장병탁 공과대학 컴퓨터공학부

연구실/전공분야바이오인텔리전스 랩
연구분야(AI 원천기술)Learning & Reasoning,Brain & Mind,Language & Cognition,Language & Cognition
연구분야(X+AI)Humanities/Social Sciences,Bio,Brain

대표논문

Answerer in questioner's mind: Information theoretic approach to goal-oriented visual dialog, S.-W. Lee, Y.-J. Heo, B.-T. Zhang, The 32nd Annual Conference on Neural Information Processing Systems (NIPS 2018), (Spotlight)
Bilinear attention networks, J.-H. Kim, J. Jun, B.-T. Zhang, The 32nd Annual Conference on Neural Information Processing Systems (NIPS 2018)
Overcoming catastrophic forgetting by incremental moment matching, S.-W. Lee, J.-H. Kim, J. Jun, J.-W. Ha, and B.-T. Zhang, The 31st Annual Conference on Neural Information Processing Systems (NIPS 2017)
Multimodal residual learning for visual QA, J.-H. Kim, S.-W. Lee, D.-H. Kwak, M.-O. Heo, J. Kim, J.-W. Ha, and B.-T. Zhang, In The 30th Annual Conference on Neural Information Processing Systems (NIPS 2016)

박재흥 융합과학기술대학원 지능정보융합학과

연구실/전공분야동적 로봇 시스템 연구실
연구분야(AI 원천기술)Robotics & Action, Autonomous Driving
연구분야(X+AI)Arts, Medicine, Manufacturing

대표논문

김건희 공과대학 컴퓨터공학부

연구실/전공분야시각 및 학습 연구실
연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Language & Cognition
연구분야(X+AI)

대표논문

김현진 공과대학 항공우주공학과

연구실/전공분야자율로봇연구실
연구분야(AI 원천기술)Vision & Perception, Robotics & Action, Autonomous Driving
연구분야(X+AI)Logistics, Manufacturing

대표논문

Autonomous helicopter flight via reinforcement learning
HJ Kim, MI Jordan, S Sastry, AY Ng, Advances in neural information processing systems, 2004
Aerial manipulation using a quadrotor with a two dof robotic arm
S Kim, S Choi, HJ Kim
IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013
Real-time monocular image-based 6-DoF localization
H Lim, SN Sinha, MF Cohen, M Uyttendaele, HJ Kim
International Journal of Robotics Research 34 (4-5), 476-492, 2015
Learning Transformable and Plannable se(3) Features for Scene Imitation of a Mobile Service Robot
J Park, J Kim, Y Jang, I Jang, HJ Kim
IEEE Robotics and Automation Letters, 2020
Fast and safe policy adaptation via alignment-based transfer
Jigang Kim, Seungwon Choi, and H. Jin Kim
IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

곽노준 융합과학기술대학원 지능정보융합학과

연구실/전공분야컴퓨터지능 및 패턴인식 연구실
연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Multi-modal Learning
연구분야(X+AI)

대표논문

Jisoo Jeong, Seungeui Lee, Jeesoo Kim and Nojun Kwak, "Consistency-based Semi-supervised Learning for Object detection", Thirty-third Conference on Neural Information Processing Systems (NeurIPS2019), Vancouver, Canada, Dec. 2019.
Simyung Chang, SeongUk Park, John Yang and Nojun Kwak, "Sym-Parameterized Dynamic Inference for Mixed-Domain Image Translation, International Conference on Computer Vision (ICCV2019), Seoul, Korea, Oct. 2019
Simyung Chang, John Yang, Jaeseok Choi and Nojun Kwak, "Genetic-Gated Networks for Deep Reinforcement Learning", Thirty-second Conference on Neural Information Processing Systems (NeurIPS2018), Montreal, Canada, Dec. 2018.
Jangho Kim, SeoungUK Park and Nojun Kwak, "Paraphrasing Complex Network: Network Compression via Factor Transfer", Thirty-second Conference on Neural Information Processing Systems (NeurIPS2018), Montreal, Canada, Dec. 2018.
Daesik Kim, Youngjoon Yoo, Jeesoo Kim, Sangkuk Lee and Nojun Kwak, "Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams", The Thirtieth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2018), Salt Lake City, UT, June 2018.
Thinking Machine: 다중 감각간 관계 지식을 활용한 통합 사고 신경망 연구, 약 18억, 한국연구재단, 2017.11 - 2020.12

이교구 융합과학기술대학원 지능정보융합학과

연구실/전공분야Music and Audio Research Group
연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Language & Cognition
연구분야(X+AI)Arts, Brain

대표논문

Hyeong-Seok Choi, Changdae Park, and Kyogu Lee, “From Inference to Generation: End-to-end Fully Self-supervised Generation of Human Face from Speech”, to appear in Proceedings of International Conference on Learning epresentations (ICLR), 2020
Jie Hwan Lee, Hyeong-Seok Choi, and Kyogu Lee, “Audio query-based music source separation”, in Proceedings of International Society for Music Information Retrieval Conference (ISMIR), 2019
Juheon Lee, Hyeong-Seok Choi, Chang-bin Jeon, Junghyun Koo, and Kyogu Lee, “Adversarially Trained End-to-end Korean Singing Voice Synthesis System”, in Proceedings of Interspeech, 2019, Best Student Paper Award
Juheon Lee, Sungkyun Chang, Sangkeun Choe, and Kyogu Lee, “COVER SONG IDENTIFICATION USING SONG-TO-SONG CROSS-SIMILARITY MATRIX WITH CONVOLUTIONAL NEURAL NETWORK”, in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
Yoonchang Han, Jaehun Kim, Kyogu Lee, “Deep convolutional neural networks for predominant instrument recognition in polyphonic music”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 25(1), pp. 208-221, 2017
"자기회귀적 적대적 생성 신경망 기반의 가창 합성 및 평가 모델 연구", 미래창조과학부/전략과제, 2017.11.01~2020.10.31
"심상의 소리: 적대적 신경망을 활용한 크로스-모달 오디오 합성/변환 연구", 과학기술정보통신부/원천기술개발사업, 2017.11.01~2020.12.31
"뇌·인지 발달과정의 기초-영아단계 모사형 실세계 상호작용 경험 기반 객체 관련 개념의 기계학습 기술, 과학기술정보통신부/정보통신방송연구개발사업", 2019.04.01~2022.12.31

이재욱 공과대학 컴퓨터공학부

연구실/전공분야아키텍처 및 코드 최적화 연구실
연구분야(AI 원천기술)AI Platform, AI Chip
연구분야(X+AI)

