겸무교수 1 페이지 | 서울대학교AI연구원(AIIS)

사람들

겸무교수

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

소속
연구분야 (AI 원천)
연구분야 (응용)
223

엄현상 공과대학 컴퓨터공학부

  • 연구실/전공분야
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)

대표논문

222

이재욱 공과대학 산업공학과

  • 연구실/전공분야Statistical Learning & Computational Finance Laboratory
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Security
  • 연구분야(X+AI)Finance

대표논문

221

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
220

조동일 공과대학 전기정보공학부

  • 연구실/전공분야Nano/Micro Systems & Controls Lab
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)

대표논문

219

장정주 경영대학 경영학과

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

대표논문

218

신영길 공과대학 컴퓨터공학부

  • 연구실/전공분야컴퓨터 그래픽스 및 이미지 처리 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning
  • 연구분야(X+AI)Bio

대표논문

Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation
Deeply Self-Supervised Contour Embedded Neural Network Applied to Liver Segmentation
AI기반 의료영상 데이터 Labeling 기술연구, (주)인피니트헬스케어, 2020-04-01~2021-03-31
인공지능기반 파노라마, CT영상 병변 인식 기술개발, (주)오스템임플란트, 2019-12-16~2021-02-15
인공지능 기반 CT 영상 분할 기술 개발, (주)오스템임플란트, 2019-02-01~2019-10-31
217

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
216

신현우 의과대학 약리학교실

  • 연구실/전공분야호흡기 약리학 / 비과학 / 수면의학
  • 연구분야(AI 원천기술)Learning & Reasoning, Robotics & Action, Human-AI Interaction
  • 연구분야(X+AI)Bio, Medicine, Pharma

대표논문

215

박재흥 융합과학기술대학원 지능정보융합학과

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

대표논문

214

임도빈 행정대학원 행정학과

  • 연구실/전공분야
  • 연구분야(AI 원천기술)AI Law & Ethics
  • 연구분야(X+AI)Humanities/Social Sciences

대표논문

저서
임도빈. (2021). 더 좋은 나라, 이렇게 하면 어떨까?:한국 사회가 묻고, 임도빈이 답하다. 서울:윤성사
엄석진 [외]. (2021). AI와 미래행정=AI and future administration. 서울: 박영사. 
임도빈. (2020). 비교행정. 백완기, 박종민(편). 학문연구의 동향과 쟁점 행정학 (pp.131-152). 서울: 대한민국학술원.


논문
임도빈. (2021). 정책과 문화예술의 관계: 코로나 19 이후의 변화를 중심으로. 문화예술융합연구, 2(1), 5-25.
정윤진, 경규웅, 임도빈. (2021). 공공봉사동기와 사회적 영향력이 직무만족에 미치는 영향: 공공서비스 개인-조직 적합성의 관점에서. 행정논총, 59(2), 175-200.
Chung, K. H., & Im, T. (2021). Happiness in developing countries: can government competitiveness substitute for formal institutions?. International Review of Administrative Sciences, 00208523211000421.
정윤진, 김필, 임도빈. (2021). 지방․지역인재 우대 인사정책에 대한 공무원의 태도.한국인사행정학회보, 20(1),37-66.
Im, T., & Campbell, J. W. (2020). Coordination, Incentives, and Persuasion: South Korea’s Comprehensive Approach to COVID-19 Containment. Korean Journal of Policy Studies, 35(3), 119-139."
213

이남인 인문대학 철학과

  • 연구실/전공분야현상학
  • 연구분야(AI 원천기술)AI Law & Ethics
  • 연구분야(X+AI)Humanities/Social Sciences

대표논문

Edmund Husserls Phaenomenologie der Instinkte, Dordrecht/Boston/London: Kluwer Academic Publishers,1993.
『현상학과 해석학』, 서울: 서울대학교 출판부, 2004.
『지각의 현상학. 후설과 메를로-퐁티』, 파주: 한길사, 2013.
『예술본능의 현상학』, 파주: 서광사, 2018.
Experience and Evidence(Husserl Studies 23(2007))
212

