Search result: Catalogue data in Spring Semester 2021
|Computational Science and Engineering Bachelor|
|For All Programme Regulations|
In the ‘electives’ subcategory, at least two course units must be successfully completed.
|151-3202-00L||Product Development and Engineering Design |
Number of participants limited to 60.
|W||4 credits||2G||K. Shea, T. Stankovic|
|Abstract||The course introduces students to the product development process. In a team, you will explore the early phases of conceptual development and product design, from ideation and concept generation through to hands-on prototyping. This is an opportunity to gain product development experience and improve your skills in prototyping and presenting your product ideas. The project topic changes each year.|
|Objective||The course introduces you to the product development process and methods in engineering design for: product planning, user-centered design, creating product specifications, ideation including concept generation and selection methods, material selection methods and prototyping. Further topics include design for manufacture and design for additive manufacture. You will actively apply the process and methods learned throughout the semester in a team on a product development project including prototyping.|
|Content||Weekly topics accompanying the product development project include:|
1 Introduction to Product Development and Engineering Design
2 Product Planning and Social-Economic-Technology (SET) Factors
3 User-Centered Design and Product Specifications
4 Concept Generation and Selection Methods
5 System Design and Embodiment Design
6 Prototyping and Prototype Planning
7 Material Selection in Engineering Design
8 Design for Manufacture and Design for Additive Manufacture
|Lecture notes||available on Moodle|
|Literature||Ulrich, Eppinger, and Yang, Product Design and Development. 7th ed., McGraw-Hill Education, 2020.|
Cagan and Vogel, Creating Breakthrough Products: Revealing the Secrets that Drive Global Innovation, 2nd Edition, Pearson Education, 2013.
|Prerequisites / Notice||Although the course is offered to ME (BSc and MSc) and CS (BSc and MSc) students, priority will be given to ME BSc students in the Focus Design, Mechanics, and Materials if the course is full.|
|151-0840-00L||Optimization and Machine Learning|
Note: previous course title until FS20 "Principles of FEM-Based Optimization and Robustness Analysis".
|W||4 credits||2V + 2U||B. Berisha, D. Mohr|
|Abstract||The course teaches the basics of nonlinear optimization and concepts of machine learning. An introduction to the finite element method allows an extension of the application area to real engineering problems such as structural optimization and modeling of material behavior on different length scales.|
|Objective||Students will learn mathematical optimization methods including gradient based and gradient free methods as well as established algorithms in the context of machine learning to solve real engineering problems, which are generally non-linear in nature. Strategies to ensure efficient training of machine learning models based on large data sets define another teaching goal of the course. |
Optimization tools (MATLAB, LS-Opt, Python) and the finite element program ABAQUS are presented to solve both general and real engineering problems.
|Content||- Introduction into Nonlinear Optimization |
- Design of Experiments DoE
- Introduction into Nonlinear Finite Element Analysis
- Optimization based on Meta Modeling Techniques
- Shape and Topology Optimization
- Robustness and Sensitivity Analysis
- Fundamentals of Machine Learning
- Generalized methods for regression and classification, Neural Networks, Support Vector machines
- Supervised and unsupervised learning
|Lecture notes||Lecture slides and literature|
|151-0206-00L||Energy Systems and Power Engineering||W||4 credits||2V + 2U||R. S. Abhari, A. Steinfeld|
|Abstract||Introductory first course for the specialization in ENERGY. The course provides an overall view of the energy field and pertinent global problems, reviews some of the thermodynamic basics in energy conversion, and presents the state-of-the-art technology for power generation and fuel processing.|
|Objective||Introductory first course for the specialization in ENERGY. The course provides an overall view of the energy field and pertinent global problems, reviews some of the thermodynamic basics in energy conversion, and presents the state-of-the-art technology for power generation and fuel processing.|
|Content||World primary energy resources and use: fossil fuels, renewable energies, nuclear energy; present situation, trends, and future developments. Sustainable energy system and environmental impact of energy conversion and use: energy, economy and society. Electric power and the electricity economy worldwide and in Switzerland; production, consumption, alternatives. The electric power distribution system. Renewable energy and power: available techniques and their potential. Cost of electricity. Conventional power plants and their cycles; state-of-the-art and advanced cycles. Combined cycles and cogeneration; environmental benefits. Solar thermal; concentrated solar power; solar photovoltaics. Fuel cells: characteristics, fuel reforming and combined cycles.|