대표논문

Tae Jun Ham, Seonghak Kim, and Sung Jun Jung, Young H. Oh, Yeonhong Park, Yoon Ho Song, Junghoon Park, Sanghee Lee, Kyoung Park, Jae W. Lee, and Deog-Kyoon Jeong, "A3: Accelerating Neural Network Attention Mechanism with Approximation", 26th IEEE International Symposium on High Performance Computer Architecture (HPCA), San Diego, California, February 2020.
Shine Kim, Jonghyun Bae, Hakbeom Jang, Wenjing Jin, Jeonghun Gong, Seungyeon Lee, Tae Jun Ham, and Jae W. Lee, "SSDStreamer: Specializing I/O Stack for Large-Scale Machine Learning", IEEE Micro, September/October 2019.
Young H. Oh, Quan Quan, Daeyeon Kim, Seonghak Kim, Jun Heo, Jaeyoung Jang, Sung Jun Jung, and Jae W. Lee, "A Portable, Automatic Data Quantizer for Deep Neural Networks", IEEE International Conference on Parallel Architectures and Compilation Techniques (PACT-27), Limassol, Cyprus, November 2018.
Channoh Kim, Jaehyeok Kim, Sungmin Kim, Dooyoung Kim, Namho Kim, Gitae Na, Young H. Oh, Hyeon Gyu Cho, and Jae W. Lee, "Typed Architectures: Architectural Support for Lightweight Scripting", 22nd ACM Architectural Support for Programming Languages and Operating Systems (ASPLOS), Xi'an, China, April 2017.
Doo Young Kim, Jin Min Kim, Hakbeom Jang, Jinkyu Jeong, and Jae W. Lee, "A Neural Network Accelerator for Mobile Application Processors", IEEE Transactions on Consumer Electronics, 61(4), November 2015.
NAND 플래시 기반 심층신경망 학습 시스템, 연구재단, 2020.3-2023.2
뉴럴 프로세싱 시스템 연구, 삼성전자, 2017.11-2020.10
Beyond Limit, 삼성전자, 2018.11-2021.10

윤성로 공과대학 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

유병준 경영대학 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

이유리 생활과학대학 의류학과

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

대표논문

이원종 융합과학기술대학원 지능정보융합학과

연구실/전공분야Applied Data Science Lab
연구분야(AI 원천기술)Learning & Reasoning
연구분야(X+AI)

대표논문

Choi, Daeyoung, and Wonjong Rhee. "Utilizing class information for deep network representation shaping." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 33. 2019.
Shin, Changho, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, and Wonjong Rhee. "Subtask gated networks for non-intrusive load monitoring." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 1150-1157. 2019.
Jung, Wonkyung, Daejin Jung, Sunjung Lee, Wonjong Rhee, and Jung Ho Ahn. "Restructuring batch normalization to accelerate CNN training." SysML (2018).
Yu, Wei, Wonjong Rhee, Stephen Boyd, and John M. Cioffi. "Iterative water-filling for Gaussian vector multiple-access channels." IEEE Transactions on Information Theory 50, no. 1 (2004): 145-152.
Rhee, Wonjong, and John M. Cioffi. "On the capacity of multiuser wireless channels with multiple antennas." IEEE Transactions on Information Theory 49, no. 10 (2003): 2580-2595.
정보이론 및 최적화이론을 활용한 딥러닝의 수학적 원리 및 응용 연구, 연구재단/중견, 2017.9~2020.8
최신 딥러닝 기법을 이용한 반도체 소자 모델링 기법 혁신, 하이닉스, 2019.3~2019.12
SKINET AutoML 구현을 위한 HPO (Hyper Parameter Optimization)및 NAS(Neural Architecture Search) 연구, SK Telecom, 2018.4~2018.12

이인아 자연과학대학 뇌인지과학과

연구실/전공분야Laboratory for Behavioral Neurophysiology of Memory
연구분야(AI 원천기술)Learning & Reasoning, Brain & Mind
연구분야(X+AI)

대표논문

Ahn JR, Lee HW, and Lee I (2019). Rhythmic pruning of perceptual noise for object representation in the hippocampus and perirhinal cortex in rats. Cell Reports 26
Jung MW, Lee H, Jeong Y, Lee JW, Lee I (2018). Remembering rewarding futures: A simulation‐selection model of the hippocampus. Hippocampus 28
Ahn JR, Lee I (2017) Neural correlates of both perception and memory for objects in the rodent perirhinal cortex. Cerebral Cortex 27
Lee I, Lee CH (2013) Contextual behavior and neural circuits. Frontiers in Neural Circuits 7
Lee I, Yoganarasimha D, Rao G, Knierim J (2004) Comparison of population coherence of place cells in hippocampal subfields CA1 and CA3. Nature 430

이재성 의과대학 핵의학교실

연구실/전공분야 핵의학 영상처리 / 정량 분석
연구분야(AI 원천기술)Vision & Perception
연구분야(X+AI)Bio, Brain, Medicine

대표논문

Generation of PET attenuation map for whole-body time-of-flight 18F-FDG PET/MRI using a deep neural network trained with simultaneously reconstructed activity and attenuation maps. J Nucl Med. 2019 Aug;60(8):1183-1189.
Improving the accuracy of simultaneously reconstructed activity and attenuation maps using deep learning. J Nucl Med. 2018 Oct;59(10):1624-1629.
Deep-dose: a voxel dose estimation method using deep convolutional neural network for personalized internal dosimetry. Sci Rep. 2019; 9:10308.
Measurement of glomerular filtration rate using quantitative SPECT/CT and deep-learning-based kidney segmentation. Sci Rep. 2019;9:4223.
r amyloid PET using a deep learning approach. Hum Brain Mapp. 2018 May 11;39(9):3769–3778.
뇌질환 임상연구를 위한 7T MR-Compatible PET System 개발, 과학기술
정보통신부, 2014.07 - 2019.04
차세대 초저선량 PET 시스템 핵심 기술 개발, 과학기술 정보통신부, 2016.06 - 2021.03

임용 법학전문대학원 법학과

연구실/전공분야경제법
연구분야(AI 원천기술)AI Law & Ethics
연구분야(X+AI)Humanities/Social Sciences, Commerce, Competition Policy

대표논문

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

임채영 자연과학대학 통계학과

연구실/전공분야공간통계학연구실
연구분야(AI 원천기술)Learning & Reasoning
연구분야(X+AI)Humanities/Social Sciences, Brain, Medicine

대표논문

차혁진 약학대학 약학과

연구실/전공분야Cell Signaling Laboratory
연구분야(AI 원천기술)Drug prediction, transcriptome analysis, Drug sensitivity prediction
연구분야(X+AI)Bio