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.
211

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)
210

김선진 사범대학 체육교육과

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

대표논문

209

정현태 의과대학 신경외과학교실

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

대표논문

208

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
207

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
206

김기현 인문대학 철학과

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

대표논문

205

최무림 의과대학 의과학과

  • 연구실/전공분야기능유전체학
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)Bio, Medicine

대표논문

204

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.
203

안창범 공과대학 건축학과

  • 연구실/전공분야건설기술연구실
  • 연구분야(AI 원천기술)Human-AI Interaction, Robotics & Action
  • 연구분야(X+AI)건설 + AI

대표논문

"Lee, H., Lee, G., Lee S., and Ahn, C. R. (2022). “Assessing Exposure to Slip, Trip, and Fall Hazards Based on Abnormal Gait Patterns Predicted from Confidence Interval Estimation: A Field Validation Study.” Automation in Construction, Elsevier.
Lee, B., Ahn, S., and Ahn, C. R. (2022). “Understanding Occupants’ Physical Distancing Behavior for Safer Facility Operation under COVID-19 in the Context of Educational Facilities.” Journal of Management in Engineering, ASCE, 38(3), 04022007.
Kim, J., Nirjhar, H. E., Kim, J., Chaspari, T., Ham, Y., Winslow, J. F., Lee, C., and Ahn, C. R. (2022). “Capturing Environmental Distress of Pedestrians using Multimodal Data: the Interplay of Bio-signals and Image-based Data.” Journal of Computing in Civil Engineering, ASCE, 36(2), 04021039.
Kim, Y., Kim, H., Murphy, R., Lee, S. and Ahn, C. (2022) “Delegation or Collaboration: Understanding Different Construction Stakeholders’ Perceptions of Robotization.” Journal of Management in Engineering, ASCE, 38(1), 04021084.
Kim, N., Anderson, B., and Ahn, C. R. (2021). “Reducing Risk Habituation to Struck-by Hazards in a Road Construction Environment Using Virtual Reality Behavioral Intervention.” Journal of Construction Engineering and Management, ASCE, 147(11), 04021157.
Zanwar, P., Kim, J., Kim, J., Manser, M., Ham, Y., Chaspari, T. and Ahn, C. R. (2021). “Use of Connected Technologies to Assess Barriers and Stressors for Age and Disability-Friendly Communities.” Frontiers in Public Health, 9(80).
Mohan, P., Lee, B., Chaspari, T., & Ahn, C. (2020). Assessment of daily routine uniformity in a smart home environment using hierarchical clustering. IEEE Journal of Biomedical and Health Informatics."
202

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.
201

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
200

이성훈 자연과학대학 화학부

  • 연구실/전공분야Molecular Electronics and Nanostructures Laboratory
  • 연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, AI Chip
  • 연구분야(X+AI)Brain, Energy

대표논문

199

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

198

차지욱 사회과학대학 심리학과

  • 연구실/전공분야SNU Connectome Lab
  • 연구분야(AI 원천기술)Learning & Reasoning
  • 연구분야(X+AI)Humanities/Social Sciences

대표논문

197

정현훈 의과대학 산부인과학교실

  • 연구실/전공분야산부인과
  • 연구분야(AI 원천기술)AI Platform, Human-AI Interaction
  • 연구분야(X+AI)Medicine

대표논문

196

양인순 공과대학 전기정보공학부

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

대표논문

195

장우진 공과대학 산업공학과

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

대표논문

194

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
193

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
192

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)
191

정재용 의과대학 임상약리학교실

  • 연구실/전공분야신약임상개발, 뇌신경분야 초기임상시험
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)

