Underwood International College

Department of Mechanical and Industrial Engineering, University of Toronto, as a visiting professor (2023.09.~2024.08.)
Associate Professor of Creative Technology Management (2021.09.~Present)
Assistant Professor of Creative Technology Management (2016.09.~2021.08)

Email: keeheon@yonsei.ac.kr, keeheon.lee@utoronto.ca
Tel: 032-749-3610
Office: Veritas Hall C407

Profile

Hi, I am a data scientist for (social) good. 

I am associated with Underwood International College and the Graduate School of Information at Yonsei University in Korea. Additionally,I initiated the "Design Intelligence Graduate Program" in the Graduate School of Communication and taught various courses there as a contribution. This program has since evolved into the Graduate Program in the Department of Innovation, leading to a Master of Science degree in Innovation. I also conceived and drafted a proposal for Makerspace i7. I served as a steering committee member for Design Factory Korea and Makerspace i7. Furthermore, I hold the role of Sustainable Development Fellow at the Institute for Global Engagement and Empowerment, where I organize a session on Artificial Intelligence and Emerging Technologies for Better Engagement and Empowerment as part of the Global Engagement and Empowerment Forum on Sustainable Development.

In addition to my own research efforts aimed at tackling significant problems, I encourage my students to undertake research initiatives of their own, utilizing data-driven approaches to address challenges in their respective contexts.

My expertise lies in extracting meanings from data. This is exemplified by my proposal of an encoder-decoder model, akin to a (de)MUX in Electrical Engineering, for scientific and technological research in the early 2010s. In this context, I find resonance in a quote from the movie "Tolkien": "Things aren't beautiful because of how they sound. They're beautiful because of what they mean."

Education

Ph.D. in Industrial Information Engineering, Yonsei University
Dissertation: Technology Analysis and Forecasting using Data Mining and Simulation (Advisor: Chang Ouk Kim)
M.A. in Industrial System Engineering, Yonsei University
B.S. in Computer Science and Industrial System Engineering, Yonsei University (Double majored in Economics)

Courses and Current Research Areas

CTM1002 IT Foundation, CTM1004 Computer Programming and Literacy, CTM2011 Social Network Analysis, CTM2014 Data Science for Business
INV6101 Automation and Optimization, INV6107 Business Intelligence, INV6108 Advanced Topics in Deep Learning

I am deeply engaged in the study of humanities, driven by the belief that innovation results from the dynamic interactions among intelligent entities, whether human or artificial. Consequently, my research focuses on the realms of human and artificial intelligence.

 Human and Artificial Intelligence Research (HAIR) Group conducts research on (1) Understanding AI algorithms and the relationship between human and artificial intelligence, (2) Developing AI for social good, (3) Evaluating the effect of AI on Science, Technology, Innovation, Society (STI-S), based on the knowledge of automation and data science (including data mining, process mining). Additionally, I manage yonsei.ai and sdgs.ai to build a community for building a better today and future.

My research interest has may parts: AI (including ML, DL, RL, Metaheuristics) and its applications (Smart Work, Ethical AI, AI Ethics, Human and AI interaction/coordination/collaboration); evaluation of the science, technology, innovation (STI) relevant to AI applications using data mining and simulation; computational intelligence for new product and service design.

Research keywords
Intelligence, Interaction, Innovation 

Selected Publications

(Refer to Google Scholar Page)

• Kwon, S., Lee, H., Park, S., Heo, Y., Lee, K., & Kang, Y. (2023). ‘Um, so like, is this how I speak?’: design implications for automated visual feedback systems on speech. Behaviour & Information Technology, 1-20.

• Kim, S., & Lee, K. (2023). The paradigm shift of mass customisation research. International Journal of Production Research, 61(10), 3350-3376.

• Thompson, N. C., Greenewald, K., Lee, K., & Manso, G. F. (2021). Deep learning's diminishing returns: The cost of improvement is becoming unsustainable. ieee Spectrum, 58(10), 50-55.

• Lee, K. (2021). A systematic review on social sustainability of artificial intelligence in product design. Sustainability, 13(5), 2668.

• Ryu, H., Kim, S., Kim, D., Han, S., Lee, K., & Kang, Y. (2020). Simple and steady interactions win the healthy mentality: Designing a chatbot service for the elderly. Proceedings of the ACM on human-computer interaction, 4(CSCW2), 1-25.

• Kang, Y., & Lee, K. (2020). Designing technology entrepreneurship education using computational thinking. Education and Information Technologies, 25, 5357-5377.

• Lee, K., & Jung, H. (2019). Dynamic semantic network analysis for identifying the concept and scope of social sustainability. Journal of cleaner production, 233, 1510-1524.

• Lee, H., Lim, J., Lee, K., & Kim, C. O. (2019). Agent simulation-based ordinal optimisation for new product design. Journal of the Operational Research Society, 70(3), 502-515.

• Lee, S. Y., & Lee, K. (2018). Factors that influence an individual's intention to adopt a wearable healthcare device: The case of a wearable fitness tracker. Technological Forecasting and Social Change, 129, 154-163.

• Song, M., Kim, S., & Lee, K. (2017). Ensemble analysis of topical journal ranking in bioinformatics. Journal of the Association for Information Science and Technology, 68(6), 1564-1583.

• Lee, K., Kim, S., Kim, E. H. J., & Song, M. (2017). Comparative evaluation of bibliometric content networks by tomographic content analysis: An application to Parkinson's disease. Journal of the Association for Information Science and Technology, 68(5), 1295-1307.

