Speakers

원용걸 / Yongkul Won

서울시립대학교 총장 / University of Seoul, President

Opening Ceremony

Opening Ceremony
원용걸
Yongkul Won
서울시립대학교 총장
University of Seoul,
President

김의승 / Eui Seung Kim

서울시 행정1부시장 / Seoul Metropolitan Government, Vice Mayor

Address of welcome

Address of welcome
김의승
Eui Seung Kim
서울시 행정1부시장
Seoul Metropolitan Government,
Vice Mayor

이형일 / HYOUNG IL LEE

통계청장 / Statistics Korea, Commissioner

Congratulatory speech

Congratulatory speech
이형일
HYOUNG IL LEE
통계청장
Statistics Korea,
Commissioner

이숙자 / Suk Ja Lee

서울특별시의회 기획경제위원회 위원장 / Chairman of Planning & Economy Committee, Seoul Metropolitan Council

Congratulatory speech

Congratulatory speech
이숙자
Suk Ja Lee
서울특별시의회 기획경제위원회 위원장
Seoul Metropolitan Council, Chairman of Planning & Economy Committee

박형수 / Hyung-soo Park

서울연구원장 / The Seoul Institute, President

Congratulatory speech

Congratulatory speech
박형수
Hyung-soo Park
서울연구원장
The Seoul Institute,
President

강요식 / Yosik Kang

서울디지털재단 이사장 / Seoul Digital Foundation

Congratulatory speech

Congratulatory speech
강요식
Yosik Kang
서울디지털재단 이사장
Seoul Digital Foundation,
President

이용희 / Yonghee Lee

서울시립대학교 교수 / University of Seoul, Professor

Keynote SessionModerator

Human-Centered Digital Innovation Powered by Big Data & AI

Work Experience
-University of Seoul, Department of Statistics, Seoul, Korea
Professor Aug. 2008 – Present
– Ewha Womans University, Department of Statistics, Seoul, Korea Assistant Professor Mar. 2005 -Jul. 2008
– Forest Research Institute, Jersey City, New Jersey, USA Senior Statistician Feb. 2003 -Mar. 2005

Educational Background
-University of Wisconsin-Madison, Madison, Wisconsin, USA (Ph.D. in Statistics, 2002)
– Seoul National University, Seoul, Korea (M.S. in Statistics, 1992)
– Seoul National University, Seoul, Korea (B.S. in Computer Science and Statistics, 1990)

Keynote Session
이용희
Yonghee Lee
서울시립대학교 교수
University of Seoul,
Professor

일리야 폴로수킨 / Illia Polosukhin

니어 프로토콜 공동창업자 / Near Protocol, Co-Founder

Keynote SessionSpeakers

The Convergence of LLMs and Blockchains

Work Experience
– NEAR Protocol, Co-Founder (2017 to Present)
– Google, Google Research, Engineering Manager (2014 to 2017)

Educational Background
– National Technical University, Kharkiv Polytechnic Institute, Undergraduate &
Master’s Degrees, Applied Math & Computer Science (2013)

Publications & Articles
– “Attention Is All You Need.” (2017)

Short Bio
Illia Polosukhin is Co-Founder of NEAR Protocol, a decentralized developer platform powered
by a sharded smart contract blockchain. NEAR’s vision of a scalable, robust, and highly usable
blockchain began in 2018 when they couldn’t find a protocol that met the needs of builders.
NEAR Protocol launched in 2020 and is focused on scaling to global mainstream adoption with
the Blockchain Operating System. Before NEAR, Illia worked in AI research at Google and co-
authored the landmark paper, “Attention Is All You Need.” Illia has appeared in the Wall Street
Journal, CNBC, Bloomberg, TIME, Wired, New York Magazine, Forbes, and TechCrunch.

Keynote Session
일리야 폴로수킨
Illia Polosukhin
니어 프로토콜 공동창업자
NEAR Protocol,
Co-Founder

김유원 / YUWON KIM

네이버클라우드 대표이사 / NAVER Cloud Corp. CEO

Keynote SessionSpeakers

Corporations’ Strategies for Technical and Ethical Responses in the Era of Hyperscale AI

Generative AI technology is presenting new possibilities for improving productivity for businesses and individuals.
As this technology is no longer a choice but rather something essential, we would like to discuss the mindset and considerations of providers of generative AI services.
As AI technology advances, the importance of building, managing, and utilizing data has never been more important.
In this context, we want to touch upon issues surrounding data and the social and ethical responsibilities businesses should have.

Work Experience
2022.09 ~ CEO / NAVER Cloud Corp.
2017 ~ 2022 Director of Data / NAVER Corp.
2016 ~ 2017 CEO / NHN D&T Corp.
2013 ~ 2017 Director of Data & Marketing / NHN Entertainment
2011 ~ 2013 Director of Data & Information / NHN Corp. (NAVER)
2006 ~ 2011 Division Head of Data Analysis / NHN Corp. (NAVER)

Educational Background
1999 ~ 2003 Ph.D., Statistics, Seoul National University
1995 ~ 1998 M.S., Statistics, Seoul National University
1991 ~ 1995 B.S., Computer Science & Statistics, Seoul National University

Keynote Session
김유원
YUWON KIM
네이버클라우드 대표이사
NAVER Cloud Corp.
CEO

웨이지에 수 / Weijie Su

펜실베니아대학교 교수 / University of Pennsylvania, Associate Professor

Keynote SessionSpeakers

Navigating the Societal Landscape of Generative AI: Opportunities and Ethical Challenges

Weijie Su is an Associate Professor in the Wharton Statistics and Data Science Department and, by courtesy, in the Department of Computer and Information Science, at the University of Pennsylvania. He is a co-director of Penn Research in Machine Learning. Prior to joining Penn, he received his PhD from Stanford University under the supervision of Emmanuel Candes in 2016 and his bachelor’s degree from Peking University in 2011. His research interests span privacy-preserving data analysis, statistical learning, optimization, mechanism design, and high-dimensional statistics. He is a recipient of the Stanford Theodore Anderson Dissertation Award in 2016, an NSF CAREER Award in 2019, an Alfred Sloan Research Fellowship in 2020, the SIAM Early Career Prize in Data Science in 2022, the IMS Peter Gavin Hall Prize in 2022, and the ASA Noether Early Career Scholar Award in 2023.

Work Experience
All at the University of Pennsylvania
7/2022–present Associate Professor, Department of Statistics and Data Science, The Wharton
School
7/2022–present Associate Professor (by courtesy), Department of Computer and Information
Science
7/2019–present Co-Director, Penn Research in Machine Learning (PRiML) Center
7/2021–present Affiliated Faculty, Warren Center for Network and Data Sciences
9/2020–present Affiliated Faculty, AI for Business at Wharton
1/2018–present Affiliated Faculty, Program in Applied Mathematics and Computational Science
7/2016–6/2022 Assistant Professor, Department of Statistics and Data Science, The Wharton
School
7/2020–6/2022 Assistant Professor (by courtesy), Department of Computer and Information
Science

Educational Background
9/2011–6/2016 Ph.D. in Statistics, Stanford University, CA
Advisor: Emmanuel Candès
9/2008–7/2011 B.A. in Economics (minor), Peking University, Beijing
9/2007–7/2011 B.S. in Mathematics, Peking University, Beijing

Short Bio
Weijie Su is an Associate Professor in the Wharton Statistics and Data Science Department
and, by courtesy, in the Department of Computer and Information Science, at the University of
Pennsylvania. He is a co-director of Penn Research in Machine Learning. Prior to joining Penn,
he received his PhD from Stanford University under the supervision of Emmanuel Candes in
2016 and his bachelor’s degree from Peking University in 2011. His research interests span
privacy-preserving data analysis, statistical learning, optimization, mechanism design, and
high-dimensional statistics. He is a recipient of the Stanford Theodore Anderson Dissertation
Award in 2016, an NSF CAREER Award in 2019, an Alfred Sloan Research Fellowship in 2020,
the SIAM Early Career Prize in Data Science in 2022, the IMS Peter Gavin Hall Prize in 2022, and
the ASA Noether Early Career Scholar Award in 2023.