대표논문

190

박태성 자연과학대학 통계학과

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

대표논문

189

이상학 데이터사이언스대학원

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

대표논문

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

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

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

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

인과성에 기반한 기계학습 모델 및 알고리즘 개발. 과학기술정보통신부/우수신진연구 2023.04.01 ~ 2028.03.31
188

오성주 사회과학대학 심리학과

  • 연구실/전공분야심리학과 지각 실험실
  • 연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception, Robotics & Action, Human-AI Interaction
  • 연구분야(X+AI)Bio, Arts, Humanities/Social Sciences, Brain

대표논문

Kwon, D., & Oh, S. (2019). The number of letters in number words influences the response time in numerical comparison tasks: Evidence using Korean number words. Attention, Perception, & Psychophysics, 81(8), 2612-2618.
Ryu, D., & Oh, S. (2018). The effect of good continuation on the contact order judgment of causal events. Journal of Vision, 18(11), 5-5.
Lee, H., & Oh, S. (2016). How directional change in reading/writing habits relates to directional change in displayed pictures. Laterality: Asymmetries of Body, Brain and Cognition, 21(1), 1-11.
Oh, S. (2013). Eyes can switch finger stroke. Perception, 42(6), 681–684.
Oh S. (2011). The eyeglass reversal. Attention, Perception & Psychophysics. 73, 1336-1343.
Baby mind: 아기 모사형 인공지능 개발
서울대학교 얼굴 데이터베이스 구축
미술감상에서 감상자 자세
187

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
186

정연석 약학대학 제약학과

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

대표논문

Atherogenic dyslipidemia promotes autoimmune follicular helper T cell responses via IL-27.
Nat Immunol. 2018 Jun;19(6):583-593. doi: 10.1038/s41590-018-0102-6
IL-27 confers a protumorigenic activity of regulatory T cells via CD39.
Proc Natl Acad Sci U S A. 2019 Feb 19;116(8):3106-3111.
Fibrinogen cleavage products and Toll-like receptor 4 promote the generation of programmed cell death 1 ligand 2-positive dendritic cells in allergic asthma.
J Allergy Clin Immunol. 2018 Aug;142(2):530-541
Proatherogenic conditions promote autoimmune T helper 17 cell responses in vivo.
Immunity. 2014 Jan 16;40(1):153-65
Follicular regulatory T cells expressing Foxp3 and Bcl-6 suppress germinal center reactions.
Nat Med. 2011 Jul 24;17(8):983-8.
185

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
184

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
183

Bernhard Egger 공과대학 컴퓨터공학부

  • 연구실/전공분야컴퓨터 시스템 및 플랫폼 연구실
  • 연구분야(AI 원천기술)Learning & Reasoning, AI Platform, AI Chip
  • 연구분야(X+AI)

대표논문

Barend Harris, Inpyo Bae, and Bernhard Egger. "Architectures and algorithms for on-device user customization of CNNs." In Integration, the VLSI Journal, Volume 67, July 2019.
Inpyo Bae, Barend Harris, Hyemi Min, and Bernhard Egger. "Auto-Tuning CNNs for Coarse-Grained Reconfigurable Array-based Accelerators." Presented at the 2018 International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES'18) and in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Volume 37, Issue, 11; November 2018.
Younghyun Cho, Surim Oh, and Bernhard Egger. "Performance Modeling of Parallel Loops on Multi-Socket Platforms using Queueing Systems." In IEEE Transactions on Parallel and Distributed Systems (TPDS), Volume 31, Issue 2; February 2020.
Younghyun Cho, Camilo A.C. Guzman, and Bernhard Egger. "Maximizing System Utilization via Parallelism Management for Co-Located Parallel Applications." In Proceedings of the the 2018 International Conference on Parallel Architectures and Compilation (PACT'18), Limassol, Cyprus, November 2018.
Changyeon Jo, Youngsu Cho, and Bernhard Egger. "A Machine Learning Approach to Live Migration Modeling." In Proceedings of the 2017 ACM Symposium on Cloud Computing (SoCC'17), Santa Clara, USA, September 2017.
Efficient Mapping and Scheduling of Resource and Dataflow for NPU Architecture Search, 삼성전자, 2020
Exploring the Effect of Data Compression on Runtime and Accuracy of DNNs, SK텔레콤, 2018-2020
H/W–컴파일러 수직적 통합 최적화된 임베디드 DNN 프로세서연구, 삼성전자, 2017-2020
182