|Lecture notes||Vorlesungsunterlagen werden verteilt|
|151-0306-00L||Visualization, Simulation and Interaction - Virtual Reality I||W||4 credits||4G||A. Kunz|
|Abstract||Technology of Virtual Reality. Human factors, Creation of virtual worlds, Lighting models, Display- and acoustic- systems, Tracking, Haptic/tactile interaction, Motion platforms, Virtual prototypes, Data exchange, VR Complete systems, Augmented reality, Collaboration systems; VR and Design; Implementation of the VR in the industry; Human Computer Interfaces (HCI).|
|Objective||The product development process in the future will be characterized by the Digital Product which is the center point for concurrent engineering with teams spreas worldwide. Visualization and simulation of complex products including their physical behaviour at an early stage of development will be relevant in future. The lecture will give an overview to techniques for virtual reality, to their ability to visualize and to simulate objects. It will be shown how virtual reality is already used in the product development process.|
• Students are able to evaluate and select the most appropriate VR technology for a given task regarding:
o Visualization technologies displays/projection systems/head-mounted displays
o Tracking systems (inertia/optical/electromagnetic)
o Interaction technologies (sensing gloves/real walking/eye tracking/touch/etc.)
• Students are able to develop a VR application
• Students are able to apply VR to industrial needs
• Students will be able to apply the gained knowledge to a practical realization
• Students will be able to compare different operation principles (VR/AR/MR/XR)
|Content||Introduction to the world of virtual reality; development of new VR-techniques; introduction to 3D-computergraphics; modelling; physical based simulation; human factors; human interaction; equipment for virtual reality; display technologies; tracking systems; data gloves; interaction in virtual environment; navigation; collision detection; haptic and tactile interaction; rendering; VR-systems; VR-applications in industry, virtual mockup; data exchange, augmented reality.|
|Lecture notes||A complete version of the handout is also available in English.|
|Prerequisites / Notice||Voraussetzungen:|
Vorlesung geeignet für D-MAVT, D-ITET, D-MTEC und D-INF
Testat/ Kredit-Bedingungen/ Prüfung:
– Teilnahme an Vorlesung und Kolloquien
– Erfolgreiche Durchführung von Übungen in Teams
– Mündliche Einzelprüfung 30 Minuten
|151-0314-00L||Information Technologies in the Digital Product||W||4 credits||3G||E. Zwicker, R. Montau|
|Abstract||Objectives, Concepts and Methods of Digitalization, Digital Product and Product Lifecycle Management (PLM), Industry 4.0|
Concepts for Digitalization: Product Structures, Optimization of Engineering Processes with digital models in Sales, Production, Service, Digital Twin versus Digital Thread
PLM Fundamentals: Objects, Structures, Processes, Integrations, Visualization
|Objective||Students learn the fundamentals and concepts of Digitalization along the in the product lifecycle on the foundation of Product Lifecycle Management (PLM) technologies, the usage of databases, the integration of CAx systems and Visualization/AR, the configuration of computer-based collaboration leveraging IT-standards as well as variant and configuration management to enable an efficient utilization of the digital product approach in industry 4.0.|
|Content||Possibilities and potential of modern IT applications focussing on PLM and CAx technologies for targeted utilization in the context of product platform - business processes - IT tools. Introduction to the concepts of Product Lifecycle Management (PLM): information modeling, data management, revision, usage and distribution of product data. Structure and functional principles of PLM systems. Integration of new IT technologies in business processes. Possibilities of publication and automatic configuration of product variants via the Internet. Using state-of-the-art information and communication technologies to develop products globally across distributed locations. Interfaces in computer-integrated product development. Selection, configuration, adaptation and introduction of PLM systems. Examples and case studies for industrial usage of modern information technologies.|
- Introduction to Digitalization (Digital Product, PLM technology)
- Database technology (foundation of digitalization)
- Object Management
- Object Classification
- Object identification with Part Numbering Systems
- CAx/PLM integration with Visualization/AR
- Workflow & Change Management
- Interfaces of the Digital Product
- Enterprise Application Integration (EAI)
|Lecture notes||Didactic concept / learning materials:|
The course consists of lectures and exercises based on practical examples.
