Timothy Roscoe: Katalogdaten im Frühjahrssemester 2018

Name	Herr Prof. Dr. Timothy Roscoe
Lehrgebiet	Informatik
Adresse	Institut für Computing Platforms ETH Zürich, STF H 314 Stampfenbachstrasse 114 8092 Zürich SWITZERLAND
Telefon	+41 44 632 88 40
E-Mail	troscoe@inf.ethz.ch
URL	http://people.inf.ethz.ch/troscoe/
Departement	Informatik
Beziehung	Ordentlicher Professor

Nummer	Titel	ECTS	Umfang	Dozierende
252-0817-00L	Distributed Systems Laboratory Im Masterstudium können zusätzlich zu den Vertiefungsübergreifenden Fächern nur max. 10 Kreditpunkte über Laboratorien erarbeitet werden. Weitere Laboratorien werden auf dem Beiblatt aufgeführt.	10 KP	9P	G. Alonso, T. Hoefler, F. Mattern, T. Roscoe, 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.
263-3830-00L	Software Defined Networking: The Data Centre Perspective	2 KP	2S	T. Roscoe, D. Wagenknecht-Dimitrova
Kurzbeschreibung	Software Defined Networks (SDN) is a change supported not only by research but also industry and redifens how traditional network management and configuration is been done.
Lernziel	Through review and discussion of literature on an exciting new trend in networking, the students get the opportunity to get familiar with one of the most promising new developments in data centre connectivity, while at the same time they can develop soft skills related to the evaluation and presentation of professional content.
Inhalt	Software Defined Networks (SDN) is a change supported not only by research but also industry and redifens how traditional network management and configuration is been done. Although much has been already investigated and there are already functional SDN-enabled switches there are many open questions ahead of the adoption of SDN inside and outside the data centre (traditional or cloud-based). With a series of seminars we will reflect on the challenges, adoption strategies and future trends of SDN to create an understanding how SDN is affecting the network operators' industry.
Literatur	The seminar is based on recent publications by academia and industry. Links to the publications are placed on the Seminar page and can be downloaded from any location with access to the ETH campus network.
Voraussetzungen / Besonderes	The seminar bases on active and interactive participation of the students.
851-0740-00L	Big Data, Law, and Policy Number of participants limited to 35 Students will be informed by 4.3.2018 at the latest	3 KP	2S	S. Bechtold, T. Roscoe, E. Vayena
Kurzbeschreibung	This course introduces students to societal perspectives on the big data revolution. Discussing important contributions from machine learning and data science, the course explores their legal, economic, ethical, and political implications in the past, present, and future.
Lernziel	This course is intended both for students of machine learning and data science who want to reflect on the societal implications of their field, and for students from other disciplines who want to explore the societal impact of data sciences. The course will first discuss some of the methodological foundations of machine learning, followed by a discussion of research papers and real-world applications where big data and societal values may clash. Potential topics include the implications of big data for privacy, liability, insurance, health systems, voting, and democratic institutions, as well as the use of predictive algorithms for price discrimination and the criminal justice system. Guest speakers, weekly readings and reaction papers ensure a lively debate among participants from various backgrounds.
860-0018-00L	Big Data, Law, and Policy (with Case Study) Limited number of participants. Students will be informed by 4.3.2018 at the latest	6 KP	2S + 2A	S. Bechtold, T. Roscoe, E. Vayena
Kurzbeschreibung	This course examines and critiques the design of the Internet, with a focus on the connection between the engineering features and principles of the network and the legal, economic, and political concerns which have followed its evolution.
Lernziel	This course examines and critiques the design of the Internet (broadly defined), with a focus on the connection between the engineering features and principles of the network (packet switching, global addressing, the end-to-end argument, etc.) and the legal, economic, and political concerns which have followed its evolution (security properties, censorship and censorship resistance, "net neutrality", etc.). No prior knowledge of networking technologies is required; conversely the course will focus only on those features of the Internet design which have strong political and legal implications (and vice versa). The course consists of two parts: lectures and seminars in one part provide an introduction and discussion of the technical, legal, and political aspects of the Internet design. The other part consists of a specific case study of some aspect of the Internet by individual students.