Das Frühjahrssemester 2021 findet sicher bis Ostern online statt. Ausnahmen: Veranstaltungen, die nur mit Präsenz vor Ort durchführbar sind. Bitte beachten Sie die Informationen der Dozierenden.

Dirk Helbing: Katalogdaten im Frühjahrssemester 2020

NameHerr Prof. Dr. Dirk Helbing
LehrgebietComputational Social Science
Computational Social Science
ETH Zürich, STD F 3
Stampfenbachstrasse 48
8092 Zürich
Telefon+41 44 632 88 80
Fax+41 44 632 17 67
DepartementGeistes-, Sozial- und Staatswissenschaften
BeziehungOrdentlicher Professor

851-0591-01LBETH - Blockchain for Sustainability Belegung eingeschränkt - Details anzeigen
Findet dieses Semester nicht statt.
Number of participants limited to 200

Particularly suitable for students of D-INFK, D-MTEC, D-ITET, D-MAVT,D-PHYS
3 KP4GD. Helbing
KurzbeschreibungBlockchain and Internet of Things technologies hold the promise to transform our societies and economies. While IoT devices allow us to measure all kinds of activity by humans and machines, the blockchain allows us to securely time-stamp and value this data and even give it a price to trade it on (new) markets. We explore this potential with a specific focus on sustainable development.
LernzielThe course provides opportunities to gain fundamental understanding of promising new technologies as well as develop creative decentralized solutions for societal challenges using these technologies.
Participants will learn the fundamentals of blockchain technology, its mechanisms, design parameters and potential for decentralized solutions. Those with software development skills will then further explore the blockchain to develop hands-on decentralized applications and smart contracts. Non-coding participants will further explore how these technologies could be used to design new economic systems. These new cryptoeconomic systems should give citizens multiple incentives to increase cooperation, health, recycling, or education and other positive externalities and to decrease emissions, waste, noise, or stress and other negative externalities. During the hackathon, participants will work in mixed teams on concrete challenges addressing some of the pressing global challenges our societies face, like climate change, financial instability, energy, or mass migration, etc. The aim is to develop decentralized approaches towards a sustainable, sharing circular economy using blockchain and IoT technologies.
Teams will produce a short report (about 10 pages), demonstrate their hackathon prototype based on blockchain technology (Ethereum platform) and present to a interdisciplinary jury on the last day. Throughout the course, participants will hone their critical thinking abilities by leaving their own discipline and discussing best approaches to solve global complex challenges in an international, multi-disciplinary setting with invited subject matter experts and peers from all around the world.
We encourage students with no programming experience, who are interested in the potential of blockchain and IoT to address global challenges, to apply as well!
860-0022-00LComplexity and Global Systems Science Information Belegung eingeschränkt - Details anzeigen
Findet dieses Semester nicht statt.
Number of participants limited to 64.

Prerequisites: solid mathematical skills.

Particularly suitable for students of D-ITET, D-MAVT and ISTP
3 KP2VD. Helbing
KurzbeschreibungThis 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.
LernzielParticipants 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.
InhaltThis 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 cascade 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.
Voraussetzungen / BesonderesMathematical skills can be helpful