Provision of lecture handouts and script digitally in Moodle.
|Prerequisites / Notice||Prerequisites: None|
Recommended: Fokus-Project, interest in Digitalization
Lecture appropriate for D-MAVT, D-MTEC, D-ITET and D-INFK
Testat/Credit Requirements / Exam:
- execution of exercises in teams (recommended)
- Oral exam 30 minutes, based on concrete problem cases
|151-0660-00L||Model Predictive Control||W||4 credits||2V + 1U||M. Zeilinger, A. Carron|
|Abstract||Model predictive control is a flexible paradigm that defines the control law as an optimization problem, enabling the specification of time-domain objectives, high performance control of complex multivariable systems and the ability to explicitly enforce constraints on system behavior. This course provides an introduction to the theory and practice of MPC and covers advanced topics.|
|Objective||Design and implement Model Predictive Controllers (MPC) for various system classes to provide high performance controllers with desired properties (stability, tracking, robustness,..) for constrained systems.|
|Content||- Review of required optimal control theory|
- Basics on optimization
- Receding-horizon control (MPC) for constrained linear systems
- Theoretical properties of MPC: Constraint satisfaction and stability
- Computation: Explicit and online MPC
- Practical issues: Tracking and offset-free control of constrained systems, soft constraints
- Robust MPC: Robust constraint satisfaction
- Nonlinear MPC: Theory and computation
- Hybrid MPC: Modeling hybrid systems and logic, mixed-integer optimization
- Simulation-based project providing practical experience with MPC
|Lecture notes||Script / lecture notes will be provided.|
|Prerequisites / Notice||One semester course on automatic control, Matlab, linear algebra.|
Courses on signals and systems and system modeling are recommended. Important concepts to start the course: State-space modeling, basic concepts of stability, linear quadratic regulation / unconstrained optimal control.
Expected student activities: Participation in lectures, exercises and course project; homework (~2hrs/week).
|151-0940-00L||Modelling and Mathematical Methods in Process and Chemical Engineering||W||4 credits||3G||M. Mazzotti|
|Abstract||Study of the non-numerical solution of systems of ordinary differential equations and first order partial differential equations, with application to chemical kinetics, simple batch distillation, and chromatography.|
|Objective||Study of the non-numerical solution of systems of ordinary differential equations and first order partial differential equations, with application to chemical kinetics, simple batch distillation, and chromatography.|
|Content||Development of mathematical models in process and chemical engineering, particularly for chemical kinetics, batch distillation, and chromatography. Study of systems of ordinary differential equations (ODEs), their stability, and their qualitative analysis. Study of single first order partial differential equation (PDE) in space and time, using the method of characteristics. Application of the theory of ODEs to population dynamics, chemical kinetics (Belousov-Zhabotinsky reaction), and simple batch distillation (residue curve maps). Application of the method of characteristic to chromatography.|
|Lecture notes||no skript|
|Literature||A. Varma, M. Morbidelli, "Mathematical methods in chemical engineering," Oxford University Press (1997) |
H.K. Rhee, R. Aris, N.R. Amundson, "First-order partial differential equations. Vol. 1," Dover Publications, New York (1986)
R. Aris, "Mathematical modeling: A chemical engineer’s perspective," Academic Press, San Diego (1999)
|151-0980-00L||Biofluiddynamics||W||4 credits||2V + 1U||D. Obrist, P. Jenny|
|Abstract||Introduction to the fluid dynamics of the human body and the modeling of physiological flow processes (biomedical fluid dynamics).|
|Objective||A basic understanding of fluid dynamical processes in the human body. Knowledge of the basic concepts of fluid dynamics and the ability to apply these concepts appropriately.|