Presentation Summary
Generative AI such as large language models have rapidly emerged as a pivotal innovation in
the realm of machine learning. These technologies raise important questions when their use
affects human decisions. In this talk, we explore three key concerns from a societal viewpoint:
First, how to create fair AI systems that adequately represent and serve minority groups.
Second, the challenge of reliably telling apart the outputs from AI and humans to maintain trust
in digital communications. Third, the complex issue of using data that may be copyrighted to
train these AI models. Throughout this talk, we will tackle these pressing issues of generative
AI, simultaneously shedding light on the substantial opportunities these innovations present.
convergence of LLMs and blockchains. As models become more efficient and compute can
increasingly decentralize, we will see more local, personalized, and affordable instances
of LLMs––provided that the industry begins to embrace more open source approaches to
governance, decentralized inference, and crowdsourced data. Finally, Illia will illustrate how AI is
transforming the future of work and the potential for AI agent frameworks to scale businesses,
communities, and research initiatives.

Keynote Session
웨이지에 수
Weijie Su
펜실베니아대학교 교수
University of Pennsylvania, Associate Professor

이정훈 / Jung Hoon LEE

서울시 디지털명예시장 / Seoul Metropolitan Government, Digital Honor Mayor / Graduate School of Information, Professor

Keynote SessionPanel

Work Experience
-The Honorary Mayor of Digital, Seoul Metropolitan
Government
-Chair & Advisory Member of Seoul Smart City Committee (2018-2022)
-Working Member of National Data Policy, Repulic of Korea
-Advisory Member of National Smart City Committee, Repulic of Korea

Educational Background
-Dept. of Engineering, University of Cambridge, PhD.
-Dept. of Management, London School of Economics, University of London, MSc
-Dept. of Electrical Electronic Engineering, University of Manchester

Publications & Articles
-2022 Smart Cities Index Report

Keynote Session
이정훈
Jung Hoon LEE
서울시 디지털명예시장
Seoul Metropolitan Government, Digital Honor Mayor / Graduate School of Information, Professor

고준형 / JoonHyung Koh

SAS Korea 이사/ SAS Korea, Senior Consultant

Keynote SessionPanel

Work Experience
– 2007년 ~ 현재 : SAS Korea – Data Scientist
– 2004년 ~ 2007년 : MCG Consulting – Risk Consultant
– 2000년 ~ 2004년 : SAS Korea – CRM Consultant

Keynote Session
고준형
JoonHyung Koh
SAS Korea 이사
SAS Korea,
Senior Consultant

변미리 / MIREE BYUN

서울연구원 본부장 / The Seoul Institute, Division Director

Session1Morderator

Work Experience
– Division Director, Office of Inclusive City Research, Seoul Institute
– Director, Urban Monitoring Center, Seoul Institute

Educational Background
-Seoul National University (major in Sociology) BA
-Seoul National University (major in Sociology) MA
-Seoul National University (major in Sociology) Ph.D

Publications & Articles
– Seoul at a Glance (2022)
– Seoul Survey (2022)
– Future Generation in Seoul (2019)
“An Empirical Analysis of the spatial Distribution and Flow Patterns of Seoul’s Single-Person Households”(2019)
“Is Seoul Socially innovative?”(2019)

Session1
변미리
MIREE BYUN
서울연구원 본부장
The Seoul Institute,
Division Director

김현성 / Hyunsung Kim

서울시립대학교 교수 / University of Seoul, Professor

Session1Speakers

전자정부의 역사와 행정혁신 / The Evolution of E-government and Administrative Innovation

E-government is defined as an innovative government that applies information technology to perform internal administrative tasks and external public services, thereby achieving new value in the era of knowledge-based society. If we admit that e-government practice is the application of electronic tool to the official administrative work, the first case of e-government can be traced back to the U.S. government’s population census work in 1890. However, at least requiring huge administrative databases and high-speed networks for the modern society, the first example of contemporary e-government practice can be traced back to the late 20th century.

In the case of South Korea, the government first introduced computers in 1967. Subsequently, through administrative computerization and the national computer network project, a nationwide information technology initiative was promoted in the mid-1990s. With the enactment of the e-Government Act in the 21st century, South Korea has been developing e-government services in earnest, reaching its current status. The South Korea’s e-government is positioned at the top in the evaluations by various international organizations including UN, taking on a leading role in the world.

Despite these achievements, e-government today continues to demand continuous change and improvement. Information and communication technology is advancing day by day, and the expectations by citizens are also increasing. If e-government merely relies on the adoption of advanced technology to enhance convenience and efficiency in providing information and administrative services, it would be inadequate. E-government must be an innovative government that embodies the values of administration demanded in the new era. Therefore, it should pursue (1) a seamless unified government, (2) an inclusive e-government accessible to all, (3) a smart e-government with proactive administrative services, and (4) a trustworthy, transparent, and secure e-government. Such mature e-government can realize an efficient and competitive government, a democratic and transparent administration, and enhance the quality of life for the citizens.

Work Experience
– Assistant, Associate, Full Professor, Department of Public
Administration, University of Seoul (1998~Present)
– Dean, College of Public Affaires and Economics,
University of Seoul (2022~Present)
– Director, Electronic Government Research Institute(EGRI),
University of Seoul (2003~2005)

Educational Background
– B.A., Public Administration, Yonsei University, 1986
– M.A., Public Administration, Yonsei University, 1988
– Ph.D., Public Administration
University of Southern California
School of Public Administration, 1995

Publications & Articles
-Ph.D. Dissertation
“The Organizational Effectiveness of Public Management Information Systems in Korea: A Principal-Agent Perspective,” USC, 1995.
– “Reinventing the Electronic Citizen Service through the Digital Signature Certification Systems,” Journal of Korean Association for Regional Information Society, 6:2, 2003.
– “A Critic of the Relationship between On-line Citizen Participation and Electronic Democracy : Comparison of Responsiveness and Collaboration,” Social Science Research Institute, Vol. 22, No. 1, 2006.

Session1
김현성
Hyunsung Kim
서울시립대학교 교수
University of Seoul,
Professor

이정환 / Jeonghwan Lee

서울디지털재단 책임연구원 / Seoul Digital Foundation, Principal Manager

Session1Speakers

Changes in Administrative Education of Public Officials’ Data according to the Appearance of GenAI

Work Experience
-Seoul Digital Foundation
-Korea Small Business Institute

Educational Background
-Completion of Ph.D. in Graduate Program in Technology Policy, Yonsei Univ
-Master of Business Administration, Hankuk Univ of Foreign Studies
-Bachelor of Business Administration, Hankuk Univ of Foreign Studies

Publications & Articles
-Seoul Generative AI Ethics Guidelines(2023)

