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

한국거래소의 초단위 거래자료 빅데이터를 분석하여 외환위기 당시 외국인 투자자의 영향을 자세히 분석한 논문을 재무금융 분야 세계 톱저널인 Journal of Financial Economics (Vol. 54, No. 2, 1999)에 게재함으로써, 한국거래소 거래자료 이터를 분석한 최초의 논문으로서 한국거래소를 전세계에 널리 알리는 쾌거를 이루었음.
전세계 주식수익률 빅데이터를 분석하여 각국 주식수익률 결정의 공통적인 팩터와 전세계의 공통적인 팩터가 어떻게 다른지를 분석하여 자산가격결정 분야에서 팩터모형의 새로운 연구방향을 제시하는 기여를 하였으며, 해당 논문은  재무금융 분야 세계 톱저널인 Review of Financial Studies (Vol. 24, No. 8, 2011)에 게재하였음.
과제명: 극단적 주식수익률의 반전현상과 복권성향의 투자행태에 관한 연구
연구비 지원기관: 한국연구재단 일반공동연구
연구수행 기간: 2014.12.01~2015.11.30
과제명: Do Domestic Investors Have an Edge? The Trading Experience of Foreign Investors in Korea
연구비 지원기관: 한국학술진흥재단 국제협동연구(우수연구성과 사례로 사후 선정됨)
연구수행 기간: 2004.12.01~2005.11.30

인공지능과 시장경쟁 : 데이터에 대한 규율을 중심으로 한국경제포럼  공동  201910
인공지능과 고용차별의 법경제학, 법경제학연구 한국경제법학회  공동  201904
인공지능과 차별 저스티스 한국법학원 공동  201904

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.

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

인슈어테크 혁명: 현황 점검 및 과제 고찰

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

Heewoong Park and Jonghun Park, "Assessment of Word-Level Neural Language Models for Sentence Completion", Applied Sciences, Vol. 10, No. 4, Feb 2020
In-Beom Park, Jaeseok Huh, Joongkyun Kim, and Jonghun Park, "A Reinforcement Learning Approach to Robust Scheduling of Semiconductor Manufacturing Facilities", to appear in IEEE Transactions on Automation Science and Engineering, 2020
Jonggwon Park, Kyoyun Choi, Sungwook Jeon, Dokyun Kim and Jonghun Park, "A Bi-directional Transformer for Musical Chord Recognition", to appear in Proc. of the 20th International Society for Music Information Retrieval Conference (ISMIR) 2019, Delft, Netherlands
Heewoong Park, Sukhyun Cho, Kyubyong Park, Namju Kim, and Jonghun Park, "TRAINING UTTERANCE-LEVEL EMBEDDING NETWORKS FOR SPEAKER IDENTIFICATION AND VERIFICATION", Proc. of InterSpeech 2018
Moon-jung Chae, Kyubyong Park, Jinhyun Bang, Soobin Suh, Jonghyuk Park, Namju Kim, and Jonghun Park, "CONVOLUTIONAL SEQUENCE TO SEQUENCE MODEL WITH NON-SEQUENTIAL GREEDY DECODING FOR GRAPHEME TO PHONEME CONVERSION", Proc. of ICASSP 2018
신경망 구조 탐색을 위한 메타러닝 기법 및 생성형 모형 기반 이상치 탐지 기술 연구, 카카오브레인, 2019.04.01~2020.03.31
잠재공간의 효과적 제어를 통한 심층신경망의 시퀀스 데이터 생성 기법 연구, 한국연구재단, 2019.6.1 - 2022.5.31
Deep Reinforcement Learning을 활용한 지능형 Real-Time Scheduling/Dispatching, 뉴로코어, 2019. 6. - 2019.11.

“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.

Hawkware: Network Intrusion Detection based on Behavior Analysis with ANNs on an IoT Device, Design Automation Conference (DAC), Jul 2020
DADE: a fast data anomaly detection engine for kernel integrity monitoring, The Journal of Supercomputing, Aug 2019
Real-Time Anomalous Branch Behavior Detection with a GPU-inspired Engine for Machine Learning Models, Design Automation and Test in Europe (DATE), Mar 2019
An SoC Architecture for Learning-Based Online Anomaly Detection on ARM, Design Automation Conference (DAC) WIP, Jun 2018
Mimicry Resilient Program Behavior Modeling with LSTM based Branch Models, DEEP LEARNING AND SECURITY WORKSHOP, May 2018
Behavior-based Malware Detection in HW support, 1억, 삼성전자
AI 포렌식 빅데이터 기반 지능형 보안 위협 분석, 8500만, 서울특별시
Embedded 시스템에서의 (AI 기반) 공격탐지 및 데이터 전송 솔루션, 1억, 삼성전자

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

Learning Discrete and Continuous Factors of Data via Alternating Disentanglement (ICML19)
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization (ICML19)
EMI: Exploration with Mutual Information (ICML19)
End-to-End Efficient Representation Learning via Cascading Combinatorial Optimization (CVPR19)
[뉴럴 프로세싱 시스템 연구/16세부]Deep adversarial reinforcement learning via expert video demonstrations, 삼성전자(주)/민간지원사업, 2017-2020
머신러닝 기반 Storage 품질 예측 시스템의 향상을 위한 최적화기반 data augmentation 방법에 관한 연구, 삼성전자(주)/민간지원사업, 2019-2024
데이터간 범용적인 상호 유사성 추론을 위한 딥러닝 모형 연구, 과학기술정보통신부/이공분야기초연구사업전략공모사업, 2017-2020

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.