|Content||This lecture is an introduction to the fluid dynamics of the human body (biomedical fluid dynamics). For selected topics of human physiology, we introduce fundamental concepts of fluid dynamics (e.g., creeping flow, incompressible flow, flow in porous media, flow with particles, fluid-structure interaction) and use them to model physiological flow processes. The list of studied topics includes the cardiovascular system and related diseases, blood rheology, microcirculation, respiratory fluid dynamics and fluid dynamics of the inner ear.|
|Lecture notes||Lecture notes are provided electronically.|
|Literature||A list of books on selected topics of biofluiddynamics can be found on the course web page.|
|227-0052-10L||Electromagnetic Fields and Waves||W||4 credits||2V + 2U||L. Novotny|
|Abstract||This course is focused on the generation and propagation of electromagnetic fields. Based on Maxwell's equations we will derive the wave equation and its solutions. Specifically, we will discuss fields and waves in free space, refraction and reflection at plane interfaces, dipole radiation and Green functions, vector and scalar potentials, as well as gauge transformations.|
|Objective||Understanding of electromagnetic fields|
|227-0418-00L||Algebra and Error Correcting Codes||W||6 credits||4G||H.‑A. Loeliger|
|Abstract||The course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course includes a self-contained introduction of the pertinent basics of "abstract" algebra.|
|Objective||The course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course includes a self-contained introduction of the pertinent basics of "abstract" algebra.|
|Content||Error correcting codes: coding and modulation, linear codes, Hamming space codes, Euclidean space codes, trellises and Viterbi decoding, convolutional codes, factor graphs and message passing algorithms, low-density parity check codes, turbo codes, polar codes, Reed-Solomon codes.|
Algebra: groups, rings, homomorphisms, quotient groups, ideals, finite fields, vector spaces, polynomials.
|Lecture notes||Lecture Notes (english)|
|227-0420-00L||Information Theory II||W||6 credits||4G||A. Lapidoth, S. M. Moser|
|Abstract||This course builds on Information Theory I. It introduces additional topics in single-user communication, connections between Information Theory and Statistics, and Network Information Theory.|
|Objective||The course's objective is to introduce the students to additional information measures and to equip them with the tools that are needed to conduct research in Information Theory as it relates to Communication Networks and to Statistics.|
|Content||Sanov's Theorem, Rényi entropy and guessing, differential entropy, maximum entropy, the Gaussian channel, the entropy-power inequality, the broadcast channel, the multiple-access channel, Slepian-Wolf coding, the Gelfand-Pinsker problem, and Fisher information.|
|Literature||T.M. Cover and J.A. Thomas, Elements of Information Theory, second edition, Wiley 2006|
|Prerequisites / Notice||Basic introductory course on Information Theory.|
|227-0104-00L||Communication and Detection Theory||W||6 credits||4G||A. Lapidoth|
|Abstract||This course teaches the foundations of modern digital communications and detection theory. Topics include the geometry of the space of energy-limited signals; the baseband representation of passband signals, spectral efficiency and the Nyquist Criterion; the power and power spectral density of PAM and QAM; hypothesis testing; Gaussian stochastic processes; and detection in white Gaussian noise.|
|Objective||This is an introductory class to the field of wired and wireless communication. It offers a glimpse at classical analog modulation (AM, FM), but mainly focuses on aspects of modern digital communication, including modulation schemes, spectral efficiency, power budget analysis, block and convolu- tional codes, receiver design, and multi- accessing schemes such as TDMA, FDMA and Spread Spectrum.|
|Content||- Baseband representation of passband signals.|
- Bandwidth and inner products in baseband and passband.
- The geometry of the space of energy-limited signals.
- The Sampling Theorem as an orthonormal expansion.
- Sampling passband signals.
- Pulse Amplitude Modulation (PAM): energy, power, and power spectral density.
- Nyquist Pulses.
- Quadrature Amplitude Modulation (QAM).