Presentation Summary
Since the introduction of ChatGPT 3.5 on November 30, 2022, the world has been captivated
by generative AI. Prominent research institutions globally have started analyzing the impact of
generative AI on fields such as medicine, education, design, law, arts, and employment. Private
enterprises are striving to achieve economic benefits through generative AI, and governments
are contemplating institutional measures to foster the generative AI industry and minimize its
societal side effects. In essence, the entire world is keenly aware of the positive and negative
impacts of generative AI. Among various sectors, the education field is adapting most agilely
to generative AI. Educational institutions worldwide are swiftly conducting research on how
to apply generative AI and are making efforts to successfully integrate it into their systems.
Many universities, both domestically and internationally, are providing guidelines for utilizing
generative AI like ChatGPT, and educational programs targeting professionals and the general
public are proliferating. At the secondary education level, Seoul, in South Korea, have been
preparing for generative AI education since March 2023, releasing materials such as ‘Seoul-
style Artificial Intelligence Ethics Education’ and ‘AI Fundamentals for Teachers.’ Incheon,
Busan, Gyeongsangbuk-do, and other regional authorities are also gearing up for generative
AI education, starting as early as March or as late as May. In summary, education is focusing
on learner-driven utilization and is evolving its methods towards utilizing AI and fostering
collaboration. The core topic of this study, like other educational fields, concerns the direction
in which administrative education will move in the era of generative AI.
To address this, the study aims to: Firstly, examine the socioeconomic changes brought about
by generative AI, analyze trends in the education sector, and explore the developments in
generative AI-related education. Secondly, assess the current status of data administration
education and investigate how the demand for data administration education is changing
through macroscopic trend analysis and comparisons. Thirdly, examine the case of data
administration education at Seoul Digital Foundation, which is considered a successful example
in the current era of generative AI, and analyze representative work application cases of
learners. Lastly, propose the direction of data administration education.
Generative AI’s educational application is still in its early stages. Therefore, real-world cases
are crucial at this juncture since there is limited accumulation of examples and theories. In this
regard, the significance of the case studies in this research is substantial. However, limitations
exist due to the relatively small proportion of case studies and the weak theoretical background
of the convergence between generative AI and education, which hinder providing a profound
direction.

Session1
이정환
Jeonghwan Lee
서울디지털재단 책임연구원
Seoul Digital Foundation, Principal Researcher

김준철 / Junchul Kim

서울연구원 연구책임자 / The Seoul Institute, Associate Research Fellow

Session1Speakers

Development of AI-enabled Smart Counseling System of Dasan Call Center

To establish a smart Dasan Call Center for innovative counseling services, this project considers the maturity of artificial intelligence (AI) technology to alleviate discomfort for Seoul citizens and improve counseling services. Additionally, a smart strategy has been established based on on-site attendance and analysis of counseling data, enabling environmental and situational analyses to improve counseling services. A pilot service has been developed to analyze currently available counseling data on “illegal parking complaints” in a specific field and identify suitable elements for counseling centers, data collection, analysis, and processing methods, while also taking into account the maturity and limitations of each technology element. Considering the current limitations of technology and the medium- to long-term strategy of transitioning to a smart contact center, generative AI can also be applied to advance AI counseling systems. By realizing the innovation of the smart counseling construction plan in this study, we expect efficient responses to incoming calls despite connection delays, improved citizen satisfaction through quick and efficient handling of complaints, and increased efficiency through AI automation of simple and repetitive counseling tasks.

Work Experience
-The Seoul Institute, 2023~current
-The Seoul Institute of Technology, 2019~2023
-Melbourne eResearch Group, The University of Melbourne, 2017~2019

Educational Background
-Ph.D, Geomatics, IE, The University of Melborune
-M.E., Geoinformatic Eng., Inha University
-B.E., Computer Science, Inha University

Publications & Articles
-Development of AI-enabled Smart System of Dasan Call Center, 2022
-Establishment of AI-enabled detection and removal system of digital sexual crime content, 2022
-Data Science-based Intelligent Video Surveillance System for Selectively Monitoring CCTV Cameras on Han River Bridges, 2021
-Establishment of Data Science System for Seoul Metropolitan Area, 2020

Session1
김준철
Junchul Kim
서울연구원 연구책임자
The Seoul Institute, Associate Research Fellow

전종준 / Jong-June Jeon

서울시립대학교 교수 / University of Seoul, Professor

Session1Speakers

Development of a sustainable and customized large language model in public domain

Large language models developed and deployed thus far have been driven in the leading artificial intelligence industry. The substantial costs associated with developing and maintaining the artificial intelligence model as a service have rendered the customization, development, and deployment of tailored models nearly infeasible in environments prioritizing data protection.
This study explores methods to construct an artificial intelligence language model within public domain, enabling the cost-effective utilization of such technology. It investigates approaches for data management, model training, and service management required for sustaining the development of customized large-scale language models. Additionally, it examines strategies essential for the sustainable development and maintenance of personalized large-scale language models, illustrated through a case study involving an artificial intelligence language model implemented at the University of Seoul.

Work Experience
• Director, Urban Bigdata & AI Institute (2023-)
• Vice director, Office of research affairs, Univsersity of Seoul (2021-2022)
• General Director, Convergence and Open Sharing System (Bigdata), Univsersity of Seoul (2021)
• General Director for Statistics and Data, Seoul Metropolitan Government (2019-2020)
• Professor, University of Seoul (2014-)

Educational Background
• Ph.D Department of Statistics, Seoul National University – High dimensional ranking model
• B.S.School of Business Administration, Seoul National University

Publications & Articles
• Causally Disentangled Generative Variational AutoEncoder”, ECAI 2023
• An, S. and Jeon J. J. (2023), “Distributional Variational AutoEncoder To Infinite Quantiles and Beyond Gaussianity”, NeuRIPS 2023
• Oh C., So J., Byun H., Lim Y., Shin M., Jeon J., Song.K (2023), Geodesic Multi-Modal Mixup for Robust Fine-Tuning, NeuRIPS 2023

Session1
전종준
Jong-June Jeon
서울시립대학교 교수
University of Seoul,
Professor

윤충식 / Chung Sik Yun

서울시 빅데이터담당관 / Seoul Metropolitan Government, Big Data Division Director

Session1Panel

Work Experience
– ICT Management Division’s Director, Ministry of Environment(2021~2023)
– Deputy Director, Ministry of the Interior and Safety(2017~2021)
– Consulting Division;s Managing Director, Oracle Korea (2012~2015)

Educational Background
– Graduate School of Business IT, Kookmin University, Ph.D (2023.2)
– Graduate School of Technology of Management, Sungkyunkwan University, Master’s Degree(2001,8)
– Sungkyunkwan University, bachelor’s degree(1993.2)

Publications & Articles
– A study on demand forecasting and the location analysis of elementary care centers(2023.2)
– The Case Study for Childcare Service Demand Forecasting Using Bigdata Reference Analysis Model(2022.12)
– A Study on Data-driven administration(2018.11)

Session1
윤충식
Chung Sik Yun
서울시 빅데이터담당관
Seoul Metropolitan Government,
Big Data Division Director

김상일 / Sang-il Kim

서울연구원 선임연구위원 / The Seoul Institute, Senior Research Fellow)

Session1Panel

Work Experience
2023. 11 – Present Division of Urban Planning and Design Research
2020. 1 – 2023.10 Director of Department of Urban Data and Information
2017. 7 – 2019.12 Director of Department of Urban Planning, Design, and Housing
2014. 7 – Senior Research Fellow
2012. 4 – 2014. 5 Director of Urban Information Center
2011. 6 – 2012. 3 Head of Urban Data and Information Team
2008. 1 – 2010. 3 Editorial Committee Member, Seoul Urban Study (a academic journal that published by the Seoul Institute)
2002.11 – Research Fellow, The Seoul Institute

Educational Status
2001. 2 Ph.D of Urban Planning, Graduate School of Seoul National University
1995. 2 Master of Urban Planning,Graduate School of Seoul National University
1993. 2 Department of Urban Engineering, Seoul National University