대표논문

천현득 자연과학대학 과학학과

연구실/전공분야인공지능 ELSI 연구센터
연구분야(AI 원천기술)AI Law & Ethics,Learning & Reasoning,Human-AI Interaction
연구분야(X+AI)Humanities/Social Sciences

대표논문

- E. Machery, C. Y. Olivola, H. Cheon, I. T. Kurniawan, C. Mauro, N. Struchiner, and H. Susianto, (Forthcoming.) “Is Identity Essentialism a Fundamental Feature of Human Cognition?” Cognitive Science.
- 이한슬, 천현득 (2023). 「알고리듬 투명성을 이해하기」, 『과학철학』 26(1): 31-58.
- Cheon, H. (2022). "A new direction for global epistemology", Metascience 31(2), 195-198
- 이한슬, 천현득 (2021). 「인공지능 윤리에서 해명가능성 원리」, 『인문학연구』 35집: 37-63.
- 천현득 (2020). 「지각의 인지적 침투와 관찰의 이론적재성」, 『과학철학』 23(1): 75-107.
- 천현득 (2019). 「인공 반려의 유혹: 인공물과의 교감을 생각한다」, 『과학철학』 22(2): 27-52.
- 천현득 (2019). 「인공지능의 존재론: 이미 도래했으나 아직 실현되지 않은 존재를 사유하기」, 『쓺-문학의 이름으로』 8집: 7-25.
- 천현득 (2019). 「"킬러 로봇"을 넘어: 자율적 군사로봇의 윤리적 문제들」, Trans-Humanities 12(2): 5-31.
- 천현득 (2017). 「인공 지능에서 인공 감정으로: 감정을 가진 기계는 실현가능한가?」, 『철학』 131: 217-243.
- Cheon, H. and E. Machery, (2016). “Scientific Concepts”, Oxford Handbook for the Philosophy of Science (ed. by Paul Humphreys)

홍진호 인문대학 독어독문학과

연구실/전공분야자연주의/세기전환기 독일어권 문학 및 문화, 환상문학, 독일공연예술
연구분야(AI 원천기술)Language & Cognition
연구분야(X+AI)Humanities/Social Sciences

대표논문

19세기 말부터 20세기 초의 독일어권 문학. 새로운 인간관과 세계관을 바탕으로 발달한 자연주의의 혁신적인 문학과 세기전환기의 독특한 문화적 흐름 속에서 형성된 다양한 문학적 양상이 주요 관심 분야이다. 특히 게르하르트 하우프트만, 아르노 홀츠, 에두아르트 폰 카이절링, 아르투어 슈니츨러 등의 작가들을 주요 연구대상으로 삼고 있다. 더불어 19세기 말부터 20세기 초반에 독일어권에서 발달한 환상문학(프란츠 카프카, 구스타프 마이링크, 알프레드 쿠빈 등)과 이를 분석하고 이해하기 위한 이론적 연구에도 관심을 기울이고 있으며, 독일 공연예술과 공연예술 이론에 대한 연구도 진행하고 있다.

강유 공과대학 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

김선 공과대학 컴퓨터공학부

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)

김아영 공과대학 기계공학부

연구실/전공분야로봇 인식 및 공간 지능 연구실
연구분야(AI 원천기술)Vision & Perception,Autonomous Driving,Robotics & Action
연구분야(X+AI)Manufacturing

대표논문

Giseop Kim, Sunwook Choi and Ayoung Kim, Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments. IEEE Transactions on Robotics, 2021.
Joowan Kim, Younggun Cho and Ayoung Kim, Proactive Camera Attribute Control using Bayesian Optimization for Illumination-Resilient Visual Navigation. IEEE Transactions on Robotics, 36(4):1256-1271, 2020
Jinyong Jeong, Younggun Cho, Young-Sik Shin, Hyunchul Roh and Ayoung Kim, Complex Urban Dataset with Multi-level Sensors from Highly Diverse Urban Environments. International Journal of Robotics Research, 38(6):642-657, 2019.

김용대 자연과학대학 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.

문태섭 공과대학 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

박건웅 자연과학대학 통계학과

연구실/전공분야
연구분야(AI 원천기술)
연구분야(X+AI)

대표논문

박종우 공과대학 기계공학부

연구실/전공분야로봇 자동화 실험실
연구분야(AI 원천기술)Learning & Reasoning, Robotics & Action, Mathematical data science
연구분야(X+AI)Medicine, Logistics, Manufacturing, Dental and medical imaging

대표논문

서봉원 융합과학기술대학원 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

서진욱 공과대학 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.

손석우 자연과학대학 지구환경과학부

연구실/전공분야날씨/기후역학실험실
연구분야(AI 원천기술)
연구분야(X+AI)

대표논문

송현오 공과대학 컴퓨터공학부

연구실/전공분야머신러닝 연구실
연구분야(AI 원천기술)Learning & Reasoning, Robotics & Action, AI Security
연구분야(X+AI)Medicine, Finance

대표논문

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

안정호 융합과학기술대학원 지능정보융합학과

연구실/전공분야SCALable Computer Architecture Laboratory
연구분야(AI 원천기술)AI Platform, AI Chip
연구분야(X+AI)

대표논문

"Partitioning Compute Units in CNN Acceleration for Statistical Memory Traffic Shaping," D. Jung, S. Lee, W. Rhee, and J. Ahn, IEEE Computer Architecture Letters, Vol. 17, No. 1, 2018
뉴럴 프로세싱 시스템 연구, 삼성전자, 2017/11-2020/10
복합 심층학습 응용분야를 위한 가속기 구조 연구, 삼성미래기술육성재단, 2017/12-2019/11

양인순 공과대학 전기정보공학부

연구실/전공분야Stochastic Control, Optimization, Reinforcement Learning
연구분야(AI 원천기술)
연구분야(X+AI)

대표논문

유승주 공과대학 컴퓨터공학부

연구실/전공분야컴퓨터 구조 메모리 연구소
연구분야(AI 원천기술)AI Platform
연구분야(X+AI)

대표논문

이경무 공과대학 전기정보공학부

연구실/전공분야컴퓨터 비전 연구실
연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Autonomous Driving
연구분야(X+AI)Bio, Medicine, Logistics, Manufacturing

대표논문

이상구 공과대학 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~.