이규언 의과대학 외과학교실

  • 연구실/전공분야유방내분비외과학
  • 연구분야(AI 원천기술)Vision & Perception, Autonomous Driving
  • 연구분야(X+AI)Medicine

대표논문

Ultrasound image analysis using deep learning algorithm for the diagnosis of thyroid nodules. Medicine (Baltimore). 2019
로봇수술 숙련도 평가 모델 및 트레이닝 시스템의 개발 및 적용 (한국연구재단 신진연구자지원사업, 2015~)
의료 빅데이터 융합 전문가 인력 양성을 위한 비정형 빅데이터의 정형화 기술 및 분석 플랫폼 개발(과학기술정보통신부, 정보통신방송연구개발사업, 세부책임자, 2019~)
181

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.
180

이기원 농업생명과학대학

  • 연구실/전공분야식의학유전체학
  • 연구분야(AI 원천기술)Learning & Reasoning, Language & Cognition, Human-AI Interaction
  • 연구분야(X+AI)Bio, Medicine, Food

대표논문

인공지능기반 최적파이토슈티컬 도출시스템 및 응용연구실, 기초연구실사업, 과기정통부
아동청소년 비만 예방관리를 위한 BT-IT 융합기반 통합 플랫폼 기술개발, 과기정통부
방송통신 융합기술을 활용한 보육기관 맞춤형 스마트 웰니스 서비스 개발, 과기정통부
179

손석우 자연과학대학 지구환경과학부

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

대표논문

178

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
177

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
176

이권상 자연과학대학 통계학과

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

대표논문

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

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

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

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

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

Lee, K., Small, D. S., Hsu, J. Y., Silver, J. H. and Rosenbaum, P. R. (2018). Discovering effect modification in an observational study of surgical mortality at hospitals with superior nursing. Journal of the Royal Statistical Society, Series A.
175

이상열 자연과학대학 통계학과

  • 연구실/전공분야시계열 예측분석 연구실
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)

대표논문

174

신형철 공과대학 전기정보공학부

  • 연구실/전공분야반도체소자 연구실
  • 연구분야(AI 원천기술)AI Chip
  • 연구분야(X+AI)Manufacturing

대표논문

173

한상진 환경대학원 환경계획학과

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

대표논문

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

공동저서
한상진, 장수은, 진장원 2019. 보행교통의 이해-걷기좋은도시 만들기의 첫걸음, 키네마인.
한상진 2020. 녹색교통을 위한 도시 가로의 재구성, in「감염병 시대 도시변화의 방향을 묻다」, 서울연구원 pp 75-97.
안전속도 5030 설계·운영매뉴얼 2019. 한상진(편), 경찰청·국토교통부
172

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
171

정덕균 공과대학 전기정보공학부

  • 연구실/전공분야집적시스템설계 연구실
  • 연구분야(AI 원천기술)AI Chip
  • 연구분야(X+AI)Semiconductor

대표논문

An efficient charge recovery logic circuit
An all-analog multiphase delay-locked loop using a replica delay line for wide-range operation and low-jitter performance
Design of PLL-based clock generation circuits
A 960-Mb/s/pin interface for skew-tolerant bus using low jitter PLL
A 0.18-μm CMOS 3.5-Gb/s continuous-time adaptive cable equalizer using enhanced low-frequency gain control method
170

송인성 경영대학 경영학과

  • 연구실/전공분야Marketing Management, Marketing Research, Marketing Modeling
  • 연구분야(AI 원천기술)Marketing analytics
  • 연구분야(X+AI)Marketing

대표논문

169

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
168

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
167

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

166

이철주 사회과학대학 언론정보학과

  • 연구실/전공분야헬스커뮤니케이션, 소셜마케팅, 과학커뮤니케이션, 환경커뮤니케이션
  • 연구분야(AI 원천기술)Language & Cognition, AI Law & Ethics, Text Mining
  • 연구분야(X+AI)Humanities/Social Sciences, Medicine, Media + AI

