Search result: Catalogue data in Spring Semester 2021

Computational Science and Engineering Bachelor Information
For All Programme Regulations
Electives
In the ‘electives’ subcategory, at least two course units must be successfully completed.
NumberTitleTypeECTSHoursLecturers
401-3902-21LNetwork & Integer Optimization: From Theory to ApplicationW6 credits3GR. Zenklusen
AbstractThis course covers various topics in Network and (Mixed-)Integer Optimization. It starts with a rigorous study of algorithmic techniques for some network optimization problems (with a focus on matching problems) and moves to key aspects of how to attack various optimization settings through well-designed (Mixed-)Integer Programming formulations.
ObjectiveOur goal is for students to both get a good foundational understanding of some key network algorithms and also to learn how to effectively employ (Mixed-)Integer Programming formulations, techniques, and solvers, to tackle a wide range of discrete optimization problems.
ContentKey topics include:
- Matching problems;
- Integer Programming techniques and models;
- Extended formulations and strong problem formulations;
- Solver techniques for (Mixed-)Integer Programs;
- Decomposition approaches.
Literature- Bernhard Korte, Jens Vygen: Combinatorial Optimization. 6th edition, Springer, 2018.
- Alexander Schrijver: Combinatorial Optimization: Polyhedra and Efficiency. Springer, 2003. This work has 3 volumes.
- Vanderbeck François, Wolsey Laurence: Reformulations and Decomposition of Integer Programs. Chapter 13 in: 50 Years of Integer Programming 1958-2008. Springer, 2010.
- Alexander Schrijver: Theory of Linear and Integer Programming. John Wiley, 1986.
Prerequisites / NoticeSolid background in linear algebra. Preliminary knowledge of Linear Programming is ideal but not a strict requirement. Prior attendance of the course Mathematical Optimization is a plus.
401-3908-21LPolynomial OptimizationW6 credits3GA. A. Kurpisz
AbstractIntroduction to Polynomial Optimization and methods to solve its convex relaxations.
ObjectiveThe goal of this course is to provide a treatment of non-convex Polynomial Optimization problems through the lens of various techniques to solve its convex relaxations. Part of the course will be focused on learning how to apply these techniques to practical examples in finance, robotics and control.
ContentKey topics include:
- Polynomial Optimization as a non-convex optimization problem and its connection to certifying non-negativity of polynomials
- Optimization-free and Linear Programming based techniques to approach Polynomial Optimization problems.
- Introduction of Second-Order Cone Programming, Semidefinite Programming and Relative Entropy Programming as a tool to solve relaxations of Polynomial Optimization problems.
- Applications to optimization problems in finance, robotics and control.
Lecture notesA script will be provided.
LiteratureOther helpful materials include:
- Jean Bernard Lasserre, An Introduction to Polynomial and Semi-Algebraic Optimization, Cambridge University Press, February 2015
- Pablo Parrilo. 6.972 Algebraic Techniques and Semidefinite Optimization. Spring 2006. Massachusetts Institute of Technology: MIT OpenCourseWare, . License: .
Prerequisites / NoticeBackground in Linear and Integer Programming is recommended.
351-1138-00LPRISMA Capstone - Rethinking Sustainable Cities and Communities
Bachelor students get preferential access to this course. All interested students must apply through a separate application process at: Link

Participation is subject to successful selection through this sign-up process.
W4 credits4VA. Cabello Llamas, M. Augsburger
AbstractThe goal of this intense one-week course is to bring students from different backgrounds together to make connections between disciplines and to build bridges to society. Supported by student coaches and experts, our student teams will use hands-on Design Thinking methods to address relevant challenges based on the UN sustainable development goals.
ObjectiveIn this intense 7-day block course students will be able to acquire and practice essential cross-disciplinary competencies as well as gaining an understanding of a human-centered innovation process. More specifically students will learn to:
- Work and think in a problem-based way.
- Put their own field into a broader context.
- Engage in collaborative ideation with a multidisciplinary team.
- Identify challenges related to relevant societal issues.
- Develop, prototype and plan innovative solutions for a range of different contexts.
- Innovate in a human-centered way by observing and interacting with key stakeholders.

The acquired methods and skills are based on the ETH competence framework and can be applied to tackle a broad range of problems in academia and society. Moving beyond traditional teaching approaches, this course allows students to engage creatively in a process of rethinking and redesigning aspects and elements of current and future urban areas, actively contributing towards fulfilling the UN SDG 11.
ContentThe course is divided in to three stages:

Warm-up and framing: The goal of this first stage is to get familiar with current problems faced by cities and communities as well as with the Design Thinking process and mindset. The students will learn about the working process, the teaching spaces and resources, as well as their fellow students and the lecturers.