- Hypothesis testing.
- The Bhattacharyya Bound.
- The multivariate Gaussian distribution
- Gaussian stochastic processes.
- Detection in white Gaussian noise.
|Literature||A. Lapidoth, A Foundation in Digital Communication, Cambridge University Press, 2nd edition (2017)|
|227-0120-00L||Communication Networks||W||6 credits||4G||L. Vanbever|
|Abstract||At the end of this course, you will understand the fundamental concepts behind communication networks and the Internet. Specifically, you will be able to:|
- understand how the Internet works;
- build and operate Internet-like infrastructures;
- identify the right set of metrics to evaluate the performance of a network and propose ways to improve it.
|Objective||At the end of the course, the students will understand the fundamental concepts of communication networks and Internet-based communications. Specifically, students will be able to:|
- understand how the Internet works;
- build and operate Internet-like network infrastructures;
- identify the right set of metrics to evaluate the performance or the adequacy of a network and propose ways to improve it (if any).
The course will introduce the relevant mechanisms used in today's networks both from an abstract perspective but also from a practical one by presenting many real-world examples and through multiple hands-on projects.
For more information about the lecture, please visit: https://comm-net.ethz.ch
|Lecture notes||Lecture notes and material for the course will be available before each course on: https://comm-net.ethz.ch|
|Literature||Most of course follows the textbook "Computer Networking: A Top-Down Approach (6th Edition)" by Kurose and Ross.|
|Prerequisites / Notice||No prior networking background is needed. The course will include some programming assignments (in Python) for which the material covered in Technische Informatik 1 (227-0013-00L) will be useful.|
|227-0159-00L||Semiconductor Devices: Quantum Transport at the Nanoscale||W||6 credits||2V + 2U||M. Luisier, A. Emboras|
|Abstract||This class offers an introduction into quantum transport theory, a rigorous approach to electron transport at the nanoscale. It covers different topics such as bandstructure, Wave Function and Non-equilibrium Green's Function formalisms, and electron interactions with their environment. Matlab exercises accompany the lectures where students learn how to develop their own transport simulator.|
|Objective||The continuous scaling of electronic devices has given rise to structures whose dimensions do not exceed a few atomic layers. At this size, electrons do not behave as particle any more, but as propagating waves and the classical representation of electron transport as the sum of drift-diffusion processes fails. The purpose of this class is to explore and understand the displacement of electrons through nanoscale device structures based on state-of-the-art quantum transport methods and to get familiar with the underlying equations by developing his own nanoelectronic device simulator.|
|Content||The following topics will be addressed:|
- Introduction to quantum transport modeling
- Bandstructure representation and effective mass approximation
- Open vs closed boundary conditions to the Schrödinger equation
- Comparison of the Wave Function and Non-equilibrium Green's Function formalisms as solution to the Schrödinger equation
- Self-consistent Schödinger-Poisson simulations
- Quantum transport simulations of resonant tunneling diodes and quantum well nano-transistors
- Top-of-the-barrier simulation approach to nano-transistor
- Electron interactions with their environment (phonon, roughness, impurity,...)
- Multi-band transport models
|Lecture notes||Lecture slides are distributed every week and can be found at|
|Literature||Recommended textbook: "Electronic Transport in Mesoscopic Systems", Supriyo Datta, Cambridge Studies in Semiconductor Physics and Microelectronic Engineering, 1997|
|Prerequisites / Notice||Basic knowledge of semiconductor device physics and quantum mechanics|
|227-0558-00L||Principles of Distributed Computing||W||7 credits||2V + 2U + 2A||R. Wattenhofer, M. Ghaffari|
|Abstract||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.|
|Objective||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.|
|Content||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
|Lecture notes||Available. Our course script is used at dozens of other universities around the world.|
|Literature||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
Society for Industrial and Applied Mathematics (SIAM), 2000, ISBN 0-89871-464-8
|Prerequisites / Notice||Course pre-requisites: Interest in algorithmic problems. (No particular course needed.)|
|252-0211-00L||Information Security||W||8 credits||4V + 3U||D. Basin, S. Capkun|
|Abstract||This course provides an introduction to Information Security. The focus|
is on fundamental concepts and models, basic cryptography, protocols and system security, and privacy and data protection. While the emphasis is on foundations, case studies will be given that examine different realizations of these ideas in practice.