대표논문

Chul-joo Lee, Kwanho Kim, & Bee-ah Kang (2019). A moderated mediation model of the relationship between media, social capital, and cancer knowledge. Health Communication. 34, 577-588. [Lead Paper]
Chul-joo Lee & Dongyoung Sohn (2016). Mapping the social capital research in communication: A bibliometric analysis. Journalism & Mass Communication Quarterly, 93(4), 728-749. [Lead Paper]
Chul-joo Lee & Jennifer Kam (2015). Why does social capital matter in health communication campaigns? Communication Research, 42(4), 459-481. [Lead Paper]
Andy Tan, Chul-joo Lee, & Jiyoung Chae (2015). Exposure to health (mis)information: Lagged effects on young adults’ health behaviors and potential pathways. Journal of Communication, 65(4), 674-698.
Chul-joo Lee (2014). The role of social capital in health communication campaigns: The case of the National Youth Anti-Drug Media Campaign. Communication Research, 41(2), 208-235.
165

윤성수 의과대학 내과학교실

  • 연구실/전공분야혈액학연구실
  • 연구분야(AI 원천기술)Learning & Reasoning
  • 연구분야(X+AI)Bio, Medicine, Pharma

대표논문

Genet Med. 2019 Dec;21(12):2695-2705. doi: 10.1038/s41436-019-0588-9.
Oncogenic effects of germline variants in lysosomal storage disease genes.
Sci Rep. 2019 Mar 5;9(1):3465. doi: 10.1038/s41598-019-39706-0.
Interpretation of EBV infection in pan-cancer genome considering viral life cycle: LiEB (Life cycle of Epstein-Barr virus).
Blood Cancer J. 2018 May 23;8(5):43. doi: 10.1038/s41408-018-0083-6.
RTK-RAS pathway mutation is enriched in myeloid sarcoma.
164

안용민 의과대학 정신과학교실

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

대표논문

기계학습 기반의 음성 분석으로 자살 위험 예측
163

현동훈 자연과학대학 수리과학부

  • 연구실/전공분야대수기하학
  • 연구분야(AI 원천기술)Learning & Reasoning, Vision & Perception
  • 연구분야(X+AI)Arts, Medicine

대표논문

162

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.
161

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
160

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
159

우지숙 행정대학원 행정학과

  • 연구실/전공분야행정과 커뮤니케이션, 정책 홍보, 인터넷 정책, 저작권법, 언론미디어
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)Humanities/Social Sciences, Media

대표논문

Copyright Law and Computer Programs: The Role of Communication in Legal Structure, (New York: Garland Publishing, 2000)
국가운영시스템 과제와 전략 (나남, 2008) 공저)
언론과 법의 지배 (박영사, 2007) (공저)
158

오민환 데이터사이언스대학원

  • 연구실/전공분야Decision-Making Algorithms, Reinforcement Learning
  • 연구분야(AI 원천기술)Learning & Reasoning
  • 연구분야(X+AI)

대표논문

Combinatorial Neural Bandits. Taehyun Hwang, Kyuwook Chai, Min-hwan Oh, International Conference on Machine Learning (ICML), 2023

Model-based Offline Reinforcement Learning with Count-based Conservatism. Byeongchan Kim, Min-hwan Oh, International Conference on Machine Learning (ICML), 2023

Model-based Reinforcement Learning with Multinomial Logistic Function Approximation. Taehyun Hwang, Min-hwan Oh, AAAI Conference on Artificial Intelligence (AAAI), 2023

Sparsity-Agnostic Lasso Bandit. Min-hwan Oh, Garud Iyengar, Assaf Zeevi, International Conference on Machine Learning (ICML), 2021

Thompson Sampling for Multinomial Logit Contextual Bandits. Min-hwan Oh, Garud Iyengar Neural Information Processing Systems (NeurIPS), 2019
157