Identifying challenges: The objective is to get to know additional methods and tools to identify a specific challenge relevant for urban areas through fieldwork and direct engagement with relevant stakeholders, resulting in the definition of an actionable problem statement that will form the starting point for the development of innovative solutions.

Solving challenges within current and future context: During this phase, students will apply the learned methods and tools to solve the identified challenge in a multi-disciplinary group by creating, developing and testing high-potential ideas. The ideas are presented to relevant academic, industry and societal stakeholders on the last day of the week.

To facilitate the fast-paced innovation journey, the multidisciplinary teams are supported throughout the week by experienced student coaches.

This course is a capstone for the student-lead initiative PRISMA. (Link).
Prerequisites / NoticeBachelor students get preferential access to this course. All interested students must apply through a separate application process at: Link

Participation is subject to successful selection through this sign-up process.
» see also Fields of Specialization
» Electives (CSE Master)
Additional Electives from the Fields of Specialization (CSE Master)
recognition of 227-0662-00L and 227-0662-10L requires the successful completion of both course units
NumberTitleTypeECTSHoursLecturers
701-1228-00LCloud Dynamics: Hurricanes Information W4 credits3GU. Lohmann
AbstractHurricanes are among the most destructive elements in the atmosphere. This lecture will discuss the physical requirements for their formation, life cycle, damage potential and their relationship to global warming. It also distinguishes hurricanes from thunderstorms and tornadoes.
ObjectiveAt the end of this course students will be able to distinguish the formation and life cycle mechanisms of tropical cyclones from those of extratropical thunderstorms/cyclones, project how tropical cyclones change in a warmer climate based on their physics and evaluate different tropical cyclone modification ideas.
Contentsee course outline at: Link
Lecture notesSlides will be made available
LiteratureA literature list can be found here: Link
Prerequisites / NoticeAt least one introductory lecture in Atmospheric Science or Instructor's consent. This lecture will build on some concepts of atmospheric dynamics and their governing equations. Thus, mathematical knowledge will be needed to use the equations to understand the material of the course.
701-1270-00LHigh Performance Computing for Weather and ClimateW3 credits3GO. Fuhrer
AbstractState-of-the-art weather and climate simulations rely on large and complex software running on supercomputers. This course focuses on programming methods and tools for understanding, developing and optimizing the computational aspects of weather and climate models. Emphasis will be placed on the foundations of parallel computing, practical exercises and emerging trends such as using GPUs.
ObjectiveAfter attending this course, students will be able to:
- Understand a broad variety of high performance computing concepts relevant for weather and climate simulations
- Work with weather and climate simulation codes that run on large supercomputers
ContentHPC Overview:
- Why does weather and climate require HPC?
- Today's HPC: Beowulf-style clusters, massively parallel architectures, hybrid computing, accelerators
- Scaling / Parallel efficiency
- Algorithmic motifs in weather and climate

