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)

“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.

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

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

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

"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

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

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

인공지능과 시장경쟁: 데이터에 대한 규율을 중심으로 한국경제포럼  공동(Book Chapter)  201910
Tech Wars: Return of the Conglomerate - Throwback or Dawn of a New Series for Competition in the Digital Era? Journal of Korean Law  단독  202002
경쟁자의 비용 증대를 통한 배제 전략의 경쟁법적 고찰 서울법학 서울시립대 법학연구소 단독  201902

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

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

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.

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~.

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

"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.

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