홍성수 공학전문대학원 응용공학과

  • 연구실/전공분야RTOS Lab
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)

대표논문

156

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
155

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

154

이준환 사회과학대학 언론정보학과

  • 연구실/전공분야Human+Computer Interaction+Design Lab
  • 연구분야(AI 원천기술)Learning & Reasoning, Language & Cognition, Human-AI Interaction
  • 연구분야(X+AI)Arts, Humanities/Social Sciences, Media + AI

대표논문

Soomin Kim, Jinsu Eun, Changhoon Oh, Bongwon Suh & Joonhwan Lee (2020) Bot in the Bunch: Facilitating Group Chat Discussion by Improving Efficiency and Participation with a Chatbot. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI ’20). Association for Computing Machinery, New York, NY, USA, Paper 654, 1-13.
Dongwhan Kim & Joonhwan Lee (2019) Designing an Algorithm-Driven Text Generation System for Personalized and Interactive News Reading, International Journal of Human–Computer Interaction, 35:2, 109-122, DOI: 10.1080/10447318.2018.1437864
Soomin Kim, Joonhwan Lee, and Gahgene Gweon (2019) Comparing Data from Chatbot and Web Surveys: Effects of Platform and Conversational Style on Survey Response Quality. In Proceedings of the 2019 CHI Conference on Human ctors in Computing Systems (CHI ’19). Association for Computing Machinery, New York, NY, USA, Paper 86, 1–12. DOI:https://doi.org/10.1145/3290605.3300316
SoHyun Park, Jeewon Choi, Sungwoo Lee, Changhoon Oh, Changdai Kim, Soohyun La, Joonhwan Lee & Bongwon Suh (2019) Designing a Chatbot for a Brief Motivational Interview on Stress Management: Qualitative Case Study, Journal of medical Internet research 21 (4), e12231, https://www.jmir.org/2019/4/e12231/
Jieun Wee, Sooyeun Jang, Joonhwan Lee & Woncheol Jang (2017) The influence of depression and personality on social networking, Computers in Human Behavior, 74, 45-52, https://doi.org/10.1016/j.chb.2017.04.003
로봇 저널리즘 기반의 방송 뉴스 콘텐츠 제작 기술 개발, 과학기술정보통신부, 2017.4.1 ~ 2019.12.31
성범죄 피해자 진술 지원 시스템 연구, 과학정보기술통신부, 2018/08/01 ~ 2020/12/31
153

윤용태 공과대학 전기정보공학부

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

대표논문

SH Oh, SW Kim, YT Yoon, Real-time Reconfiguration Strategy of Self-adequate Distribution Network based on Deep Reinforcement Learning, CIGRE Symposium 2019, Aalborg, Denmark, 4-7 June 2019.
152

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)
151

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

150

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
149

제원호 자연과학대학 물리천문학부

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

대표논문

Interfacial thermodynamics of spherical nanodroplets: Molecular understanding of surface tension via hydrogen bond network
GCIceNet: A Graph Convolution Network For Deep Learning Of Ice Phases
AI-based atomic force microscopy
리더연구과제 0차원 나노플루이딕스
148

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.
147

염헌영 공과대학 컴퓨터공학부

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

대표논문

146

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
145

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.
144

탁성희 간호대학 간호학과

  • 연구실/전공분야성인간호
  • 연구분야(AI 원천기술)Human-AI Interaction
  • 연구분야(X+AI)Aging Care Services and Wellness