Session1
김상일
Sang-il Kim
서울연구원 선임연구위원
The Seoul Institute,
Senior Research Fellow

박재휘 / Jaehui Park

서울시립대학교 교수 / University of Seoul, Associate Professor

Session2Morderator

Work Experience
– Mar. 2022-present Associate Professor, University of Seoul
– Mar. 2020-Feb. 2022 Assistant Professor, University of Seoul
– Mar. 2018-Feb. 2020 Assistant Professor, Incheon National University
– Sep. 2012- Feb. 2018 Research Engineer, Electronics and Telecommunications Research Institute (ETRI)

Educational Background
– 2012 Ph.D., Computer Science and Engineering, Seoul National University, Seoul, Korea
– 2008 M.S., Computer Science and Engineering, Seoul National University,Seoul, Korea
– 2005 B.S., Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea

Publications & Articles
– Soyun Shin, Jaehui Park and Moonwook Ryu. 2023. Integrating Heterogeneous Graphs Using Graph Transformer Encoder for Solving Math Word Problems. IEEE ACCESS, Volume 11, pp. 27609-27619
– Yeonchan Ahn, Sang-goo Lee, Junho Shim and Jaehui Park. 2022. Retrieval-Augmented Response Generation for Knowledge-Grounded Conversation in the Wild. IEEE ACCESS, Volume 10, pp. 131374-131385
– Yeonchan Ahn, Sang-goo Lee and Jaehui Park. 2020. Exploiting Text Matching Techniques for Knowledge-Grounded Conversation. IEEE ACCESS, Volume 8, pp. 126201-126214

Session2
박재휘
Jaehui Park
서울시립대학교 교수
University of Seoul, Associate Professor

리완 / Wan Li

케임브리지대학교 교수 / University of Cambridge, Associate Professor

Session2Speakers

Beyond big data – what else is needed for smarter cities?

Dr Li Wan, Associate Professor in urban planning and development at the Department of Land Economy, University of Cambridge. He is the Director for the MPhil in Planning, Growth and Regeneration (PGR) programme, and Fellow of Gonville and Caius College. Dr Wan is interested in interdisciplinary modelling of urban land use and transport systems. His recent research interests include strategic planning at the city/regional level, impact study of flexible working, micromobility and electric vehicles, and transport decarbonisation. Dr Li Wan is a co-investigator of the Centre for Smart Infrastructure and Construction and a Trustee of the IJURR Foundation. His new book: Digital Twins for Smart Cities (2023).

Presentation Summary
The rise of urban big data has opened new frontiers for understanding, planning and managing
cities. But some clarifications and reflections should be made in terms of the processes and
challenges of translating data through analytics into objective and actionable policy insights,
and subsequently informing the development of policy options, solutions and visions in a multi-
stakeholder setting. This presentation will revisit some of the critical lessons from the early
smart-city movement and then discuss some major and recurring challenges and limitations
of utilizing big geospatial data set and digital technology (e.g. city digital twin) in city planning
through a few international case studies. Some propositions on the potential use of big data for
city planning are proposed for discussion.

Session2
리완
Li Wan
케임브리지대학교 교수
University of Cambridge, Professor

Saeed AlShahrani

Saeed AlShahrani / SDAIA, Smart Riyadh Operation Center, General Manager

Session2Speakers

Work Experience
– Smart Riyadh Operation Center General Manager
– Enterprise Architecture Research Manager
– Founder and CEO of Qantarah Fintech Company

Educational Background
– 2011 M.S Information Technology, Carnegie Mellon University Pittsburgh, USA
– 2006 B.S. Computer Science, Saint Louis University, Saint Louis, MO, USA

Presentation Summary
Having a smart national platform can be a great addition; however, how can a smart platform
be on top of all cities’ platforms yet be simple and provide situational awareness as well as
other use cases and features
smart platforms provide. This seems the natural evolution of smart city platforms. In this
presentation, we will discuss SDAIA’s experience in this area and challenges faced.

Session2
Saeed AlShahrani
SDAIA, Smart Riyadh Operation Center, General Manager

김상일 / Sang-il Kim

서울연구원 선임연구위원 / The Seoul Institute, Senior Research Fellow

Session2Speakers

Trends in Urban Change in Seoul Through Trips and Migration

Trips and migration imply a lot of information about a city and its changes. This presentation is an omnibus of attempts to read the characteristics of Seoul and its changes under the theme of ‘population’ by utilizing traffic data based on mobile phone location information and migration data based on resident registration. By analyzing the time and purpose of passage, origin and destination of population groups by gender and age, we can read trends in the centrality and changing functions of the city center. By identifying travel distances and travel times, we hope to gain implications for a more efficient urban spatial structure. We will identify who is clustered in which neighborhoods, and we will use single-year migration data to infer where people are migrating along the life cycle.

Work Experience
2023. 11 – Present Division of Urban Planning and Design Research
2020. 1 – 2023.10 Director of Department of Urban Data and Information
2017. 7 – 2019.12 Director of Department of Urban Planning, Design, and Housing
2014. 7 – Senior Research Fellow
2012. 4 – 2014. 5 Director of Urban Information Center
2011. 6 – 2012. 3 Head of Urban Data and Information Team
2008. 1 – 2010. 3 Editorial Committee Member, Seoul Urban Study (a academic journal that published by the Seoul Institute)
2002.11 – Research Fellow, The Seoul Institute

Educational Status
2001. 2 Ph.D of Urban Planning, Graduate School of Seoul National University
1995. 2 Master of Urban Planning,Graduate School of Seoul National University
1993. 2 Department of Urban Engineering, Seoul National University

Session2
김상일
Sang-il Kim
서울연구원 선임연구위원
The Seoul Institute,
Senior Research Fellow

원유복 / YuBok WON

서울특별시 통계데이터전문관 / Seoul Metropolitan Government, Statistical Data Specialist

Session2Speakers

Work Experience
– Seoul Metropolitan Government, Statistical Data Specialist
– Overall Management of Big Data Analysis for Implementing Data-Driven Administration in
Seoul Metropolitan Government
– Planning and Policy Research for the Development and Integration of Communication Data,
including Seoul’s Resident Population

Educational Background
M.S. Department of Statistics , Korea University

Publications & Articles
Estimation of de facto population in Seoul Analysis of Total Crime Count Data Based on Spatial
Association Structure
– Analysis of Violent Crime Count Data Based on Bivariate Conditional Auto-Regressive Model
– A Study on Influence Factors on Citizen’s Satisfaction Level
(Case of the Survey on Citizen’s Satisfaction Level for Administrative Services of Seoul City)

Presentation Summary
Seoul Metropolitan Government has felt the limitations of explaining a complex and ever-
changing society using only public data like the registered population. Since 2018, the city has
introduced new concepts of population and has been utilizing these in various policies including
safety, tourism, and commercial areas. The presentation topic includes collaborative research
achievements and applications derived from the fusion analysis of private big data and public
data. Moreover, in response to the increased importance of logistics policy during the COVID-19
period, the city developed living logistics data and, more recently, has been developing
and utilizing real-time urban data. Among these, today I will introduce data on Seoul’s living
population and living movement.

