Roger Wattenhofer: Katalogdaten im Frühjahrssemester 2021

Name	Herr Prof. Dr. Roger Wattenhofer
Lehrgebiet	Distributed Computing
Adresse	Inst. f. Techn. Informatik u. K. ETH Zürich, ETZ G 96 Gloriastrasse 35 8092 Zürich SWITZERLAND
Telefon	+41 44 632 63 12
E-Mail	wattenhofer@ethz.ch
URL	http://www.disco.ethz.ch
Departement	Informationstechnologie und Elektrotechnik
Beziehung	Ordentlicher Professor

Nummer	Titel	ECTS	Umfang	Dozierende
227-0558-00L	Principles of Distributed Computing	7 KP	2V + 2U + 2A	R. Wattenhofer, M. Ghaffari
Kurzbeschreibung	We study the fundamental issues underlying the design of distributed systems: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques.
Lernziel	Distributed computing is essential in modern computing and communications systems. Examples are on the one hand large-scale networks such as the Internet, and on the other hand multiprocessors such as your new multi-core laptop. This course introduces the principles of distributed computing, emphasizing the fundamental issues underlying the design of distributed systems and networks: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques, basically the "pearls" of distributed computing. We will cover a fresh topic every week.
Inhalt	Distributed computing models and paradigms, e.g. message passing, shared memory, synchronous vs. asynchronous systems, time and message complexity, peer-to-peer systems, small-world networks, social networks, sorting networks, wireless communication, and self-organizing systems. Distributed algorithms, e.g. leader election, coloring, covering, packing, decomposition, spanning trees, mutual exclusion, store and collect, arrow, ivy, synchronizers, diameter, all-pairs-shortest-path, wake-up, and lower bounds
Skript	Available. Our course script is used at dozens of other universities around the world.
Literatur	Lecture Notes By Roger Wattenhofer. These lecture notes are taught at about a dozen different universities through the world. Distributed Computing: Fundamentals, Simulations and Advanced Topics Hagit Attiya, Jennifer Welch. McGraw-Hill Publishing, 1998, ISBN 0-07-709352 6 Introduction to Algorithms Thomas Cormen, Charles Leiserson, Ronald Rivest. The MIT Press, 1998, ISBN 0-262-53091-0 oder 0-262-03141-8 Disseminatin of Information in Communication Networks Juraj Hromkovic, Ralf Klasing, Andrzej Pelc, Peter Ruzicka, Walter Unger. Springer-Verlag, Berlin Heidelberg, 2005, ISBN 3-540-00846-2 Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes Frank Thomson Leighton. Morgan Kaufmann Publishers Inc., San Francisco, CA, 1991, ISBN 1-55860-117-1 Distributed Computing: A Locality-Sensitive Approach David Peleg. Society for Industrial and Applied Mathematics (SIAM), 2000, ISBN 0-89871-464-8
Voraussetzungen / Besonderes	Course pre-requisites: Interest in algorithmic problems. (No particular course needed.)
227-0559-00L	Seminar in Deep Neural Networks Number of participants limited to 25.	2 KP	2S	R. Wattenhofer, O. Richter
Kurzbeschreibung	In this seminar participating students present and discuss recent research papers in the area of deep neural networks.
Lernziel	We aim at giving the students an in depth view on the current advances in the area by discussing recent papers as well as discussing current issues and difficulties surrounding deep neural networks. The students will learn to read, evaluate and challenge research papers, prepare coherent scientific presentations and lead a discussion on their topic.
Inhalt	The seminar will cover a range of research directions, with a focus on Graph Neural Networks, Algorithmic Learning, Reinforcement Learning and Natural Language Processing. It will be structured in blocks with each focus area being briefly introduced before presenting and discussing recent research papers. Papers will be allocated to the students based on their preferences. For more information see www.disco.ethz.ch/courses.html.
Skript	Slides of presentations will be made available.
Literatur	The paper selection can be found on www.disco.ethz.ch/courses.html.
Voraussetzungen / Besonderes	It is expected that students have prior knowledge and interest in machine and deep learning, for instance by having attended appropriate courses.
252-0817-00L	Distributed Systems Laboratory	10 KP	9P	G. Alonso, T. Hoefler, A. Klimovic, A. Singla, R. Wattenhofer, C. Zhang
Kurzbeschreibung	Entwicklung und / oder Evaluation eines umfangreicheren praktischen Systems mit Technologien aus dem Gebiet der verteilten Systeme. Das Projekt kann aus unterschiedlichen Teilbereichen (von Web-Services bis hin zu ubiquitären Systemen) stammen; typische Technologien umfassen drahtlose Ad-hoc-Netze oder Anwendungen auf Mobiltelefonen.
Lernziel	Erwerb praktischer Kenntnisse bei Entwicklung und / oder Evaluation eines umfangreicheren praktischen Systems mit Technologien aus dem Gebiet der verteilten Systeme.
Inhalt	Entwicklung und / oder Evaluation eines umfangreicheren praktischen Systems mit Technologien aus dem Gebiet der verteilten Systeme. Das Projekt kann aus unterschiedlichen Teilbereichen (von Web-Services bis hin zu ubiquitären Systemen) stammen; typische Technologien umfassen drahtlose Ad-hoc-Netze oder Anwendungen auf Mobiltelefonen. Zu diesem Praktikum existiert keine Vorlesung. Bei Interesse bitte einen der beteiligten Professoren oder einen Assistenten der Forschungsgruppen kontaktieren.
363-1153-00L	New Technologies in Banking and Finance	3 KP	2V	B. J. Bergmann, P. Cheridito, H. Gersbach, P. Mangold, J. Teichmann, R. Wattenhofer
Kurzbeschreibung	Technological advances, digitization and the ability to store and process vast amounts of data has changed the landscape of banking and finance in recent years. This course will unpack the technologies underlying these transformations and reflect on the impacts on the financial world, covering also change management perspectives.
Lernziel	After taking this course, students will be able to - Understand recent technological developments and how they drive transformation in banking and finance - Understand the challenges of this digital transformation when managing financial and non-financial risks - Reflect on the impacts this transformation has on workflows, agile working, project and change management
Inhalt	The financial manager of the future is commanding a wide set of skills ranging from a profound understanding of technological advances and a sensible understanding of the impact on workflows and business models. Students with an interest in finance and banking are invited to take the course without explicit theoretical knowledge in financial economics. As the course will cover topics like machine learning, cyber security, distributed computing, and more, an understanding of these technologies is welcomed, however not mandatory. The course will also go beyond technological advances and will also cover management-related contents. The course is divided in sections, each covering different areas and technologies. Students are asked to solve small cases in groups for each section. Invited guest speakers will contribute to the sessions. In addition, separate networking sessions will provide entry opportunities into finance and banking. More information on the speakers and specific session can be found here: https://riskcenter.ethz.ch/education/lectures.html and on the moodle page.
Voraussetzungen / Besonderes	The course is opened to students from all backgrounds. Some experience with quantitative disciplines such as probability and statistics, however, is useful.