이영기 공과대학 컴퓨터공학부

연구실/전공분야인간 중심 컴퓨터 시스템 연구실
연구분야(AI 원천기술)AI Platform, Human-AI Interaction
연구분야(X+AI)Humanities/Social Sciences, Commerce, Healthcare, Education

대표논문

전동석 융합과학기술대학원 지능정보융합학과

연구실/전공분야Mobile Multimedia Systems Group
연구분야(AI 원천기술)AI Platform, AI Chip
연구분야(X+AI)Bio, Brain

대표논문

J. Park, J. Lee, and D. Jeon, “A 65-nm Neuromorphic Image Classification Processor With Energy-Efficient Training Through Direct Spike-Only Feedback,” IEEE Journal of Solid-State Circuits (JSSC), 2020.
S. Moon, K. Shin, and D. Jeon, “Enhancing Reliability of Analog Neural Network Processors,” IEEE Transactions on VLSI Systems (TVLSI), 2019.
J. Park, Y. Kwon, Y. Park, and D. Jeon, “Microarchitecture-Aware Code Generation for Deep Learning on Single-ISA Heterogeneous Multi-Core Mobile Processors,” IEEE Access, 2019.
D. Jeon, Q. Dong, Y. Kim, X. Wang, S. Chen, H. Yu, D. Blaauw, and D. Sylvester, “A 23-mW Face Recognition Processor with Mostly-Read 5T Memory in 40-nm CMOS,” IEEE Journal of Solid-State Circuits (JSSC), 2017.
D. Jeon, N. Ickes, P. Raina, H.-C. Wang, and A. P. Chandrakasan, “A 0.6V, 8mW 3D Vision Processor for a Navigation Device for the Visually Impaired,” IEEE International Solid-State Circuits Conference (ISSCC), 2016.
자가 학습이 가능한 초저전력 혼성신호 뉴로모픽 프로세서 설계, 과학기술정보통신부, 2019~2022.
고효율 딥러닝 하드웨어 가속기 개발, 한국과학기술연구원, 2019~2021.
모바일 시스템을 위한 저전력 머신 러닝 하드웨어 가속기 개발, 과학기술정보통신부, 2016~2019.

전병곤 공과대학 컴퓨터공학부

연구실/전공분야소프트웨어 플랫폼 연구실
연구분야(AI 원천기술)Learning & Reasoning, AI Platform, AI Chip
연구분야(X+AI)

대표논문

Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs. NSDI 2019.
Parallax: Sparsity-aware Data Parallel Training of Deep Neural Networks. EuroSys 2019.
Apache Nemo: A Framework for Building Distributed Dataflow Optimization Policies. ATC 2019.
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems. OSDI 2018.
Improving the Expressiveness of Deep Learning Frameworks with Recursion. EuroSys 2018.
(SW 스타랩) 다양한 분석을 고속 수행하는 단일화된 빅데이터 스택 개발
[뉴럴 프로세싱 시스템 연구/17세부] 대규모 클러스터에서 딥러닝 학습을 자동 분산하는 시스템
비디오 튜링 테스트를 통과할 수준의 비디오 스토리 이해 기반의 질의응답 기술 개발

정교민 공과대학 전기정보공학부

연구실/전공분야머신 인텔리전스 연구실
연구분야(AI 원천기술)Learning & Reasoning, Language & Cognition
연구분야(X+AI)

대표논문

Hyeongu Yun, Yongkeun Hwang and Kyomin Jung, Improving Context-Aware Neural Machine Translation Using Self-Attentive Sentence Embedding , AAAI Conference on Artificial Intelligence (AAAI), Jan 2020, New York City, New York, USA
Hyoungwook Nam, Segwang Kim, Kyomin Jung, Number Sequence Prediction Problems and Computational Powers of Neural Network Models , AAAI Conference on Artificial Intelligence (AAAI)- (Oral), Jan 2019, Honolulu, Hawaii, USA
Seunghyun Yoon, Joongbo Shin, Kyomin Jung, Learning to Rank Question-Answer Pairs using Hierarchical Recurrent Encoder with Latent Topic Clustering , Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), June 2018, New Orleans, LA, USA
논리적 추론을 위한 딥러닝 아키텍쳐 개발, 삼성전자 미래기술육성센터, 2019-2022
대화 상황과 감정 인지형 인공지능 대화 시스템 개발, KEIT, 2017-2022

조성준 공과대학 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

주한별 공과대학 컴퓨터공학부

연구실/전공분야비주얼 컴퓨팅 연구실
연구분야(AI 원천기술)Learning & Reasoning,Vision & Perception,Robotics & Action
연구분야(X+AI)

대표논문

BANMo: Building Animatable 3D Neural Models from Many Casual Videos, CVPR 2022
PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization.CVPR 2020
Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction in A Triadic Interaction, CVPR 2019
Panoptic Studio: A Massively Multiview System for Social Interaction Capture, TPAMI 2019
Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies, CVPR 2018

차지욱 사회과학대학 심리학과

연구실/전공분야커넥톰연구실/신경과학
연구분야(AI 원천기술)Learning & Reasoning, Brain & Mind
연구분야(X+AI)Neuroscience, Bio, Humanities/Social Sciences, Medicine,Brain

대표논문

"The sexual brain, genes, and cognition: A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children." Human Brain Mapping
"Association of Genome-wide Polygenic Scores for Multiple Psychiatric and Common Traits Identify Preadolescent Youth with Risk for Suicide." JAMA Network Open
"Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth." Human Brain Mapping
"Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data." NPJ Digital Medicine
"Diagnosis and prognosis of Alzheimer's disease using brain morphometry and white matter connectomes." Neuroimage-Clinical
"Associations between brain structure and connectivity in infants and exposure to selective serotonin reuptake inhibitors during pregnancy. " JAMA pediatrics
"The Effects of Obstructive Sleep Apnea Syndrome on the Dentate Gyrus and Learning and Memory in Children.'" The Journal of Neuroscience
"Clinically anxious individuals show disrupted feedback between inferior frontal gyrus and prefrontal-limbic control circuit." Journal of Neuroscience
"Neural correlates of aggression in medication-naive children with ADHD: multivariate analysis of morphometry and tractography." Neuropsychopharmacology
"Hyper-reactive human ventral tegmental area and aberrant mesocorticolimbic connectivity in overgeneralization of fear in generalized anxiety disorder." Journal of Neuroscience
"Circuit-wide structural and functional measures predict ventromedial prefrontal cortex fear generalization: implications for generalized anxiety disorder." Journal of Neuroscience

최진영 공과대학 전기정보공학부

연구실/전공분야인지지능 연구실
연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception
연구분야(X+AI)security, visual surveillance