Session2
원유복
YuBok WON
서울특별시 통계데이터전문관
Seoul Metropolitan Government, Statistical Data Specialist

조정우 / Jungwoo CHO

한국교통연구원 부연구위원 / Korea Transport Institute, Associate Research Fellow

Session2Panel

Work Experience
-Postdoc, Applied Science Research Institute, KAIST (‘20-’21)
-Associate Research Fellow, Korea Transport Institute (‘21-current)

Educational Background
-BA., Civil and Environmental Engineering, KAIST (‘14)
-MS., Civil and Environmental Engineering, KAIST (‘15)
-Ph.D. in Transportation Engineering, Civil and Environmental Engineering, KAIST (‘20)

Publications & Articles
Cho, J., & Yoon, Y. (2018). How to assess the capacity of urban airspace: A topological approach using keep-in and keep-out geofence. Transportation Research Part C: Emerging Technologies, 92, 137-149.
Vascik, P. D., Cho, J., Bulusu, V., & Polishchuk, V. (2020). Geometric approach towards airspace assessment for emerging operations. Journal of Air Transportation, 28(3), 124-133.
Cho, J., & Yoon, Y. (2021). Extracting the topology of urban airspace through graph abstraction. Transportation Research Part C: Emerging Technologies, 127, 103116.
Yoon, Y. & Cho, J. (2020). Method for identifying available airspace for unmanned aerial vehicle operations, KR Patent 10-2070817
Yoon, Y., Kim, S. & Cho, J. (2019). Risk evaluation method for Unmanned Aerial Vehicle flight routes in the three-dimensional grid space, KR Patent 10-2013664-0,000

Session2
조정우
Jungwoo CHO
한국교통연구원 부연구위원
Korea Transport Institute,
Associate Research Fellow

스티븐 취엔 / Steven Jige Quan

서울대학교 환경대학원 교수 / Graduate School of Environmental Studies SNU, Associate Professor

Session2Panel

Work Experience
– Associate Professor, Graduate School of Environmental Studies, Seoul National University
– Assistant Professor, Graduate School of Environmental Studies, Seoul National University
– Lecturer/Postdoc Fellow, College of Design, Georgia Institute of Technology
– Department Chief Planner, Tsinghua Urban Planning & Design Institute

Educational Background
– PhD in City and Regional Planning, College of Design, Georgia Institute of Technology
– MS in Computer Science, College of Computing, Georgia Institute of Technology
– ME in Urban Planning, College of Architecture, Tsinghua University
– BArch (5-year), College of Architecture, Tsinghua University

Publications & Articles
– Bansal, P. & Quan, S. J.* Examining temporally varying nonlinear effects of urban form on urban
heat island using explainable machine learning: A case of Seoul. Building and Environment 247,
110957. 2023.
– Quan, S. J. & Kim, K. Did new electricity progressive tariff system change energy usage pattern
in Seoul apartments? Evidence from integrated multisource dataset and combined analytical
models. Energy and Buildings 287, 112979. 2023.
– Bansal, P. & Quan, S. J.* Relationships between building characteristics, urban form and building
energy use in different local climate zone contexts: An empirical study in Seoul. Energy and
Buildings 272, 112335. 2022.
– Quan, S. J. Urban-GAN: An artificial intelligence-aided computation system for plural urban
design. Environment and Planning B: Urban Analytics and City Science 49(9). 2022.
– Quan, S. J.*, Park, J., Economou, A., & Lee, S. Artificial intelligence-aided design: Smart Design
for sustainable city development. Environment and Planning B: Urban Analytics and City Science
46(8), 1581-1599. 2019.

Session2
스티븐 취엔
Steven Jige Quan
서울대학교 환경대학원 교수
Graduate School of Environmental Studies SNU, Professor

최준영 / Junyoung CHOI

서울연구원, 본부장 / The Seoul Institute, Research fellow

Session3Morderator

Work Experience
– Nov, 2023 ~ , Research fellow, Seoul Institute
– May, 2020 ~ Oct 2023, Research fellow, Seoul Institute of Technology(SIT)
– Jan 2021 ~ June 2022, Director of Center for Data Science, SIT
– Feb 2023 ~ , Chair of Big Data Research Committee, Korea Planning Association(KPA)

Educational Background
– Aug 2011, Ph.D., Urban Planning, Hanyang Univ.
– Feb 2001, M.E., Urban Planning, Hanyang Univ.
– Feb 1999, BSc, Urban Planning, Hanyang Univ.

Publications & Articles
– Choi, J. Y., Choi, S. B., Lee, J. H., Kim, T. H., & Im, W. S. (2023). DESIGNING A FOSS4G-BASED WALKABLE LIVING AREA PLANNING SUPPORT MODULE TO ASSISTS THE KOREAN 15-MINUTE CITY. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 48, 19-24.
– Choi et al. (2023) Development of an Integrated Lifecycle Service with a Focus on Moving and Residence (Korean), SIT
– Choi, J., & Kim, H. M. (2021). State-of-the-art of Korean smart cities: A critical review of the Sejong smart city plan. Smart Cities for Technological and Social Innovation, 51-72.

Session3
최준영
Junyoung CHOI
서울연구원, 본부장
The Seoul Institute,
Research fellow

이원재 / Won Jae Lee

서울시 데이터분석가 / Seoul Metropolitan Government, Big Data Analyst

Session3Speakers

Leveraging real-time big data to transform city services

Real-time big data is generated by the countless sensors around us.
With the advancement of real-time data processing technology, it has become possible to provide rapidly analysed real-time information to individuals in the city.

Seoul Metropolitan Government has developed “Seoul Real-time City Data”, which analyses and fuses public data such as traffic and environment, and private data such as communication and consumption in real time.
The data includes real-time key information about the city and predictive information using AI technology.
The data is also updated in real time and made available to the public through the Seoul Open Data Plaza.

In this presentation, I will introduce ‘Seoul Real-Time City Data’ and explore how it has revolutionised the public sector and how it will change the lives of citizens in the future.

Work Experience
– [2015~2016] Nonghyup Bank (Card Division)
– [2016~Now] Seoul Metropolitan Government (Big Data Division)

Educational Background
– The University of Seoul. Statistics BS.

Session3
이원재
Won Jae Lee
서울시 데이터분석가
Seoul Metropolitan Government,
Big Data Analyst

오미애 / Miae Oh

한국보건사회연구원 정보통계연구센터장 / Korea Institute for Health and Social Affairs, Head of Center for Research on Statistics and Information

Session3Speakers

Policy Utilization of Big Data in the Health and Welfare Sector

Work Experience
– Research Fellow/ Head, Korea Institute for health and social affairs (Dec.2012 – date)
– Adjunct Professor, ChungNam National University(Sep.2020 – Aug.2022)

Educational Background
– Ph.D. in Statistics, Seoul National University(Mar.2006-Feb.2013)
– B.S. in Statistics, Ewha Womans University(Mar.2001-Aug.2005)

Publications & Articles
– A Study on Fake News Detection through Machine Learning in the Health and Social Welfare(2022), Korea Institute for health and social affairs
– A Study on the Applicability and Prospect of Digital Technology in the Health and Social Welfare(2022), Korea Institute for health and social affairs
– A study on the model for detecting emerging issues in health and social welfare(2022), National Research council for economics, humanities and social sciences

Presentation Summary
In the field of health and welfare, there is a welfare blind spot detection system created as a
result of innovation in the public sector using AI, which was prompted by the suicide case of
the Songpa mother and her two daughters. This system collects risk signal information such as
electricity, water, and gas cut-offs to uncover and support the vulnerable populations in welfare
blind spots. It uses big data analysis to identify at-risk groups and shares the list of individuals
with local governments. In this presentation, we would like to introduce the welfare blind spot
detection system, as well as discuss a system for detecting children in crisis and research
related to re-abuse.