Writing HPC code:
- Data locality and single node efficiency
- Shared memory parallelism with OpenMP
- Distributed memory parallelism with MPI
- GPU computing
- High-level programming and domain-specific languages
Literature- Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein, CRC Press, 2011
- Computer Organization and Design, D.H. Patterson and J.L. Hennessy
- Parallel Computing, A. Grama, A. Gupta, G. Karypis, V. Kumar (Link)
- Parallel Programming in MPI and OpenMP, V. Eijkhout (Link)
Prerequisites / Notice- fundamentals of numerical analysis and atmospheric modeling
- basic experience in a programming language (C/C++, Fortran, Python, …)
- experience using command line interfaces in *nix environments (e.g., Unix, Linux)
151-0110-00LCompressible FlowsW4 credits2V + 1UT. Rösgen
AbstractTopics: unsteady one-dimensional subsonic and supersonic flows, acoustics, sound propagation, supersonic flows with shocks and Prandtl-Meyer expansions, flow around slender bodies, shock tubes, reaction fronts (deflagration and detonation).
Mathematical tools: method of characteristics and selected numerical methods.
ObjectiveIllustration of compressible flow phenomena and introduction to the corresponding mathematical description methods.
ContentThe interaction of compressibility and inertia is responsible for wave generation in a fluid. The compressibility plays an important role for example in unsteady phenomena, such as oscillations in gas pipelines or exhaust pipes. Compressibility effects are also important in steady subsonic flows with high Mach numbers (M>0.3) and in supersonic flows (e.g. aeronautics, turbomachinery).
The first part of the lecture deals with wave propagation phenomena in one-dimensional subsonic and supersonic flows. The discussion includes waves with small amplitudes in an acoustic approximation and waves with large amplitudes with possible shock formation.
The second part deals with plane, steady supersonic flows. Slender bodies in a parallel flow are considered as small perturbations of the flow and can be treated by means of acoustic methods. The description of the two-dimensional supersonic flow around bodies with arbitrary shapes includes oblique shocks and Prandtl-Meyer expansions etc.. Various boundary conditions, which are imposed for example by walls or free-jet boundaries, and interactions, reflections etc. are taken into account.
Lecture notesnot available
Literaturea list of recommended textbooks is handed out at the beginning of the lecture.
Prerequisites / Noticeprerequisites: Fluiddynamics I and II
327-0613-00LComputer Applications: Finite Elements in Solids and Structures Information
The course will only take place if at least 7 students are enrolled.
W4 credits2V + 2UA. Gusev
AbstractTo introduce the Finite Element Method to the students with a general interest in the topic
ObjectiveTo introduce the Finite Element Method to the students with a general interest in the topic
ContentIntroduction; Energy formulations; Displacement finite elements; Solutions to the finite element equations; Linear elements; Convergence, compatibility and completeness; Higher order elements; Beam and frame elements, Plate and shell elements; Dynamics and vibration; Generalization of the Finite Element concepts (Galerkin-weighted residual and variational approaches)
Lecture notesAutographie
Literature- Astley R.J. Finite Elements in Solids and Structures, Chapman & Hill, 1992
- Zienkiewicz O.C., Taylor R.L. The Finite Element Method, 5th ed., vol. 1, Butterworth-Heinemann, 2000
151-0212-00LAdvanced CFD MethodsW4 credits2V + 1UP. Jenny
AbstractFundamental and advanced numerical methods used in commercial and open-source CFD codes will be explained. The main focus is on numerical methods for conservation laws with discontinuities, which is relevant for trans- and hypersonic gas dynamics problems, but also CFD of incompressible flows, Direct Simulation Monte Carlo and the Lattice Boltzmann method are explained.
ObjectiveKnowing what's behind a state-of-the-art CFD code is not only important for developers, but also for users in order to choose the right methods and to achieve meaningful and accurate numerical results. Acquiring this knowledge is the main goal of this course.

Established numerical methods to solve the incompressible and compressible Navier-Stokes equations are explained, whereas the focus lies on finite volume methods for compressible flow simulations. In that context, first the main theory and then numerical schemes related to hyperbolic conservation laws are explained, whereas not only examples from fluid mechanics, but also simpler, yet illustrative ones are considered (e.g. Burgers and traffic flow equations). In addition, two less commonly used yet powerful approaches, i.e., the Direct Simulation Monte Carlo (DSMC) and Lattice Boltzmann methods, are introduced.

For most exercises a C++ code will have to be modified and applied.
Content- Finite-difference vs. finite-element vs. finite-volume methods
- Basic approach to simulate incompressible flows
- Brief introduction to turbulence modeling
- Theory and numerical methods for compressible flow simulations
- Direct Simulation Monte Carlo (DSMC)
- Lattice Boltzmann method
Lecture notesPart of the course is based on the referenced books. In addition, the participants receive a manuscript and the slides.
Literature"Computational Fluid Dynamics" by H. K. Versteeg and W. Malalasekera.
"Finite Volume Methods for Hyperbolic Problems" by R. J. Leveque.
Prerequisites / NoticeBasic knowledge in
- fluid dynamics
- numerical mathematics
- programming (programming language is not important, but C++ is of advantage)
401-8908-00LContinuous Time Quantitative Finance (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: MFOEC204