|Objective||Master fundamental concepts in Information Security and their|
application to system building. (See objectives listed below for more details).
|Content||1. Introduction and Motivation (OBJECTIVE: Broad conceptual overview of information security) Motivation: implications of IT on society/economy, Classical security problems, Approaches to |
defining security and security goals, Abstractions, assumptions, and trust, Risk management and the human factor, Course verview. 2. Foundations of Cryptography (OBJECTIVE: Understand basic
cryptographic mechanisms and applications) Introduction, Basic concepts in cryptography: Overview, Types of Security, computational hardness, Abstraction of channel security properties, Symmetric
encryption, Hash functions, Message authentication codes, Public-key distribution, Public-key cryptosystems, Digital signatures, Application case studies, Comparison of encryption at different layers, VPN, SSL, Digital payment systems, blind signatures, e-cash, Time stamping 3. Key Management and Public-key Infrastructures (OBJECTIVE: Understand the basic mechanisms relevant in an Internet context) Key management in distributed systems, Exact characterization of requirements, the role of trust, Public-key Certificates, Public-key Infrastructures, Digital evidence and non-repudiation, Application case studies, Kerberos, X.509, PGP. 4. Security Protocols (OBJECTIVE: Understand network-oriented security, i.e.. how to employ building blocks to secure applications in (open) networks) Introduction, Requirements/properties, Establishing shared secrets, Principal and message origin authentication, Environmental assumptions, Dolev-Yao intruder model and
variants, Illustrative examples, Formal models and reasoning, Trace-based interleaving semantics, Inductive verification, or model-checking for falsification, Techniques for protocol design,
Application case study 1: from Needham-Schroeder Shared-Key to Kerberos, Application case study 2: from DH to IKE. 5. Access Control and Security Policies (OBJECTIVES: Study system-oriented security, i.e., policies, models, and mechanisms) Motivation (relationship to CIA, relationship to Crypto) and examples Concepts: policies versus models versus mechanisms, DAC and MAC, Modeling formalism, Access Control Matrix Model, Roll Based Access Control, Bell-LaPadula, Harrison-Ruzzo-Ullmann, Information flow, Chinese Wall, Biba, Clark-Wilson, System mechanisms: Operating Systems, Hardware Security Features, Reference Monitors, File-system protection, Application case studies 6. Anonymity and Privacy (OBJECTIVE: examine protection goals beyond standard CIA and corresponding mechanisms) Motivation and Definitions, Privacy, policies and policy languages, mechanisms, problems, Anonymity: simple mechanisms (pseudonyms, proxies), Application case studies: mix networks and crowds. 7. Larger application case study: GSM, mobility
|263-4660-00L||Applied Cryptography |
Number of participants limited to 150.
|W||8 credits||3V + 2U + 2P||K. Paterson|
|Abstract||This course will introduce the basic primitives of cryptography, using rigorous syntax and game-based security definitions. The course will show how these primitives can be combined to build cryptographic protocols and systems.|
|Objective||The goal of the course is to put students' understanding of cryptography on sound foundations, to enable them to start to build well-designed cryptographic systems, and to expose them to some of the pitfalls that arise when doing so.|
|Content||Basic symmetric primitives (block ciphers, modes, hash functions); generic composition; AEAD; basic secure channels; basic public key primitives (encryption,signature, DH key exchange); ECC; randomness; applications.|
|Literature||Textbook: Boneh and Shoup, “A Graduate Course in Applied Cryptography”, https://crypto.stanford.edu/~dabo/cryptobook/BonehShoup_0_4.pdf.|
|Prerequisites / Notice||Students should have taken the D-INFK Bachelor's course “Information Security" (252-0211-00) or an alternative first course covering cryptography at a similar level. / In this course, we will use Moodle for content delivery: https://moodle-app2.let.ethz.ch/course/view.php?id=14558.|
|252-0570-00L||Game Programming Laboratory |
In the Master Programme max. 10 credits can be accounted by Labs on top of the Interfocus Courses. Additional Labs will be listed on the Addendum.