Session3
오미애
Miae Oh
한국보건사회연구원 정보통계연구센터장
Korea Institute for Health and Social Affairs, Head of Center for Research on Statistics and Information

우찬균 / Chankyun Woo

통계개발원 통계방법연구실 주무관 / Statistics Research Institute Data Science Team, Assistant Deputy Director

Session3Speakers

Statistical Pioneering : AI-Driven Statistical Classification

Statistical classification takes up a lot of time and manpower at Statistics Korea. And it is so important that it is used in more than 31 types of statistical surveys.
For this important task, Statistics Korea’s Statistics Research Institute has introduced machine learning technology to improve statistical classification work faster and more efficiently.
As part of the Digital Public Service Innovation Project organized by the Ministry of Science and ICT in 2022, the system was developed with the National Information society Agency (NIA) and is currently used by Statistics Korea for statistical classification.

Work Experience
-2018 / Statistics Korea Survey System management Division
-2014 / Statistics Korea Statistical Service Planning Division

Educational Background
– M.S. in Bigdata convergence and Natural Language Processing at Korea University Graduate
School of Computer & Information Technology

Publications & Articles
– Korean Standard Industry Classification Multilingual Classification Using Data Augmentation
(KSC 2022)
– Comparison of Korean Standard Industrial Classification Automatic Classification Model on
Deep Learning (ASK 2020)

Session3
우찬균
Chankyun Woo
통계개발원 통계방법연구실 주무관
Statistics Research Institute Data Science Team,
Assistant Deputy Director

소우야마 벤 다우 / Soumaya Intissar BEN DHAOU

UNU센터 연구원 / UNU-EGOV, Research Specialist

Session3Speakers

Global assessment for responsible AI in cities

Educational Background
– Ph.D. in Information Systems and Technology and Digital Governance from a joint program of
University of Quebec in Montreal, Concordia University, HEC Montreal, and McGill University
in Canada.

Publications & Articles
•Isagah, T., & Ben Dhaou, S. I. (2023, July). Problem Formulation and Use Case Identification
of AI in Government: Results from the Literature Review. In Proceedings of the 24th Annual
International Conference on Digital Government Research (pp. 434-439).
•Charmaine Distor, Soumaya I. Ben Dhaou, Morten Meyerhoff Nielsen (2023) Metaverse vs.
metacurse: The role of governments and public sector use cases EGOV-CeDEM-ePart-2023
•Inês Campos Ruas, Soumaya I. Ben Dhaou, Zoran Jordanoski (2023) Blockchain and the GDPR
– the shift needed to move forward EGOV-CeDEM-ePart-2023

Short Bio
Soumaya Ben Dhaou is Research Specialist at the United Nations University Operating Unit on
Policy-driven Electronic Government (UNU-EGOV), a think-tank devoted to multidisciplinary
research on how digital transformation may contribute to empowered democratic citizenship,
trustworthy public infrastructures, more inclusive societies and, in broad terms, to sustainable
development. She is coordinating the research line on “Digital transformation, Innovation
and Emerging Technologies”, investigating the potentials of emerging technologies such as
Blockchain, Artificial Intelligence, IoT and Data Analytics and their impact on transforming
urban centres and settlements, Government and public service. She is investigating with her
team “the leapfrogging strategies with emerging technologies in Africa” and exploring the
implications of the most recent technologies such as Metaverse and ChatGPT on Government
and Public Service. She is committed to advancing smart cities and digital governance for
sustainable development. With a strong focus on innovation and emerging technologies, her
work encompasses various dimensions of urban transformation.
Currently, she is collaborating with UN-HABITAT on a global survey assessing the responsible
use of AI in cities. This project exemplifies her dedication to exploring cutting-edge
technologies for urban development. Soumaya is lead contact for UNU-EGOV collaboration
with the International Telecommunications Union (ITU) where she was responsible for a number
of working groups under the U4SSC (United 4 Smart Sustainable Cities Communities) and led
the Blockchain for cities project and co-lead “simple way to be smart” focusing on smart cities
and digital governance, emphasizing the need for efficient, inclusive, and sustainable urban
development.

Presentation Summary
Statistical classification takes up a lot of time and manpower at Statistics Korea. And it is so
important that it is used in more than 31 types of statistical surveys.
For this important task, Statistics Korea’s Statistics Research Institute has introduced machine
learning technology to improve statistical classification work faster and more efficiently.
As part of the Digital Public Service Innovation Project organized by the Ministry of Science and
ICT in 2022, the system was developed with the National Information society Agency (NIA) and
is currently used by Statistics Korea for statistical classification.

Session3
소우야마 벤 다우
Soumaya Intissar BEN DHAOU
UNU센터 연구원
UNU-EGOV,
Research Specialist

노승철 / Seung Chul Noh

한신대학교 교수 / Han Shin university, Assistant Professor

Session3Panel

Work Experience
– 2015~2021,Seoul Institute(Researcher / Bigdata analytics Team Leader)
– 2013~2014, The Korea Rural Economics Institute(Researcher)

Educational Background
– 2013 PhD Seoul University, Urban Planning
– 2009 M.A Seoul University, Urban Planning
– 2006 B.S Jung Ang University, Architect

Publications & Articles
2021, Seung Chul, Noh and Jung-Ho Park, “Café and Restaurant under My Home: Predicting Urban Commercialization through Machine Learning”,
2020, Sanghyo Kim, Kyei-Im Lee, Seong-Yoon Heo and Seung-Chul Noh, 2020.10, “Identifying Food Deserts and People with Low Food Access, and Disparities in Dietary Habits and Health in Korea”
2013, Advanced statistical analysis(book), Seoul:

Session3
노승철
Seung Chul Noh
한신대학교 교수
Han Shin university,
Assistant Professor

박지혜 / Jihye Park

서울디지털재단 책임연구원 / Seoul Digital Foundation, Principal Researcher

Session3Panel

Work Experience
– Sep 2019 ~ Present : Principal Researcher, AI&Big Data Team, Seoul Digital Foundation
– Jun 2017 ~ Aug 2019 : Research Specialist, Future Planning Center, Chungbuk Research Institute

Educational Background
– Ph.D. in Business Administration, Kyung Hee University, Korea (2018)
※ Integrated Master’s and Doctorate Program
– B.A. in Business Administration, Kyung Hee University, Korea (2013)

Publications & Articles
– JH., Park., HJ., Yoon., & JH., Park.(2019), The interaction effects of information cascades, system recommendations and recommendations on software downloads, Online Information Review.
– JH., Park., JS., Park., & JH., Park.(2018), The Effects of User Engagements for User and Company Generated Videos on Music Sales: Empirical Evidence From YouTube, Frontiers in Psychology.
– JH., Park., & JH., Park.(2016), Investigating the Influence of a Food-Themed TV Program on Delivery Food Order Amount Using Big Data with Difference-in-Differences Method, Information Systems Review.

Session3
박지혜
Jihye Park
서울디지털재단 책임연구원
Seoul Digital Foundation,
Principal Researcher

주성환 / Sunghwan Ju

서울디지털재단 경영전략실장 / Seoul Digital Foundation , General Manager

Session4Morderator

Work Experience
– General Manager of the Seoul Digital Foundation

Educational Background
– Ph.D of Business Administration

Session4
주성환
Sunghwan Ju
서울디지털재단 경영전략실장
Seoul Digital Foundation ,
General Manager

목광수 / Kwangsu Mok

서울시립대학교 교수 / University of Seoul, Professor

Session4Speakers

The Ethics of AI and Big Data for Sustainable Development and Prosperity

In this presentation, I will argue that an ethics of AI and big data is needed in the AI and big data era to ensure that AI and big data can be used sustainably for prosperity and development. This is because if we fail to effectively address the ethical issues raised by AI and big data technologies, and if we lose the trust of citizens as data providers, we will not be able to obtain the continuous supply of high quality data that is necessary for the sustainable use of AI. The ethics of AI and big data needs to be systematically established through a proper relationship between the three tiers of theory, institutions, and individuals for “ethics realization,” effectively engaging and cooperating through a division of labor. At present, the ethics of the individual tier, which is necessary for the realization of ethical values, has received relatively less attention and needs to be strengthened. To this end, I propose a virtue-based AI ethics model for AI professionals and citizens, which effectively contributes to motivating their normativity in the first-person perspective.