대표논문

Tak, SH. (2018). 4차 산업혁명시대 Gerontological Nursing in the Era of the Fourth Industrial Revolution. 노인간호학회지 Journal of Korean Gerontological Nursing. 20, S160~165. (doi: 10.17079/jkgn.2018.20.s1.s160)
Bidelman, GM., Lowther, JE., Tak, SH., & Alain, C. (2017). Mild Cognitive Impairment Is Characterized by Deficient Brainstem and Cortical Representations of Speech. Journal of Neuroscience, 37(13), 3610-3620. (doi: 10.1523/JNEUROSCI.3700-16.2017)
Tak, S., Zhang, H., Patel, H., & Hong, S. (2015). Computer activities for persons with dementia. The Gerontologist, 55, S40-49. (doi: 10,1093/geront/gnv003)
Tak, S., Zhang, H., & Hong, S. (2015). Preferred computer activities among individuals with dementia: a pilot study. Journal of Gerontological Nursing, 41(3), 50-57. March 1st, 2015 (Online advance release at November 7, 2014) (doi:10.3928/00989134-20141029-01)
Tak, S., Kedia, S., Tongumpun, T., Hong, SH. (2015). Activity engagement: perspectives from nursing home residents with dementia. Educational Gerontology, 41(3), 182-192. March 1, 2015 (Online advance release at August 21, 2014.) (doi:10.1080/03601277.2014.937217)
치매문제행동모델을 적용한 홀로그래픽 혼합현실 시뮬레이션 간호교육 모듈 개발과 효과. Development and evaluation of holographic mixed reality-based simulation nursing eudcational program using dementia-compromized behavior model. 이공학개인기초연구지원사업 (2018R1D1A1A02085994). 2018.11.01.~2019.10.31. 한국연구재단(책임연구자)
치매노인을 위한 컴퓨터인지훈련프로그램에 대한 문헌고찰 및 치매고위험노인의 활동프로그램 개발과 평가 Computerized cognitive training in persons with dementia: a systematic review & Effects of an integrated activity program for older adults with low education and mild dementia. 2015.10.01 – 2017.09.30. 서울대학교 신임교수지원사업 & 차세대 신진학자 초빙사업. (연구책임자)
Center for Technologies and Research in Alzheimer’s Care. 2013-2015. FedEx Institute of Technology Innovation Grant, University of Memphis Foundation. USA. (연구책임자 & Director)
143

홍성욱 자연과학대학 생명과학부

  • 연구실/전공분야과학사연구실
  • 연구분야(AI 원천기술)AI Law & Ethics
  • 연구분야(X+AI)Arts, Humanities/Social Sciences, Manufacturing

대표논문

<포스트휴먼 오디세이>
"인공지능은 인간을 차별하는가?"
<크로스 사이언스>
<미래는 오지 않는다>
<홍성욱의 과학 에세이>
인공지능: 과학, 역사, 철학
인공지능의 윤리적, 법적, 사회적 문제들
인공지능과 차별
142

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.
141

심규석 공과대학 전기정보공학부

  • 연구실/전공분야데이타마이닝 및 데이터베이스
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)

대표논문

140

원중호 자연과학대학 통계학과

  • 연구실/전공분야
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)

대표논문

139

이유리 생활과학대학 의류학과

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

대표논문

138

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
137

안우영 사회과학대학 심리학과

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

대표논문

Ahn, W.-Y., Kishida, K. T., Gu, X., Lohrenz, T., Harvey, A. H., Alford, J. R., Smith, K. B., Yaffe, G., Hibbing, J. R., Dayan, P., & Montague, P. R. (2014) Nonpolitical images evoke neural predictors of political ideology. Current Biology, 24, 1-7.
Ahn, W.-Y., Haines, N., & Zhang, L. (2017) Revealing neuro-computational mechanisms of reinforcement learning and decision-making with the hBayesDM package. Computational Psychiatry, 1:1.
Ahn, W.-Y. & Vassileva, J. (2016) Machine learning identifies substance-specific behavioral markers for heroin and amphetamine dependence. Drug and Alcohol Dependence, 161, 247-257.
Aylward, J., Valton, V., Ahn, W. Y., Bond, R. L., Dayan, P., Roiser, J. P., & Robinson, O. J. (2019). Altered learning under uncertainty in unmedicated mood and anxiety disorders. Nature Human Behaviour, 3(10), 1116-1123.
Yang, J., Pitt, M. A., Ahn, W. Y., & Myung, J. I. (in press) ADOpy: A Python Package for Adaptive Design Optimization. Behavior Research Methods.
  기계학습을 이용한 빠르고 높은 신뢰도의 멀티모달 금연 표지 개발, 한국연구재단 (연구책임자), 2017-2022년
작업기억-의사결정 상호작용의 뇌신경망에 관한 통합적 연구, 한국연구재단 (공동연구자), 2018-2020년
뇌영상기법과 기계학습을 이용한 비정상적 의사결정의 신경계산학적 기전 연구, 서울대학교 창의선도 신진 연구자 지원사업 (연구책임자), 2019-2022년
136

