Emo Welzl: Catalogue data in Autumn Semester 2020

Name	Prof. em. Dr. Emo Welzl
Name variants	Emo Welzl
Field	Computer Science
Address	Inst. f. Theoretische Informatik ETH Zürich, OAT Z 13.2 Andreasstrasse 5 8092 Zürich SWITZERLAND
Telephone	+41 44 632 73 70
E-mail	emo@inf.ethz.ch
URL	http://www.inf.ethz.ch/personal/emo/
Department	Computer Science
Relationship	Professor emeritus

Number	Title	ECTS	Hours	Lecturers
252-1425-00L	Geometry: Combinatorics and Algorithms	8 credits	3V + 2U + 2A	B. Gärtner, E. Welzl, M. Hoffmann, M. Wettstein
Abstract	Geometric structures are useful in many areas, and there is a need to understand their structural properties, and to work with them algorithmically. The lecture addresses theoretical foundations concerning geometric structures. Central objects of interest are triangulations. We study combinatorial (Does a certain object exist?) and algorithmic questions (Can we find a certain object efficiently?)
Learning objective	The goal is to make students familiar with fundamental concepts, techniques and results in combinatorial and computational geometry, so as to enable them to model, analyze, and solve theoretical and practical problems in the area and in various application domains. In particular, we want to prepare students for conducting independent research, for instance, within the scope of a thesis project.
Content	Planar and geometric graphs, embeddings and their representation (Whitney's Theorem, canonical orderings, DCEL), polygon triangulations and the art gallery theorem, convexity in R^d, planar convex hull algorithms (Jarvis Wrap, Graham Scan, Chan's Algorithm), point set triangulations, Delaunay triangulations (Lawson flips, lifting map, randomized incremental construction), Voronoi diagrams, the Crossing Lemma and incidence bounds, line arrangements (duality, Zone Theorem, ham-sandwich cuts), 3-SUM hardness, counting planar triangulations.
Lecture notes	yes
Literature	Mark de Berg, Marc van Kreveld, Mark Overmars, Otfried Cheong, Computational Geometry: Algorithms and Applications, Springer, 3rd ed., 2008. Satyan Devadoss, Joseph O'Rourke, Discrete and Computational Geometry, Princeton University Press, 2011. Stefan Felsner, Geometric Graphs and Arrangements: Some Chapters from Combinatorial Geometry, Teubner, 2004. Jiri Matousek, Lectures on Discrete Geometry, Springer, 2002. Takao Nishizeki, Md. Saidur Rahman, Planar Graph Drawing, World Scientific, 2004.
Prerequisites / Notice	Prerequisites: The course assumes basic knowledge of discrete mathematics and algorithms, as supplied in the first semesters of Bachelor Studies at ETH. Outlook: In the following spring semester there is a seminar "Geometry: Combinatorics and Algorithms" that builds on this course. There are ample possibilities for Semester-, Bachelor- and Master Thesis projects in the area.
252-4202-00L	Seminar in Theoretical Computer Science	2 credits	2S	E. Welzl, B. Gärtner, M. Ghaffari, M. Hoffmann, J. Lengler, D. Steurer, B. Sudakov
Abstract	Presentation of recent publications in theoretical computer science, including results by diploma, masters and doctoral candidates.
Learning objective	The goal is to introduce students to current research, and to enable them to read, understand, and present scientific papers.
Prerequisites / Notice	This seminar takes place as part of the joint research seminar of several theory groups. Intended participation is for students with excellent performance only. Formal restriction is: prior successful participation in a master level seminar in theoretical computer science.
263-0006-00L	Algorithms Lab Only for master students, otherwise a special permission by the student administration of D-INFK is required.	8 credits	4P + 3A	E. Welzl
Abstract	Students learn how to solve algorithmic problems given by a textual description (understanding problem setting, finding appropriate modeling, choosing suitable algorithms, and implementing them). Knowledge of basic algorithms and data structures is assumed; more advanced material and usage of standard libraries for combinatorial algorithms are introduced in tutorials.
Learning objective	The objective of this course is to learn how to solve algorithmic problems given by a textual description. This includes appropriate problem modeling, choice of suitable (combinatorial) algorithms, and implementing them (using C/C++, STL, CGAL, and BGL).
Literature	T. Cormen, C. Leiserson, R. Rivest: Introduction to Algorithms, MIT Press, 1990. J. Hromkovic, Teubner: Theoretische Informatik, Springer, 2004 (English: Theoretical Computer Science, Springer 2003). J. Kleinberg, É. Tardos: Algorithm Design, Addison Wesley, 2006. H. R. Lewis, C. H. Papadimitriou: Elements of the Theory of Computation, Prentice Hall, 1998. T. Ottmann, P. Widmayer: Algorithmen und Datenstrukturen, Spektrum, 2012. R. Sedgewick: Algorithms in C++: Graph Algorithms, Addison-Wesley, 2001.