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

Subsidies for Illegal Activities? - Reframing IUU Fishing from the Law Enforcement Perspective JOURNAL OF INTERNATIONAL ECONOMIC LAW  단독  201906
Two bites at the same apple? ‘derivative’ ISDS proceedings in the revised Korea-US FTA JOURNAL OF EAST ASIA AND INTERNATIONAL LAW  단독  201903
TRADE AGREEMENTS' NEW FRONTIER-REGULATION OF STATE-OWNED ENTERPRISES AND OUTSTANDING SYSTEMIC CHALLENGES ASIAN JOURNAL OF WTO & INTERNATIONAL HEALTH LAW AND POLICY  단독  201903

Jaeyong Lee and Steven N. MacEachern. (2020). A New Proof of the Stick-Breaking Construction of Dirichlet Processes. JKSS.
Kyoungjae Lee, Jaeyong Lee and Lizhen Lin. (2019.12) Minimax Posterior Convergence Rates and Model Selection Consistency in High-dimensional DAG Models based on Sparse Cholesky Factors. Annals of Statistics, 47(6), 3413-3437.
Kyoungjae Lee and Jaeyong Lee.(2018).  Optimal Bayesian Minimax Rates for Unconstrained Large Covariance Matrices. Bayesian Analysis, 13(4), 1215-1233.
Seongil Jo, Jaeyong Lee, Peter Muller, Fernando A. Quintana & Lorenzo Trippa. (2017). Dependent Species Sampling Models for Spatial Density Estimation. Bayesian Analysis, 12(2), 379-406.
Sarat C. Dass, Jaeyong Lee, Kyoungjae Lee & Jonghun Park. (2017). Laplace based approximate posterior inference for differential equation models. Statistics and Computing, 27(3), 679-698.
인공지능과 빅데이터 분석을 위한 베이즈 추론의 수학적 기반 이론 연구. 과학기술정보통신부. 2018.09.01-2023.08.31.
신뢰도 검사시 불량발생 리스크, 추가 샘플링 확보에 따른 리스크 감소 대책 등에 대한 통계적 확률적 연구. 삼성전자. 2018.09.01-2023.08.31.
카드 거래 자료를 이용한 카드 고객 거래 패턴 분석. 코나아이(주). 2019.01.01-2019.05.31.

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

Numerical Method for Comparison on Homomorphically Encrypted Numbers, With Dongwoo Kim, Duhyeong Kim, Hunhee Lee and Keewoo Lee, Asiacrypt'19 (Invited to Journal of Cryptology)
Statistical Zeroizing Attack: Cryptanalysis of Candidates of BP Obfuscation over GGH15 Multilinear Map, With Wonhee Cho, Minki Hhan, Jiseung Kim and Changmin Lee, CRYPTO'19
Cryptanalyses of Branching Program Obfuscations over GGH13 Multilinear Map from the NTRU Problem, With Minki Hhan, Jiseung Kim and Changmin Lee, CRYPTO'18

The Role of Education Interventions in Improving Economic Rationality (with Hyuncheol Bryant Kim, Booyuel Kim, and Cristian Pop-Eleches). Science, 362(6410), 83-86. 2018.
Who Is (More) Rational? (with Shachar Kariv, Wieland Müller and Dan Silverman). American Economic Review, 105(6), 1518-1550. 2014.
Consistency and Heterogeneity of Individual Behavior under Uncertainty (with Raymond Fisman, Douglas Gale and Shachar Kariv). American Economic Review, 97(5), 1921-1938. 2007.
Trading in Networks: Theory and Experiment (with Andrea Galeotti and Sanjeev Goyal). Journal of the European Economic Association, 15(4), 784-817. 2017.
Estimating Ambiguity Aversion in a Portfolio Choice Experiment (with David Ahn, Douglas Gale, and Shachar Kariv). Quantitative Economics, 5(2), 195-223. 2014.

『우리의 지속가능한 에너지』 (2017) 임현묵 외, 유네스코한국위원회
『리더들이 꼭 알아야 할 에너지기술』 (2015) 차동형 외, 지오북
에너지 클라우드 기술의 가치평가시스템 구축, 한국연구재단 원천기술개발사업, 2019.06~2020.12