Biometrics 73 (4), 1433-1442.
Byungwon Kim, Stephan Huckemann, Joern Schulz, and Sungkyu Jung (2019). “Small sphere distributions for directional data with application to medical imaging”, Scandinavian Journal of Statistics. 46(4) 1047-1071.