Mind the enrolment deadlines at UZH:
Link
W3 credits3VUniversity lecturers
AbstractAmerican Options, Stochastic Volatility, Lévy Processes and Option Pricing, Exotic Options, Transaction Costs and Real Options.
ObjectiveThe course focuses on the theoretical foundations of modern derivative pricing. It aims at deriving and explaining important option pricing models by relying on some mathematical tools of continuous time finance.
A particular focus on jump processes is given. The introduction of possible financial crashes is now essential in some models and a clear understanding of Poisson processes is therefore important. A standard background in stochastic calculus is required.
ContentStochastic volatility models
Itô's formula and Girsanov theorem for jump-diffusion processes
The pricing of options in presence of possible discontinuities
Exotic options
Transaction costs
Lecture notesSee: Link
LiteratureSee: Link
Prerequisites / NoticeThis course replaces "Continuous Time Quantitative Finance" (MFOEC108), which will be discontinued. Students who have taken "Continuous Time Quantitative Finance" (MFOEC108) in the past, are not allowed to book this course "Continuous Time Quantitative Finance" (MFOEC204).
227-0662-00LOrganic and Nanostructured Optics and Electronics (Course)
Does not take place this semester.
W3 credits2GV. Wood
AbstractThis course examines the optical and electronic properties of excitonic materials that can be leveraged to create thin-film light emitting devices and solar cells. Laboratory sessions provide students with experience in synthesis and optical characterization of nanomaterials as well as fabrication and characterization of thin film devices.
ObjectiveGain the knowledge and practical experience to begin research with organic or nanostructured materials and understand the key challenges in this rapidly emerging field.
Content0-Dimensional Excitonic Materials (organic molecules and colloidal quantum dots)

Energy Levels and Excited States (singlet and triplet states, optical absorption and luminescence).

Excitonic and Polaronic Processes (charge transport, Dexter and Förster energy transfer, and exciton diffusion).

Devices (photodetectors, solar cells, and light emitting devices).
LiteratureLecture notes and reading assignments from current literature to be posted on website.
227-0662-10LOrganic and Nanostructured Optics and Electronics (Project) Information Restricted registration - show details
Does not take place this semester.
W3 credits2AV. Wood
AbstractThis course examines the optical and electronic properties of excitonic materials that can be leveraged to create thin-film light emitting devices and solar cells. Laboratory sessions provide students with experience in synthesis and optical characterization of nanomaterials as well as fabrication and characterization of thin film devices.
ObjectiveGain the knowledge and practical experience to begin research with organic or nanostructured materials and understand the key challenges in this rapidly emerging field.
Content0-Dimensional Excitonic Materials (organic molecules and colloidal quantum dots)

Energy Levels and Excited States (singlet and triplet states, optical absorption and luminescence).

Excitonic and Polaronic Processes (charge transport, Dexter and Förster energy transfer, and exciton diffusion).

Devices (photodetectors, solar cells, and light emitting devices).
LiteratureLecture notes and reading assignments from current literature to be posted on website.
Prerequisites / NoticeAdmission is conditional to passing 227-0662-00L Organic and Nanostructured Optics and Electronics (Course)
262-0200-00LBayesian Phylodynamics – Taming the BEASTW4 credits2G + 2AT. Stadler, T. Vaughan
AbstractHow fast is COVID-19 spreading at the moment? How fast was Ebola spreading in West Africa? Where and when did these epidemic outbreak start? How can we construct the phylogenetic tree of great apes, and did gene flow occur between different apes? At the end of the course, students will have designed, performed, presented, and discussed their own phylodynamic data analysis to answer such questions.
ObjectiveAttendees will extend their knowledge of Bayesian phylodynamics obtained in the “Computational Biology” class (636-0017-00L) and will learn how to apply this theory to real world data. The main theoretical concepts introduced are:
* Bayesian statistics
* Phylogenetic and phylodynamic models
* Markov Chain Monte Carlo methods
Attendees will apply these concepts to a number of applications yielding biological insight into:
* Epidemiology
* Pathogen evolution
* Macroevolution of species
ContentDuring the first part of the block course, the theoretical concepts of Bayesian phylodynamics will be presented by us as well as leading international researchers in that area. The presentations will be followed by attendees using the software package BEAST v2 to apply these theoretical concepts to empirical data. We will use previously published datasets on e.g. COVID-19, Ebola, Zika, Yellow Fever, Apes, and Penguins for analysis. Examples of these practical tutorials are available on Link.
In the second part of the block course, students choose an empirical dataset of genetic sequencing data and possibly some non-genetic metadata. They then design and conduct a research project in which they perform Bayesian phylogenetic analyses of their dataset. A final written report on the research project has to be submitted after the block course for grading.
Lecture notesAll material will be available on Link.
LiteratureThe following books provide excellent background material:
• Drummond, A. & Bouckaert, R. 2015. Bayesian evolutionary analysis with BEAST.
• Yang, Z. 2014. Molecular Evolution: A Statistical Approach.
• Felsenstein, J. 2003. Inferring Phylogenies.
More detailed information is available on Link.
Prerequisites / NoticeThis class builds upon the content which we teach in the Computational Biology class (636-0017-00L). Attendees must have either taken the Computational Biology class or acquired the content elsewhere.
701-1708-00LInfectious Disease DynamicsW4 credits2VS. Bonhoeffer, R. D. Kouyos, R. R. Regös, T. Stadler
AbstractThis course introduces into current research on the population biology of infectious diseases. The course discusses the most important mathematical tools and their application to relevant diseases of human, natural or managed populations.
ObjectiveAttendees will learn about:
* the impact of important infectious pathogens and their evolution on human, natural and managed populations
* the population biological impact of interventions such as treatment or vaccination
* the impact of population structure on disease transmission

