Sachit Mahajan: Catalogue data in Spring Semester 2021

Name Dr. Sachit Mahajan
Address
Computational Social Science
ETH Zürich, STD F 2
Stampfenbachstrasse 48
8092 Zürich
SWITZERLAND
E-mailsachit.mahajan@gess.ethz.ch
DepartmentHumanities, Social and Political Sciences
RelationshipLecturer

NumberTitleECTSHoursLecturers
860-0022-00LComplexity and Global Systems Science Restricted registration - show details
Number of participants limited to 50.

Prerequisites: solid mathematical skills.

Particularly suitable for students of D-ITET, D-MAVT and ISTP
3 credits2SD. Helbing, S. Mahajan
AbstractThis course discusses complex techno-socio-economic systems, their counter-intuitive behaviors, and how their theoretical understanding empowers us to solve some long-standing problems that are currently bothering the world.
ObjectiveParticipants should learn to get an overview of the state of the art in the field, to present it in a well understandable way to an interdisciplinary scientific audience, to develop models for open problems, to analyze them, and to defend their results in response to critical questions. In essence, participants should improve their scientific skills and learn to think scientifically about complex dynamical systems.
ContentThis course starts with a discussion of the typical and often counter-intuitive features of complex dynamical systems such as self-organization, emergence, (sudden) phase transitions at "tipping points", multi-stability, systemic instability, deterministic chaos, and turbulence. It then discusses phenomena in networked systems such as feedback, side and cascading effects, and the problem of radical uncertainty. The course progresses by demonstrating the relevance of these properties for understanding societal and, at times, global-scale problems such as traffic jams, crowd disasters, breakdowns of cooperation, crime, conflict, social unrests, political revolutions, bubbles and crashes in financial markets, epidemic spreading, and/or "tragedies of the commons" such as environmental exploitation, overfishing, or climate change. Based on this understanding, the course points to possible ways of mitigating techno-socio-economic-environmental problems, and what data science may contribute to their solution.
Lecture notes"Social Self-Organization
Agent-Based Simulations and Experiments to Study Emergent Social Behavior"
Helbing, Dirk
ISBN 978-3-642-24004-1
LiteraturePhilip Ball
Why Society Is A Complex Matter
https://www.springer.com/gp/book/9783642289996

Globally networked risks and how to respond
Nature: https://www.nature.com/articles/nature12047

Global Systems Science and Policy
https://library.oapen.org/bitstream/handle/20.500.12657/28004/1001993.pdf?sequence=1#page=214

Managing Complexity: Insights, Concepts, Applications
https://www.springer.com/gp/book/9783540752608

Further links:

http://global-systems-science.org

http://www.global-systems-science.org/wp-content/uploads/2013/06/GSS-06-06-2013-F1.pdf

http://www.global-systems-science.org/wp-content/uploads/2013/06/GSS_SynthesisPaper_070613_final.pdf

https://ec.europa.eu/digital-single-market/en/global-systems-science

Further literature will be recommended in the lectures.
Prerequisites / NoticeMathematical skills can be helpful