장원철 자연과학대학 통계학과

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

대표논문

135

김진수 공과대학 컴퓨터공학부

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

대표논문

134

Myunghee Cho Paik (조명희) 자연과학대학 통계학과

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

대표논문

Contextual multi-armed bandit algorithm for semiparametric reward model. presented at ICML 2019
Doubly Robust Lasso Bandit. presented at NeurIPs 2019
Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric.  presented at ACML 2019 and published at Machine Learning
Lipschitz continuous autoencoders in application to anomaly detection.  accepted for AISTAT 2020
Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation. published at CSDA
딥러닝의 통계적 접근: 의료영상자료를 위한 합성곱 신경망 모형의 새로운 통계적 추론 방법 연구 (연구재단 중견연구, 2017-03-01 - 2020-02-29)
133

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.
132

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.
131

조정효 사범대학 물리교육과

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

대표논문

Hoang DT, Song J, Periwal V, and Jo J. Network inference in stochastic systems from neurons to currencies: Improved performance at small sample size, Phys Rev E, 99:023311 (2019)
Song J, Marsili M, and Jo J. Resolution and relevance trade-offs in deep learning, Journal of Statistical Mechanics, 12:123406 (2018)
Hoang DT, Jo J and Periwal V. Data-driven inference of hidden nodes in networks, Phys Rev E, 99:042114 (2019)
Cubero RJ, Jo J, Marsili M, Roudi Y and Song J. Statistical criticality arises in most informative representations, Journal of Statistical Mechanics, 6:063402 (2019)
Xu J and Jo J. Immunological recognition by articial neural networks, Journal of Korean Physical Society, 73:1908-1917 (2018)
Dynamics Inference from Time Series Data, NRF, 2019.06.01 - 2022.02.28
130

천정희 자연과학대학 수리과학부

  • 연구실/전공분야동형암호, 정보보호
  • 연구분야(AI 원천기술)AI Security, AI Theory
  • 연구분야(X+AI)Medicine, Finance, Commerce

대표논문

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
129

강형진 의과대학 소아과학교실

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

대표논문

128

이경수 공과대학 기계공학부

  • 연구실/전공분야Vehicle Dynamics & Control Laboratory
  • 연구분야(AI 원천기술)
  • 연구분야(X+AI)

대표논문

127

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
126

이광근 공과대학 컴퓨터공학부

  • 연구실/전공분야프로그래밍 연구실
  • 연구분야(AI 원천기술)AI Platform, AI Security, ai verification, security, safety
  • 연구분야(X+AI)

대표논문

[book] Introduction to Static Analysis: an abstract interpretation perspective, MIT Press, 2020
Adaptive Static Analysis via Learning with Bayesian Optimization, TOPLAS 40(4), no.14, 2018
Global Sparse Analysis Framework, TOPLAS 36(3), no.8, 2014
Optimizing Homomorphic Evaluation Circuits by Program Synthesis and Term Rewriting, PLDI 2020
Selective Context-Sensitivity Guided by Impact Pre-Analysis, PLDI 2014
과기부 연구재단 선도연구센터(ERC), 소프트웨어무결점 연구센터, 센터장, 2008-2015
과기부 연구재단 창의연구단(CRI), 프로그램분석시스템 연구단, 연구단장, 1998-2003
125

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

124

문수묵 공과대학 전기정보공학부

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

대표논문

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