Work Experience
– University of Seoul, Dept. of Philosophy, Professor (2016.03 ~ )
– Gyeongsang National University, Dept. of Philosophy, Professor (2011.09 ~ 2016.02)

Educational Background
– Michigan State University, Dept. of Philosophy, Ph.D (2009.5)
– Seoul National University, Dept. of Philosophy, M.A. (2002.2)
– Seoul National University, Dept. of Philosophy, B.A. (2000.2)

Publications & Articles
– 단독 저서『루치아노 플로리디, 정보 윤리학』(2023, 컴북스)
Luciano Floridi, The Ethics of Information
– 단독 저서『정의론과 대화하기』(2021, 텍스트큐브)
Conversations with John Rawls’s Theory of Justice
– 공동 저서『인공지능의 윤리학』(2019, 한울)
Ethics of Artificial Intelligence
– “An Artificial Intelligence Ethics for Professionals”(『철학논총』Vol.102(4), 2020)
– “Classifying Three Tiers of Ethics and Exploring Their Relationship in the Era of Science and
Technology: Focusing on Artificial Intelligence Ethics” (『범한철학』Vol.98(3), 2020)

Session4
목광수
Kwangsu Mok
서울시립대학교 교수
University of Seoul,
Professor

황원석 / Wonseok Hwang

서울시립대학교 교수 / University of Seoul, Assistant Professor

Session4Speakers

Reconsidering AI application in the legal domain

Recent advancements in deep learning for AI have shown remarkable performance across numerous NLP tasks in legal domain. In particular, GPT-4’s achievement of passing the bar exam has garnered widespread attention. However, it is less well-known that GPT-4 underperforms in the Chinese lawyer qualification tests. Additionally, GPT-4 still demonstrates imperfect performance in many legal AI tasks. In this talk, we will first introduce various applications of AI in the legal domain, using exemplary tasks from Korean precedents. Then, we will examine the potential problems that may arise from the bold application of AI. Finally, we will discuss where AI can be more convincingly applied based on the IRAC legal reasoning framework.

Work Experience
2023- / Assistant Professor at University of Seoul
2023- / AI Advisor at LBox
2021-2023 / Research Scientist at LBox
2018-2021 / Research Engineer at Naver
2014-2018 / Research Fellow at KIAS

Educational Background
2010-2014 / Ph.D. in Physics, Seoul National University
2007-2010 / M.S. in Physics, Seoul National University
2003-2007 / B.S. in Physics, Seoul National University

Publications & Articles
– Wonseok Hwang*, Saehee Eom, Hanuhl Lee, Hai Jin Park, and Minjoon Seo,”Data-efficient
End-to-end Information Extraction for Statistical Legal Analysis”, EMNLP 2022 Natural Legal
Language Processing Workshop.
– Wonseok Hwang*, Dongjun Lee, Kyoungyeon Cho, Hanuhl Lee, and Minjoon Seo*,”A Multi-Task
Benchmark for Korean Legal Language Understanding and Judgement Prediction”, NeurIPS
2022.
– Geewook Kim, Wonseok Hwang, Minjoon Seo, and Seunghyun Park,Semi-Structured Query
Grounding for Document-Oriented Databases with Deep Retrieval and Its Application to
Receipt and POI Matching, AAAI 2022 Workshop on Knowledge Discovery from Unstructured
Data in Financial Services.
– Geewook Kim, Teakgyu Hong, Moonbin Yim, Jinyoung Park, Jinyeong Yim, Wonseok
Hwang, Sangdoo Yun, Dongyoon Han, Seunghyun Park,OCR-free Document Understanding
Transformer”, ECCV 2022.
– Teakgyu Hong, DongHyun Kim, Mingi Ji, Wonseok Hwang, Daehyun Nam, Sungrae Park,BROS:
A Pre-trained Language Model Focusing on Text and Layout for Better Key Information
Extraction from Documents, AAAI 2022.
– Wonseok Hwang*, Hyunji Lee, Jinyeong Yim, Geewook Kim,and Minjoon Seo,Cost-
effective End-to-end Information Extraction for Semi-structured Document Images, EMNLP
2021(short).
– Wonseok Hwang*, Jinyeong Yim, Seunghyun Park, Sohee Yang, and Minjoon Seo,Spatial
Dependency Parsing for 2D Document Understanding, Findings of ACL 2021.

Session4
황원석
Wonseok Hwang
서울시립대학교 교수
University of Seoul,
Assistant Professor

손고은 / Goeun Son

서울디지털재단 선임연구원 / Seoul Digital Foundation, Senior Researcher

Session4Speakers

The Service Development Case using Large Language Model in Generative AI

This study aims to describe the LLAMA-SDF model developed by the Seoul Digital Foundation and its application in chatbot service development.
Developing a model suitable for public services requires building an open-source, cost-effective, internally serviceable model with low risk of data leakage for security.
For this reason, the Seoul Digital Foundation selected LLAMA2-ko-chat, a Korean model based on Meta’s LAMA2, as a pre-trained model for the development of the LLAMA-SDF model.
To reduce hallucination phenomena, data construction involved the conversion of 106 videos of elderly digital education content, owned by the foundation, into text as foundational data. To supplement the insufficient data, data augmentation was performed using GPT-3.5 turbo, and fine tuning was performed using the T5 model.
To improve model performance, we used techniques such as Fine-tuning(SFT, RLHF), Prompt learning and applied LoRA Adapter to utilize GPU memory efficiently.
The developed LAMA-SDF model was applied to digital counseling chatbot for the elderly with the aim of providing a question-and-answer environment for the elderly’s digital queries.
This study has important significance in contributing to the realization of smart public administration and the development of citizen-centered services by laying the groundwork for the development of a generative artificial intelligence language model.

Work Experience
National Institute of Meteorological Sciences (Earth System Research Division)
Coreintec Inc. (Convergence LABs.)
University of Ulsan (foundation for industry cooperation)

Educational Background
Pusan National Universtiy, Atmospheric Environmental Science Major, Bachelor of Science
Pusan National University, Atmospheric Sciences Major, Master of Science
Kookmin University, AI·Bigdata Major, Master of Engineering

Publications & Articles
– The Characteristics in the Simulation of High-resolution Coastal Weather Using the WRF and
SWAN Models, 2014, Journal of Environmental Science International, 23(3). 409-431.
– The Analysis of Sea Characteristics and Zone Classification on the Korean Peninsula using
Cluster Analysis, 2015, Journal of the Korean Data Analysis Society, 17(4), 2129-2138.

Session4
손고은
Goeun Son
서울디지털재단 선임연구원
Seoul Digital Foundation,
Senior Researcher

김혜진 / Hyejin Kim

서울연구원 부연구위원 / The Seoul Institute, Associate Research Fellow

Session4Speakers

Technological Strategies for Non-contact Smart Civil Petition Service

Despite the high demand for non-face-to-face civil complaints, there are still cases where direct visits or mail applications are required, so a technical application strategy is needed to switch to a simplified application method that does not require visits.

In this study, we developed a three-step plan to convert civil service that requires direct visits or mail applications to contactless.
(Step 1) Analyze the status of civil service, identify implications, and review the applicable laws and regulations.
(Step 2) Review and improve the civil service process based on the implications derived from step 1.
(Step 3) Research and development of application plan for technology necessary for improving civil service.