• Lee, K., Jung, H., & Song, M. (2016). Subject–method topic network analysis in communication studies. Scientometrics, 109, 1761-1787.

• Jung, H., Lee, K., & Song, M. (2016). Examining characteristics of traditional and Twitter citation. Frontiers in Research Metrics and Analytics, 1, 6.

• Lee, K., Lee, H., & Kim, C. O. (2014). Pricing and timing strategies for new product using agent-based simulation of behavioural consumers. Journal of Artificial Societies and Social Simulation, 17(2), 1.

• Lee, K., Kim, S., Kim, C. O., & Park, T. (2013). An agent-based competitive product diffusion model for the estimation and sensitivity analysis of social network structure and purchase time distribution. Journal of Artificial Societies and Social Simulation, 16(1), 3.

• Kim, S., Lee, K., Cho, J. K., & Kim, C. O. (2011). Agent-based diffusion model for an automobile market with fuzzy TOPSIS-based product adoption process. Expert Systems with Applications, 38(6), 7270-7276.

• Ko, J. M., Son, J. H., Ahn, Y. D., Lee, K. H., Yang, S. W., Kim, S. H., ... & Lee, Y. H. (2009). The Development of Customized Overcrowding Index for an Emergency Department. Journal of the Korean Society of Emergency Medicine, 20(4), 435-444.

• 이다빈, & 이기헌. (2020). 역사 학습효과 증진을 위한 웹 가상박물관 디자인 가이드라인에 대한 연구-사용자 경험 디자인을 중심으로. 박물관학보, (38), 27-58.

• 양준석, 이기헌, & 조화순. (2020). 한국 언론기사를 대규모 역사데이터로 활용한 동북아 해양영토분쟁 분석. 국제지역연구, 24(2), 73-97.

• 이기헌, 정효정, & 송민. (2015). 문헌정보학 분야 핵심 학술지들의 가중 주제-방법 네트워크 분석. 한국문헌정보학회지, 49(3), 457-488.

More Information

Work Experience

• Senior Researcher, Innovation Strategy and Policy Research Group (Social Science Korea), KAIST (Supervisor: Wonjoon Kim)
• Postdoctoral Research Fellow, Big Data-based Future Model of Knowledge Service Team (BK PLUS), Yonsei University (Superviser: Min Song)

Awards

• 2022 Yonsei University, Seoul - Certificate of Merit for Excellent Research

• 2019 QS Reimagine Education Award (Bronze in Social Science)

• 2016 Korea Institute of Science and Technology Convergence Research Policy Center, Seoul - KIST Convergence Research Policy Fellowship 

• 2014 Yonsei University, Seoul - Certificate of Merit for Excellent Paper

• 2013 Hyundai Mobis, Seoul - 2nd Prize (right next to Oracle), Hyundai Mobis Automobile A/S Part Demand Forecasting

 Research Grant

• Past Meets Future: Deep Learning Innovations in Historical Map Digitization and Infrastructure Insights (PI: Keeheon Lee; 2024-2026)

• Human-Object Interaction-based Visual Understanding for Smart Work / funded by National Research Foundation of Korea (PI: Keeheon Lee; 2021-2024)

• Big knowledge driven automatic hypothesis inference for new bio-knowledge discovery / funded by National Research Foundation of Korea (PI: Min Song, Co: Keeheon Lee; 2021-2022)

• Technology-Society Interaction Data Science: Generative Adversarial Scenario Model for Strategic Planning / funded by National Research Foundation of Korea (PI: Keeheon Lee; Mar. 2017-2020)

• A Study on Knowledge Data Representation and Analysis for Big Data-driven Future Studies/ funded by Yonsei University (PI: Keeheon Lee; May 2017-Current)

• Big Data Analysis for The Historical and Social Origin of Territorial Dispute/ funded by Northeast Asian History Foundation (PI: Whasun Cho Co: Keeheon Lee, Joonsuk Yang, Byung-Jae Lee; June 2017-Current)

• Projects that I conducted before 2016 are: 

• Opiniomics: Analysis and Prediction on Dynamic Public Opinion in Smart Society

• Acropolis 3.0: Big Data Public Opinion Analysis Framework

• Modeling Virtual Markets with Consumers: Socio-Demographic Properties and Social Network: Application to Product Portfolio Optimization

• Social Scientometrics: Social and Psychological Research Dynamics Simulation

• Large-scale Agent-based Distributed Simulation for Product Diffusion and Optimization

• A study on Analytical Hierarchical Process and Analytical Network Process

• Product Diffusion Simulation and Optimal Product Design Based on Consumer Social Network

• Heterogeneous Consumer-Agent Network Simulation Model for New Product Diffusion: Application to Price and Supply Volume Strategy

Articles (other than scientific articles):

• Spatial computing

• 게임현실과 현실의 괴리감을 좁히는 디지털게임기술 경영

• 본질에 충실한 문화관광을 가능하게 하는 과학기술

• Artificial intelligence 

• "국방AI, 인간 살해?…절대로 이런 실험 일어나지 않았다"

• "AI가 인간 조종자 살해? 인간은 무책임하게 AI 사용하지 않아"

• "AI가 인간 조종자 살해? 그렇게 무책임한 프로그램 없어"

• 'AI가 인간 조종자 살해? 그렇게 무책임한 프로그램 없어'

• "AI가 인간 조종자 살해? 그렇게 무책임한 프로그램 없어"