대표논문

Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning, CVPR 2017
A Comprehensive Overhaul of Feature Distillation, ICCV 2019
Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning, ICCV 2019
Associative Variational Auto-encoder with Distributed Latent Spaces and Associators, AAAI 2020
Context-aware Deep Feature Compression for High-speed Visual Tracking, CVPR 2018
예지형 시각 지능 원천 기술 개발, 과학기술정보통신부, 2014. 4. 1 ~ 2024. 2. 29
Thinking Machine: 다중 감각 심층 신경망 기반 연상 작용의 실현 및 영상 생성 연구, 과학기술정보통신부, 2017. 09. 01 - 2020. 12. 31
실외 무인 경비 로봇을 위한 멀티모달 지능형 정보분석 기술 개발, 과학기술정보통신부, 2017. 04. 01 ~ 2021. 12. 31

하순회 공과대학 컴퓨터공학부

연구실/전공분야통합설계 및 병렬 처리 연구실
연구분야(AI 원천기술)AI Platform, AI Chip
연구분야(X+AI)embedded systems, electronic systems

대표논문

" Tensor Virtualization Technique to Support Efficient Data Reorganization for CNN Accelerators," DAC 2020 (to appear)
"A Novel CNN(Convolutional Neural Network) Accelerator That Enables Fully-pipelined Execution of Layers," ICCD 2019
"Fast Performance Estimation and Design Space Exploration of Manycore-based Neural Processors," DAC 2019
"C-GOOD: C-code Generation Framework for Optimized On-device Deep Learning," ICCAD 2018
"Joint Optimization of Speed, Accuracy, and Energy for Embedded Image Recognition Systems," DATE 2018
단말용 뉴럴 프로세서 시뮬레이션 및 소프트웨어 최적화 기술, 삼성종합기술원, 2016. 12 - 2020. 10
MIDAP (Memory-In-the DAtapath Processor) 뉴럴 프로세서의 성능 개선 연구, 삼성전자, 2018.5 - 2020.4
이종 하드웨어 가속기를 포함하는 모바일 플랫폼을 위한 시스템 수준의 딥 러닝 추론 최적화 기법, 삼성전자, 2018.3 - 2018.12

한보형 공과대학 전기정보공학부

연구실/전공분야컴퓨터 비전 연구실
연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Language & Cognition
연구분야(X+AI)

대표논문

Hyeonwoo Noh, Seunghoon Hong, Bohyung Han: Learning Deconvolution Network for Semantic Segmentation. ICCV 2015
Hyeonseob Nam, Bohyung Han: Learning multi-domain convolutional neural networks for visual tracking. CVPR 2016
Hyeonwoo Noh, Andre Araujo, Jack Sim, Tobias Weyand, Bohyung Han: Large scale image retrieval with attentive deep local features. ICCV 2017
Paul Hongseok Seo, Geeho Kim, Bohyung Han: Combinatorial Inference against Label Noise. NeurIPS 2019
Minsoo Kang, Jonghwan Mun, Bohyung Han: Towards Oracle Knowledge Distillation with Neural Architecture Search. AAAI 2020
Distributed Combinatorial Deep Learning. Google AI Focused Research Award
Privacy Preserving Semantic Image Compression. Kakao Brain
Neural Processing Research Center (대규모 인공 신경망에서의 학습 및 추론 알고리즘 개발), SAIT

황대희 자연과학대학 생명과학부

연구실/전공분야시스템 메디슨 실험실
연구분야(AI 원천기술)Learning & Reasoning
연구분야(X+AI)Bio, Medicine

대표논문

황승원 공과대학 컴퓨터공학부

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

대표논문

https://seungwonh.github.io/

177

강재승 의과대학 해부학교실

연구실/전공분야세포및분자생물학
연구분야(AI 원천기술)Human-AI Interaction
연구분야(X+AI)Brain, Medicine, Pharma

대표논문

176

강형진 의과대학 소아과학교실

연구실/전공분야분자종양학
연구분야(AI 원천기술)
연구분야(X+AI)

대표논문

175

고길곤 행정대학원 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

174

고봉찬 경영대학 경영학과

연구실/전공분야Investments, Asset Pricing, Corporate Finance, and Derivatives
연구분야(AI 원천기술)
연구분야(X+AI)Humanities/Social Sciences, Finance, Commerce

대표논문

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

173

고학수 법학전문대학원 법학과

연구실/전공분야개인정보보호의 법경제학/IT 정책의 법경제학/계약협상
연구분야(AI 원천기술)AI Law & Ethics
연구분야(X+AI)Humanities/Social Sciences, Medicine, Finance

대표논문

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

172

고형석 공과대학 전기정보공학부

연구실/전공분야그래픽스 및 미디어 연구실
연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception
연구분야(X+AI)Manufacturing

대표논문

Wonseop Lee, Hyeong-Seok Ko. Heuristic misfit reduction: A programmable approach for 3D garment fit customization. Computer & Graphics, 71, 1-13.
Dong-Hoon Han, Ick-Hoon Cha, Kyung-Hyun Lee and Hyeong-Seok Ko. Garment Preconditioning and Regional Simulation Omission for Trying-On Virtual Ensembles. Computer Animation and Social Agents 2019.
Goanghun Kim and Hyeong-Seok Ko. A Practical Approach to Physically‐Based Reproduction of Diffusive Cosmetics. Computer Graphics Forum. Volume 37, Number 7.
CCTV 영상으로부터 3D 모델과 딥러닝 및 이미지 품질 개선 기술을 활용한 정면 얼굴 복원 기술 개발, 과학기술정보통신부, 2018~2023.
의류 직물의 3D 재현 연구. 한국연구재단. 2012~2015.
증강현실 기술을 이용한 실시간 매직미러 서비스 기술개발. 정보통신산업진흥원. 2012~2014.

171

국웅 자연과학대학 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

170

권일웅 행정대학원 행정학과

연구실/전공분야조직경제학, 산업조직론, 노동경제학
연구분야(AI 원천기술)AI and Labor Force
연구분야(X+AI)Humanities/Social Sciences, Government Policy and Regulation

대표논문

"Trust or Distrust: Entrepreneurs vs. Self-Employed" (with Kitae Sohn), Small Business Economics, forthcoming.
"Public-Private Mixed Delivery and Information Effects" (with Sangin Park), Economica, 2018, 85(337), 75-91.
"What Does CEOs' Pay-for-Performance Reveal About Shareholders' Attitude Toward Earnings Overstatements?" (with Katherine Guthrie and Jan Sokolowsky), Journal of Business Ethics, 2017, 146(2), 419-450.
"Job Dissatisfaction of the Self-Employed in Indonesia" (with Kitae Sohn), Small Business Economics, 2017, 49(1), 233-249.
"The Effect of Public Service Motivation and Job Level on Bureaucrats' Preference for Direct Policy Instruments" (with Miyeon Song, Seyoung Cha, Naon Min), Journal of Public Administration Research and Theory, 2017, 27(1), 36-51.

