K-DS 컨소시엄

강연안내

K-DS Distinguished Lecture Series

Making Discoveries for Humanity and Society
with Data Science

강연 일시
2024년 3월 29일 (금) 오후 2시
연사 이름
Meeyoung Cha
소속
Professor, KAIST Chief Investigator, IBS Scientific Director, MPI-SP
문의
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연사소개

Meeyoung Cha

(Current) Professor at School of Computing, KAIST

(Current) Chief Investigator at the Institute for Basic Science (IBS)

(Current) Director, at Max Planck Institute for Security and Privacy (MPI-SP), Germany

(Former) Visiting Professor, Facebook Data Science Team, USA

Received ACM IMC Test-of-Time Award, AAAI ICWSM Test-of-Time Award, MSIT Award

강연개요

Making Discoveries for Humanity and Society with Data Science

Data science is an interdisciplinary field of study that extracts knowledge and insight from diverse forms of data through the use of scientific methods, algorithms, and systems. In particular, data science based on mathematical modeling and artificial intelligence (AI) has become critical for effectively handling astronomically growing data in various fields.

In this talk, I will introduce two research themes—poverty mapping and fake news detection—that address global issues and have a social impact. These research themes are examples of computational social science.

I will also talk about life as a data scientist, based on my experiences collaborating with world-class scientists at Facebook, AT&T Research, and Max Planck Institute, as well as NGOs like the United Nations Pulse Lab and the World Customs Organization.

K-DS Distinguished Lecture Series

How to Manage Societies Better than Optimal?

강연 일시
2024년 4월 26일 (금) 오후 4시
연사 이름
Dirk Helbing
소속
Professor of Computational Social Science, ETH Zurich
문의
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연사소개

Dirk Helbing

Professor of Computational Social Science at ETH Zurich

More than 10 Publications in Nature, Science, and PNAS

Recipient of Honorary Ph.D. from TU Delft

Former Director of the Ph.D. School in "Engineering Social Technologies for a Responsible Digital Future" at TU Delft

Active Member of the External Faculty of the Complexity Science Hub Vienna

강연개요

How to Manage Societies Better than Optimal?

Given the ongoing digital revolution and our present-day sustainability challenges, the ways cities and societies are operated are currently being reinvented. Societies are complex systems. This has important implications for how a society should be managed: Not like a company, and also not like a machine! I will illustrate our insights by means of pattern formation and self-organisation phenomena in social systems as well as applications to self-governance and self-control. Based on this, I will argue that the requirement of organizing societies in a more resilient way implies the need for more decentralized solutions based on digitally assisted self-organization – a concept, which is also compatible with sustainability requirements and greater participation. I will further discuss, how collective intelligence and co-creation can be supported in ways that promote favourable systemic outcomes – outcomes that are better than optimal, i.e. better than when optimization is applied. As an application example, I will present a field study on participatory budgeting, which has been recently carried out in Aarau, Switzerland. Specifically, I will show, how voting rules can be improved to promote individual and systemic benefits, such as inclusion and fairness.

K-DS Distinguished Lecture Series

Human Mobility Science

강연 일시
2024년 5월 24일 (금) 오전 10시
연사 이름
Gautam Malviya Thakur
소속
Group Leader, Location Intelligence R&D, Oak Ridge National Laboratory
문의
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연사소개

Gautam Malviya Thakur

(Current) Senior Staff Scientist and founding group leader of the Location Intelligence Group in the Geospatial Science and Human Security Division.

(Former) Deutsche Telekom Research Laboratories, Berlin, on transportation system modeling and understanding the network anatomy of major cities worldwide

(Former) Disney Research Laboratory, Zürich, on activity-driven mobility modeling of guests visiting the Disney theme parks

Research Interests in interconnected topics related to activity-driven human mobility modeling, place-based characterization, multi-scale global land use modeling, passive sensing, and spatially explicit disinformation detection.

Senior member of both ACM and IEEE

강연개요

Human Mobility Science

Human Mobility Modeling enables the understanding and characterization of time-variant movement and place visitation of individuals (or groups) in the real world. This knowledge is critical for domains like transportation planning, epidemic modeling, and energy use forecasting. Traditionally, simplistic statistical models such as a random walk or power law distribution were used to model these mobility patterns; however, it was determined that real-world mobility patterns are more complex and, therefore, require data-informed approaches for an accurate depiction. This talk will focus on the art and science of human mobility modeling with an emphasis on the use of Foundation Geoint data (demographics, points of interest, building footprint, etc.), behavior-driven movement-based patterns life generation, design and construction of data-informed human mobility model (HumoNet), spatio-temporal mobility interventions, and approaches to accurately benchmark mobility data to evaluate the presence of real-world mobility kinematics. The talk will conclude with the characterization of human mobility patterns from real-world scenarios, including disaster mitigation and cyber security attacks on critical infrastructure systems.

K-DS Distinguished Lecture Series

Frontiers of Collective Intelligence

강연 일시
2024년 6월 7일 (금) 오후 4시
연사 이름
Manuel Cebrián Ramos
소속
Senior Research Scientist, Spanish National Research Council
문의
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연사소개

Manuel Cebrián Ramos

Current Position: Senior Research Scientist at the Center for Automation and Robotics, Spanish National Research Council; Member of the National Advisory Board for Artificial Intelligence, Spanish Government

Research Focus: Computational Social Science, Network Science, Artificial Intelligence

Past Affiliations: Max Planck Society, Massachusetts Institute of Technology (MIT), Commonwealth Scientific and Industrial Research Organisation (CSIRO), University of California at San Diego, Brown University

Publications: Articles in Science, Nature, and Proceedings of the National Academy of Sciences on computational approaches to societal challenges

Recognition: Research featured in The New York Times, The Economist, The Guardian

강연개요

Frontiers of Collective Intelligence

In today’s world, complex systems capable of solving problems under significant pressure are omnipresent, including social networks, cities, and the Internet. The advent of Artificial Intelligence (AI) has added a new dimension to these systems, igniting debates about its deployment and long-term societal impacts. This seminar diverges from the conventional AI discourse, spotlighting an alternative form of experimental intelligence: Collective Intelligence. Collective Intelligence, which has evolved alongside the Internet, is distinguished by the collective capacity to address challenges and make decisions in ways that surpass the capabilities of individual members. In this seminar, I will share insights from several pivotal situations I have encountered, which illustrate the application of Collective Intelligence. In this seminar, we will explore the versatile applications of Collective Intelligence, including locating hidden entities across vast geographies, coordinating global searches for missing individuals, reassembling critically important shredded documents, and directing human actors in real-time via the Internet. By examining both the untapped potential and the inherent challenges of Collective Intelligence, the seminar aims to foster a dialogue on how the lessons learned from these experiences can inform the future development and strategic deployment of Artificial Intelligence.

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