In addition, we proposed an intelligent online civil complaint application service that can easily create and use an online civil complaint channel. The service supports an automation function that makes it easier for civil petitioners to apply online, and allows civil petitioners to create and process online application channels.

Work Experience
– 2023.11 ~ Present: Associate Research Fellow, The Seoul Institute
– 2020.12 ~ 2023.10: Principal Researcher, Seoul Institute of Technology
– 2015.07 ~ 2020.11: Senior Researcher, LG Electronics
– 2014.03 ~ 2015.06: Post-doctoral Researcher, Senior Researcher, Korea Institute of Science and Technology

Educational Background
– 2007.09 ~ 2014.02: Ph.D in Information and Communications Engineering, Gwangju Institute of Science and Technology(GIST)
– 2006.03 ~ 2007.08: M.S. in Information and Communications Engineering, Gwangju Institute of Science and Technology(GIST)

Session4
김혜진
Hyejin Kim
서울연구원 부연구위원
The Seoul Institute,
Associate Research Fellow

강민규 / Mingyu Kang

서울시립대학교 교수 / University of Seoul, Assistant Professor

Session4Panel

Work Experience
– 2021-Present: Head of Big Data Research Center, Urban Big Data and Artificial Intelligence Institute (UBAI), University of Seoul (UOS)
– 2020-Present: Assistant Professor, Department of Urban Administration, University of Seoul (UOS)
– 2009-2020: Researcher, Korea Research Institute for Human Settlements (KRIHS)

Educational Background
– 2019: University of Washington, Department of Urban Design and Planning, Ph.D. in Urban Design and Planning
– 2009: Seoul National University, Department of Environmental Planning, M.A. in City Planning
– 2007: Seoul National University, Department of Political Science, B.A. in Political Science (Summa Cum Laude)

Publications & Articles
– (2022) “Does polycentric development produce less transportation carbon emissions? Evidence from urban form identified by night-time lights across US metropolitan areas”, Urban Climate, 44, 101223.
– (2019) “Night on South Korea: Unraveling the Relationship between Urban Development Patterns and DMSP-OLS Night-Time Lights”, Remote Sensing, 11(18), 2140.
– (2018) “Capturing fine-scale travel behaviors: a comparative analysis between personal activity location measurement system (PALMS) and travel diary”, International Journal of Health Geographics, 17:40.

Session4
강민규
Mingyu Kang
서울시립대학교 교수
University of Seoul, Assistant Professor

김현철 / Hyeon Cheol KIM

이화여자대학교 법학전문대학원 교수 / Law School, Ewha Womans University, Professor

Session4Panel

Work Experience
– Professor, School of Law, Ewha Womans University
– Vice-President, Korean Association of Legal Philosophy
– Member, Board of Directors, Fourth Industrial Revolution Convergence Law Association

Educational Background
– 1994-2000 : Seoul National University, College of Law, Ph.D. in Law
– 1992-1994 : Seoul National University, College of Law, Master of Law
– 1988-1992 : Seoul National University, College of Law, Bachelor of Law

Publications & Articles
– Philosophy of Law : Theory and Issue, Seoul, Pakyoung Press, 2022
– Understanding of Fourth Industrial Revolution, Seoul, Pakyoung Press, 2020
– Law and Bioethics, Seoul, Ewha Univ. Press, 2020

Session4
김현철
Hyeon Cheol KIM
이화여자대학교 법학전문대학원 교수
Law School, Ewha Womans University,
Professor

전종준 / Jong-June Jeon

서울시립대학교 도시과학빅데이터·AI연구원장 / Urban Big Data and AI Institute, President

종합토의Morderator

Work Experience
– 2023.11 ~ Present: Associate Research Fellow, The Seoul Institute
– 2020.12 ~ 2023.10: Principal Researcher, Seoul Institute of Technology
– 2015.07 ~ 2020.11: Senior Researcher, LG Electronics
– 2014.03 ~ 2015.06: Post-doctoral Researcher, Senior Researcher, Korea Institute of Science and Technology

Educational Background
– 2007.09 ~ 2014.02: Ph.D in Information and Communications Engineering, Gwangju Institute of Science and Technology(GIST)
– 2006.03 ~ 2007.08: M.S. in Information and Communications Engineering, Gwangju Institute of Science and Technology(GIST)

종합토의
전종준
Jong-June Jeon
서울시립대학교 도시과학빅데이터·AI연구원장
Urban Big Data and AI Institute, President

조혜림 / Hyerim Cho

서울연구원 디지털연구실장 / The Seoul Institute, Research Fellow

종합토의Panel

Work Experience
-Transportation Engineering / traffic Operation / ITS
-analysis of smart card data
-Transportation Planning

Educational Background
-Seoul City University (Ph.D., Major in Transportation Engineering)

Publications & Articles
– Improvement of efficient operation of private railways in Seoul (2023, SIT)
Measures to promote traffic safety in autonomous mobility testbed of Seoul (2023, SIT)
Implement Public Service Features in Autonomous Vehicle in Seoul(2023, MDPI)
– Analysis of the Impact of LRT Integration on Seoul Metropolitan Transportation (2022, SIT)
A pilot system for estimation of Seoul traffic demand (2021, SIT)
Establishment of Sang-am Smart Mobility Cluster (2021, SIT)
Analysis of Seoul’s Traffic Changes Due to COVID-19 and Future Response Strategies (2020, Transportation technology and policy)

종합토의
조혜림
Hyerim Cho
서울연구원 디지털연구실장
The Seoul Institute, Research Fellow

주성환 / Sunghwan Ju

서울디지털재단 경영전략실장 / Seoul Digital Foundation, General Manager

종합토의Panel

Work Experience
– General Manager of the Seoul Digital Foundation

Educational Background
– Ph.D of Business Administration

종합토의
주성환
Sunghwan Ju
서울디지털재단 경영전략실장
Seoul Digital Foundation, General Manager

윤충식 / Chung Sik Yun

서울시 빅데이터담당관 / Seoul Metropolitan Government, Big Data Division Director

Session1Panel

Work Experience
– ICT Management Division’s Director, Ministry of Environment(2021~2023)
– Deputy Director, Ministry of the Interior and Safety(2017~2021)
– Consulting Division;s Managing Director, Oracle Korea (2012~2015)

Educational Background
– Graduate School of Business IT, Kookmin University, Ph.D (2023.2)
– Graduate School of Technology of Management, Sungkyunkwan University, Master’s Degree(2001,8)
– Sungkyunkwan University, bachelor’s degree(1993.2)

Publications & Articles
– A study on demand forecasting and the location analysis of elementary care centers(2023.2)
– The Case Study for Childcare Service Demand Forecasting Using Bigdata Reference Analysis Model(2022.12)
– A Study on Data-driven administration(2018.11)

종합토의
윤충식
Chung Sik Yun
서울시 빅데이터담당관
Seoul Metropolitan Government,
Big Data Division Director

김근식 / Keunsik Kim

통계청 빅데이터통계과장 / Statistics Korea, Director, Big Data & Statistics Division

종합토의Panel

Work Experience
– (Present) Director, Big Data & Statistics Division, Statistics Korea
– (~ ’21.1) Chief Risk Officer, KBank
– (~ ‘16.4) General Manager of Risk Management Department, Woori Bank
– (~ ‘99.3) Senior Consultant, of SAS Korea

Educational Background
– B.S. / M.S., Department of Computer Science & Statistics. Seoul National University(Major in Statistics)
– MBA, Sogang Business School of Sogang University (Major in Finance)

종합토의
김근식
Keunsik Kim
통계청 빅데이터통계과장
Statistics Korea, Director, Big Data & Statistics Division

2023 Seoul Big Data Forum Secretariat