169

권준수 자연과학대학 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

168

권태경 공과대학 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

167

김경환 의과대학 흉부외과학교실

연구실/전공분야흉부외과학
연구분야(AI 원천기술)
연구분야(X+AI)Medicine

대표논문

166

김기현 인문대학 철학과

연구실/전공분야분석철학, 심리철학, 현대 인식론
연구분야(AI 원천기술)AI Law & Ethics
연구분야(X+AI)Humanities/Social Sciences

대표논문

165

김도헌 자연과학대학 물리천문학부

연구실/전공분야Laboratory for integrated quantum systems
연구분야(AI 원천기술)
연구분야(X+AI)Physics

대표논문

164

김동규 공과대학 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

163

김명수 공과대학 컴퓨터공학부

연구실/전공분야3차원 모델링 및 처리 연구실
연구분야(AI 원천기술)Robotics & Action
연구분야(X+AI)Medicine, Manufacturing

대표논문

162

김선진 사범대학 체육교육과

연구실/전공분야운동 학습 및 발달, 제어
연구분야(AI 원천기술)
연구분야(X+AI)

대표논문

161

김유겸 사범대학 체육교육과

연구실/전공분야Health Behavior&Promotion / 스포츠 조직 / 스포츠마케팅
연구분야(AI 원천기술)Learning & Reasoning, Language & Cognition, AI Law & Ethics
연구분야(X+AI)Humanities/Social Sciences

대표논문

160

김장우 공과대학 전기정보공학부

연구실/전공분야고성능 컴퓨터 시스템 연구실
연구분야(AI 원천기술)AI Platform, AI Chip
연구분야(X+AI)Brain, Medicine, Energy

대표논문

"FlexLearn: Fast and Highly Efficient Brain Simulations Using Flexible On-Chip Learning", Eunjin Baek, Hunjun Lee, Youngsok Kim, and Jangwoo Kim, ACM/IEEE International Symposium on Microarchitecture (MICRO), Oct 2019
"MnnFast: A Fast and Scalable System Architecture for Memory-Augmented Neural Networks", Hanhwi Jang, Joonsung Kim, Jae-Eon Jo, Jaewon Lee, and Jangwoo Kim, ACM/IEEE International Symposium on Computer Architecture (ISCA), Jun 2019
"Flexon: A Flexible Digital Neuron for Efficient Spiking Neural Network Simulations"
Dayeol Lee, Gwangmu Lee, Dongup Kwon, Sunghwa Lee, Youngsok Kim, and Jangwoo Kim, ACM/IEEE International Symposium on Computer Architecture (ISCA), Jun 2018
"μLayer: Low Latency On-Device Inference Using Cooperative Single-Layer Acceleration and Processor-Friendly Quantization", Youngsok Kim, Joonsung Kim, Dongju Chae, Daehyun Kim, and Jangwoo Kim, ACM European Conference on Computer Systems (EuroSys), Mar 2019
"FIDR: A Scalable Storage System for Fine-Grain Inline Data Reduction with Efficient Memory Handling", Mohammadamin Ajdari, Wonsik Lee, Pyeongsu Park, Joonsung Kim, and Jangwoo Kim, ACM/IEEE International Symposium on Microarchitecture (MICRO), Oct 2019
인공지능 가상머신: 이종 인공지능의 동시, 고속, 독립 실행을 위한 컴퓨터 구조/삼성미래기술육성사업/2019.6-2022.5
이종 스파이크 뉴런 기반의 인간 두뇌 규모 시뮬레이션을 위한 프로세서 및 시스템 개발/한국연구재단/2017.3-2021.2
대규모 뉴럴 프로세싱을 위한 FPGA 기반의 확장형 시스템 개발/삼성전자/2017.11-2020.10

159

김정훈 의과대학 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

158

김주한 의과대학 의과학과

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

대표논문

157

김준범 경영대학 경영학과

연구실/전공분야Marketing Management, Digital Marketing, Data-Driven Marketing
연구분야(AI 원천기술)
연구분야(X+AI)Humanities/Social Sciences, Business/Marketing/Management

대표논문

im, Paulo Albuquerque, and Bart J. Bronnenberg (2017), “The Probit Choice Model under Sequential Search with an Application to Online Retailing,” Management Science, 63(11), 3911-3929.
Bronnenberg, Bart. J., Jun B. Kim, and Carl F. Mela (2016). “Zooming in on Choice: How do Consumers Search for Cameras Online?” Marketing Science, 35(5), 693-712.
Jiao Xu, Chris Forman, Jun B. Kim, and Koert Van Ittersum (2014), “News Media Platforms: Complements or Substitutes? The Case of Mobile News,” Journal of Marketing, 78:4 (July), 97-112
Jun B. Kim, Paulo Albuquerque, and Bart J. Bronnenberg (2011), “Modeling Online Consumer Search,” Journal of Marketing Research, 48:1 (February), 13-27

156

김지홍 공과대학 컴퓨터공학부

연구실/전공분야
연구분야(AI 원천기술)
연구분야(X+AI)

대표논문

155

김진수 공과대학 컴퓨터공학부

연구실/전공분야시스템 소프트웨어 및 구조 연구실
연구분야(AI 원천기술)AI Platform, AI Chip
연구분야(X+AI)

대표논문

154

김청택 사회과학대학 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.

153

김치헌 의과대학 신경외과학교실

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

대표논문

152

김태완 공과대학 조선해양공학과

연구실/전공분야Computer Aided Design and Information Technology Lab
연구분야(AI 원천기술)Learning & Reasoning, Robotics & Action, Autonomous Driving
연구분야(X+AI)Finance, Logistics, Manufacturing

대표논문

151

김태현 공과대학 컴퓨터공학부

연구실/전공분야양자정보 및 양자컴퓨팅 연구실
연구분야(AI 원천기술)Quantum AI
연구분야(X+AI)

대표논문

150

김현섭 인문대학 철학과

연구실/전공분야윤리학, 정치철학, 법철학
연구분야(AI 원천기술)Human-AI Interaction, AI Law & Ethics, Autonomous Driving
연구분야(X+AI)Humanities/Social Sciences

대표논문

기술적, 의학적, 윤리적, 법적 관점에서 바라본 인공지능의 책임성 (교육부, 2019.7부터 진행중)
자율주행자동차에 대한 융합연구토대마련 (서울대학교, 2016)

149

김현진 의과대학 의과학과

연구실/전공분야생체자기공명연구실
연구분야(AI 원천기술)
연구분야(X+AI)Brain, Medicine

대표논문

Lee HH, Kim H. Intact metabolite spectrum mining by deep learning in proton magnetic resonance spectroscopy of the brain. Magn Reson Med 2019;82:33-48.
Lee H, Lee HH, Kim H. Reconstruction of spectra from truncated free induction decays by deep learning in proton magnetic resonance spectroscopy. Magn Reson Med 2020 https://doi.org/10.1002/mrm.28164.
Lee HH, Kim H. Deep learning-based target metabolite isolation and big data-driven measurement uncertainty estimation in proton magnetic resonance spectroscopy of the brain. Magn Reson Med 2020 (in press)

148

김형주 공과대학 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

147

김홍기 치의학대학원 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)

146

김홍수 보건대학원 보건학과

연구실/전공분야고령화 보건정책∙서비스 연구실
연구분야(AI 원천기술)
연구분야(X+AI)Bio, Medicine

대표논문

145

나종연 생활과학대학 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.