|W||10 credits||9P||B. Sumner|
|Abstract||The goal of this course is the in-depth understanding of the technology and programming underlying computer games. Students gradually design and develop a computer game in small groups and get acquainted with the art of game programming.|
|Objective||The goal of this new course is to acquaint students with the|
technology and art of programming modern three-dimensional computer
|Content||This course addresses modern three-dimensional computer game technology. During the course, small groups of students will design and develop a computer game. Focus will be put on technical aspects of game development, such as rendering, cinematography, interaction, physics, animation, and AI. In addition, we will cultivate creative thinking for advanced gameplay and visual effects. |
The "laboratory" format involves a practical, hands-on approach with traditional lectures. We will meet once a week to discuss technical issues and to track progress. For development we use MonoGames, which is a collection of libraries and tools that facilitate game development. While development will take place on PCs, we will ultimately deployour games on the Xbox One console.
At the end of the course we will present our results to the public.
|Lecture notes||Game Design Workshop: A Playcentric Approach to Creating Innovative Games by Tracy Fullerton|
|Prerequisites / Notice||The number of participants is limited.|
- Good programming skills (Java, C++, C#, etc.)
- CG experience: Students should have taken, at a minimum, Visual
Computing. Higher level courses are recommended, such as Introduction
to Computer Graphics, Surface Representations and Geometric Modeling,
and Physically-based Simulation in Computer Graphics.
|252-0538-00L||Shape Modeling and Geometry Processing||W||8 credits||2V + 1U + 4A||O. Sorkine Hornung|
|Abstract||This course covers the fundamentals and some of the latest developments in geometric modeling and geometry processing. Topics include surface modeling based on point clouds and polygonal meshes, mesh generation, surface reconstruction, mesh fairing and parameterization, discrete differential geometry, interactive shape editing, topics in digital shape fabrication.|
|Objective||The students will learn how to design, program and analyze algorithms and systems for interactive 3D shape modeling and geometry processing.|
|Content||Recent advances in 3D geometry processing have created a plenitude of novel concepts for the mathematical representation and interactive manipulation of geometric models. This course covers the fundamentals and some of the latest developments in geometric modeling and geometry processing. Topics include surface modeling based on point clouds and triangle meshes, mesh generation, surface reconstruction, mesh fairing and parameterization, discrete differential geometry, interactive shape editing and digital shape fabrication.|
|Lecture notes||Slides and course notes|
|Prerequisites / Notice||Prerequisites:|
Visual Computing, Computer Graphics or an equivalent class. Experience with C++ programming. Solid background in linear algebra and analysis. Some knowledge of differential geometry, computational geometry and numerical methods is helpful but not a strict requirement.
|263-5806-00L||Computational Models of Motion||W||8 credits||2V + 2U + 3A||S. Coros, M. Bächer, B. Thomaszewski|
|Abstract||This course covers fundamentals of physics-based modelling and numerical optimization from the perspective of character animation and robotics applications. The methods discussed in class derive their theoretical underpinnings from applied mathematics, control theory and computational mechanics, and they will be richly illustrated using examples ranging from locomotion controllers and crowd simula|
|Objective||Students will learn how to represent, model and algorithmically control the behavior of animated characters and real-life robots. The lectures are accompanied by programming assignments (written in C++) and a capstone project.|
|Content||Optimal control and trajectory optimization; multibody systems; kinematics; forward and inverse dynamics; constrained and unconstrained numerical optimization; mass-spring models for crowd simulation; FEM; compliant systems; sim-to-real; robotic manipulation of elastically-deforming objects.|
|Prerequisites / Notice||Experience with C++ programming, numerical linear algebra and multivariate calculus. Some background in physics-based modeling, kinematics and dynamics is helpful, but not necessary.|
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