Attendees will learn how:
* the emergence spread of infectious diseases is described mathematically
* the impact of interventions can be predicted and optimized with mathematical models
* population biological models are parameterized from empirical data
* genetic information can be used to infer the population biology of the infectious disease

The course will focus on how the formal methods ("how") can be used to derive biological insights about the host-pathogen system ("about").
ContentAfter an introduction into the history of infectious diseases and epidemiology the course will discuss basic epidemiological models and the mathematical methods of their analysis. We will then discuss the population dynamical effects of intervention strategies such as vaccination and treatment. In the second part of the course we will introduce into more advanced topics such as the effect of spatial population structure, explicit contact structure, host heterogeneity, and stochasticity. In the final part of the course we will introduce basic concepts of phylogenetic analysis in the context of infectious diseases.
Lecture notesSlides and script of the lecture will be available online.
LiteratureThe course is not based on any of the textbooks below, but they are excellent choices as accompanying material:
* Keeling & Rohani, Modeling Infectious Diseases in Humans and Animals, Princeton Univ Press 2008
* Anderson & May, Infectious Diseases in Humans, Oxford Univ Press 1990
* Murray, Mathematical Biology, Springer 2002/3
* Nowak & May, Virus Dynamics, Oxford Univ Press 2000
* Holmes, The Evolution and Emergence of RNA Viruses, Oxford Univ Press 2009
Prerequisites / NoticeBasic knowledge of population dynamics and population genetics as well as linear algebra and analysis will be an advantage.
Case Studies
NumberTitleTypeECTSHoursLecturers
401-3667-21LCase Studies Seminar (Spring Semester 2021) Information W3 credits2SV. C. Gradinaru, R. Hiptmair, R. Käppeli, M. Reiher
AbstractIn the CSE Case Studies Seminar invited speakers from ETH, from other universities as well as from industry give a talk on an applied topic. Beside of attending the scientific talks students are asked to give short presentations (10 minutes) on a published paper out of a list.
Objective
ContentIn the CSE Case Studies Seminar invited speakers from ETH, from other universities as well as from industry give a talk on an applied topic. Beside of attending the scientific talks students are asked to give short presentations (10 minutes) on a published paper out of a list (containing articles from, e.g., Nature, Science, Scientific American, etc.). If the underlying paper comprises more than 15 pages, two or three consecutive case studies presentations delivered by different students can be based on it. Consistency in layout, style, and contents of those presentations is expected.
Prerequisites / NoticeIn Spring 2020 the talks will be given via Zoom.
About the video conferencing system Zoom:

Zoom is a do-it-yourself video conferencing system supported by ETH. With Zoom, one person can give a lecture with a presentation and up to 100 people can join in via chat or audio connection.Use the provided link to enter the Zoom room at the designated time. Download/Open the Zoom App or join the meeting via the browser. Please test whether you can join the room and whether the audio works properly beforehand. We recommend you use a headset in order to minimize unwanted sounds from your environment.

More Info:

Link
Link
Link
GESS Science in Perspective
Science in Perspective
» see Science in Perspective: Type A: Enhancement of Reflection Capability
» Recommended Science in Perspective (Type B) for D-MATH
Language Courses
» siehe Studiengang Wissenschaft im Kontext: Sprachkurse ETH/UZH
Colloquia
NumberTitleTypeECTSHoursLecturers
401-5650-00LZurich Colloquium in Applied and Computational Mathematics Information E-0 credits1KR. Abgrall, R. Alaifari, H. Ammari, R. Hiptmair, S. Mishra, S. Sauter, C. Schwab
AbstractResearch colloquium
Objective
  • First page Previous page Page  5  of  5     All