144

노종선 공과대학 전기정보공학부

연구실/전공분야Coding and Cryptography Laboratory
연구분야(AI 원천기술)privacy preserving machine learning, fully homomorphic encryption algorithms, error correcting codes, information theory
연구분야(X+AI)medical image analysis, financial data analysis, private data analysis

대표논문

[1] Eunsang Lee, Joon-Woo Lee, Junghyun Lee, Yongjune Kim, Young-Sik Kim, Jong-Seon No, and Wooseok Choi, “Low-complexity deep convolutional neural networks on fully homomorphic encryption using multiplexed parallel convolutions,” accepted for presentation in ICML 2022.

[2] Yongwoo Lee, Joon-Woo Lee, Young-Sik Kim, Yongjune Kim, Hyungchul Kang, and Jong-Seon No, “High-precision and low-complexity approximate homomorphic encryption by error variance minimization,” Accepted in EUROCRYPT 2022 (Top-tier conference, accept ratio: 23.0%).

[3] Joon-Woo Lee, Eunsang Lee, Yongwoo Lee, Young-Sik Kim, and Jong-Seon No, “High-precision bootstrapping of RNS-CKKS homomorphic encryption using optimal minimax polynomial approximation and inverse sine function,” EUROCRYPT 2021, pp. 618-647, Springer, Cham, 2021 (Top-tier conference, accept ratio : 19.5%).

[4] Eunsang Lee, Joon-Woo Lee, Young-Sik Kim, and Jong-Seon No, “Minimax approximation of sign function by composite polynomial for homomorphic comparison,” Accepted for publication in IEEE Transactions on Dependable and Secure Computing, August 2021 (IF : 7.329).

[5] Hee-Youl Kwak, Jae-Won Kim, Hosung Park, and Jong-Seon No, “Optimization of SC-LDPC codes for window decoding with target window sizes,” accepted for publication in IEEE Transactions on Communications, March 2022.

[6] Joon-Woo Lee, Hyungchul Kang, Yongwoo Lee, Wooseok Choi, Jieun Eom, Maxim Deryabin, Eunsang Lee, Junghyun Lee, Donghoon Yoo, Young-Sik Kim, and Jong-Seon No, “Privacy-preserving machine learning with fully homomorphic encryption for deep neural network,” IEEE Access, vol. 10, pp. 30039-30054, 2022.

[7] Eunsang Lee, Joon-Woo Lee, Young-Sik Kim, and Jong-Seon No, “Optimization of homomorphic comparison algorithm on RNS-CKKS scheme,” IEEE Access, vol. 10, pp. 26163-26176, 2022.

[8] Zahyun Koo, Yongwoo Lee, Joon-Woo Lee, Young-Sik Kim, and Jong-Seon No, “Improved reduction between SIS problems over structured lattices,” IEEE Access, vol. 9, pp. 157083-157092, 2021.

[9] Joon-Woo Lee, Young-Sik Kim, and Jong-Seon No, “Analysis of modified shell sort for fully homomorphic encryption,” IEEE Access, vol. 9, pp. 126198-126215, 2021.

[10] J Jeong, Seong-Joon Park, Jae-Won Kim, Jong-Seon No, Ha Hyeon Jeon, Jeong Wook Lee, Albert No, Sunghwan Kim, and Hosung Park, ""Cooperative sequence clustering and decoding for DNA storage system with fountain codes,” Bioinformatics, vol. 37, issue 19, pp. 3136-3143, October 2021.

[11] Dong-Hoon Lee, Young-Sik Kim, and Jong-Seon No, ""Bit security estimation using various information-theoretic measures,” IEEE Access, vol. 9, pp. 140103-140115, 2021.

[12] Yongwoo Lee, Wijik Lee, Young-Sik Kim, and Jong-Seon No, ""Modified pqsigRM: RM code-based signature scheme,"" IEEE Access, vol. 8, pp. 177506-177518, September 2020.

[13] YongWoo Lee, Joon-Woo Lee, Young-Sik Kim, and Jong-Seon No, ""Near-optimal polynomial for modulus reduction using L2-norm for approximate homomorphic encryption,"" IEEE Access, vol. 8, pp. 144321-144330, August 2020.

[14] Zahyun Koo, Jong-Seon No, and Young-Sik Kim, ""Reduction from module-SIS to ring-SIS under norm constraint of ring-SIS,"" IEEE Access, vol. 8, 140998-141006, 2020.

[15] Jinkyu Cho, Young-Sik Kim, and Jong-Seon No, ""Homomorphic computation in Reed-Muller codes,"" IEEE Access, vol. 8, pp. 108622-108628, June 2020.

[16] Eunsang Lee, Young-Sik Kim, Jong-Seon No, Minki Song, and Dong-Joon Shin, ""Modification of FrodoKEM using Gray and error-correcting codes,"" IEEE Access, vol. 7, pp. 179564-179574, December 2019.

[17] Hee-Youl Kwak, Jong-Seon No, and Hosung Park, ""Design of irregular SC-LDPC codes with non-uniform degree distributions by linear programming,"" IEEE Transactions on Communications, vol. 67, no. 4, pp. 2632-2646, April 2019."

143

류경석(Ernest Ryu) 자연과학대학 수리과학부

연구실/전공분야류경석 교수 연구실
연구분야(AI 원천기술)Deep Learning Theory, Optimization
연구분야(X+AI)

대표논문

A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast. J. Lee, C. Park, E. K. Ryu, NeurIPS, 2021.
Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k2) Rate on Squared Gradient Norm. T. Yoon and E. K. Ryu, International Conference on Machine Learning (long presentation), 2021.
WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points. A. No, T. Yoon, S. Kwon, and E. K. Ryu, International Conference on Machine Learning, 2021.

142

문병로 공과대학 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

141

문봉기 공과대학 컴퓨터공학부

연구실/전공분야
연구분야(AI 원천기술)
연구분야(X+AI)

대표논문

140

문수묵 공과대학 전기정보공학부

연구실/전공분야가상머신 및 최적화 연구실
연구분야(AI 원천기술)
연구분야(X+AI)

대표논문

139

문일경 공과대학 산업공학과

연구실/전공분야공급망관리 연구실
연구분야(AI 원천기술)logistics & simulation
연구분야(X+AI)Logistics, Manufacturing

대표논문

Traveling Salesman Problem with a Drone Station, IEEE Transactions on Systems, Man and Cybernetics: Systems (2019.01) Vol. 49, Issue 1, pp.42-52
드론을 활용한 통합 물류 운용 시스템 및 그 방법 : 등록 (10-1924729)
2018.11.27
Online Banner Advertisement Scheduling for Advertising Effectiveness, Computers & Industrial Engineering (2020.02) Vol. 140,106226
Supply Chain Coordination with a Single Supplier and Multiple Retailers considering Customer Arrival Times and Route Selection
Transportation Research Part E (2017.10), Vol. 106, pp. 78-97
Robust Empty Container Repositioning Considering Foldable Containers
European Journal of Operational Research (2020.02) Vol. 280, pp 909-925
스마트 교통·에너지·환경 및 안전 기술을 고려한 스마트 시티 통합운영시스템 개발, 한국연구재단, 2019년 9월~2024년 2월
아모레퍼시픽 공급망 관리 진단 및 개선 자문, 아모레퍼시픽, 2020년2월~2020년7월
Service Buffer Stock 재고 객관성 & 수요예측연구, LG 디스플레이, 2016년 3월~2016년 8월

138

민경복 의과대학 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)

137

박건수 공과대학 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

136

박기완 경영대학 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

135

박동열 사범대학 불어교육과

연구실/전공분야불어학
연구분야(AI 원천기술)Language & Cognition
연구분야(X+AI)Humanities/Social Sciences

대표논문

134

박성호 경영대학 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.

133

박세웅 공과대학 전기정보공학부

연구실/전공분야네트워크 연구실
연구분야(AI 원천기술)Learning & Reasoning, Robotics & Action, Human-AI Interaction
연구분야(X+AI)Logistics, Manufacturing, Energy

대표논문

Seowoo Jang, Kang G. Shin, and Saewoong Bahk "Post-CCA and Reinforcement Learning based Bandwidth Adaptation in 802.11ac Networks," IEEE Transactions on Mobile Computing, vol. 17, no. 2, pp. 419-432, Feb. 2018.
Jeongyoon Heo, Byungjun Kang, Jin Mo Yang, Jeongyeup Paek, and Saewoong Bahk, "Performance-Cost Tradeoff of Using Mobile Roadside Units for V2X Communication," IEEE Transactions on Vehicular Technology, vol. 68, no. 9, pp. 9049-9059, Sep. 2019.
Hyung-Sin Kim, JeongGil Ko, and Saewoong Bahk, "Smarter Markets for Smarter Life: Applications, Challenges and Deployment Experiences," IEEE Communications Magazine, vol. 55, no. 5, pp. 34-41, May. 2017.
Sung-Guk Yoon, Young-June Choi, Jong-Keun Park and Saewoong Bahk, "Stackelberg Game based Demand Response for At-Home Electric Vehicle Charging," IEEE Transactions on Vehicular Technology, vol. 65, issue 6, pp. 4172-4184, June 2016.
Jongwook Lee and Saewoong Bahk, "On the MDP-based Cost Minimization for Video-on-Demand Services in a Heterogeneous Wireless Network with Multi-Homed Terminals," IEEE Transactions on Mobile Computing, vol. 12, issue. 9, pp. 1737-1749, Sep. 2013
One of Top 100 Research results in 2018 - Disaster Communication Convergence Technology Research (2016.04.01-2017.12.31.) IITP

132

박소정 경영대학 경영학과

연구실/전공분야Insurance, Risk Management
연구분야(AI 원천기술)
연구분야(X+AI)Finance

대표논문

인슈어테크 혁명: 현황 점검 및 과제 고찰

131

박순애 행정대학원 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

130

박우진 공과대학 산업공학과

연구실/전공분야삶향상기술 연구실
연구분야(AI 원천기술)Human-AI Interaction, Autonomous Driving
연구분야(X+AI)User Experience

대표논문

129

박종헌 공과대학 산업공학과

연구실/전공분야Information Management Lab
연구분야(AI 원천기술)Learning & Reasoning, Language & Cognition
연구분야(X+AI)Arts, Finance, Manufacturing

대표논문

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.

128

박주연 생활과학대학 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

127

박준용 자연과학대학 통계학과

연구실/전공분야
연구분야(AI 원천기술)
연구분야(X+AI)

대표논문

126

박진수 경영대학 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.

125

박창민 의과대학 영상의학교실

연구실/전공분야방사선인공지능연구실
연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Human-AI Interaction
연구분야(X+AI)Medicine

대표논문

Development and Validation of a Deep Learning-Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs. JAMA Netw Open. 2 (3), e191095 2019 Mar 1
Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs. Radiology. 290 (1), 218-228 Jan 2019
Development and Validation of a Deep Learning-based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs. Clin Infect Dis. 69 (5), 739-747 2019 Aug 16
Deep Learning for Chest Radiograph Diagnosis in the Emergency Department. Radiology. 293 (3), 573-580 Dec 2019
CT-based Deep Learning Model to Differentiate Invasive Pulmonary Adenocarcinomas Appearing as Subsolid Nodules Among Surgical Candidates: Comparison of the Diagnostic Performance With a Size-Based Logistic Model and Radiologists. Eur Radiol. 2020 Feb 13[Online ahead of print]
2017.03.-2020.02. 인공지능 딥러닝 알고리즘을 이용한 폐결절 분류 및 폐암 진단 시스템 개발. 한국연구재단 (미래창조과학부)
2017.11-2019.10.31. 다기관 의료영상 인공지능 연구를 위한 보안 클라우드 플랫폼. 서울시 산학연 협력사업 (서울시)

124

박태성 자연과학대학 통계학과

연구실/전공분야생물정보통계연구실
연구분야(AI 원천기술)
연구분야(X+AI)

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서울대학교 AI 연구원은AI 원천기술(core AI) 연구자와 AI 응용기술(x+AI) 연구자가 함께 활동하고 있습니다.

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서울대학교 AI 연구원은
AI 원천기술(core AI) 연구자와 AI 응용기술(x+AI) 연구자가 함께 활동하고 있습니다.