Search result: Catalogue data in Spring Semester 2022
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 SeminarStudents may also choose a seminar from the Master's program in Computer Science. It is their responsibility to make sure that they meet the requirements and conditions for this seminar. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 252-3810-00L | Datacenter Network Monitoring and Management  Number of participants limited to 22. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | D. Wagenknecht-Dimitrova | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The seminar addresses questions of network monitoring in datacenters, with focus on security. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The seminar addresses questions of network monitoring in datacenters, with focus on security. Students will learn about network threats and approaches to prevent and resolve those. Both traditional distributed and modern programmable networks will be discussed. Special attention will be given to the challenge of data collection and data processing for security purposes. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The seminar focuses on papers in high quality conferences, and whitepapers and blogs from leading industry. Real world incidents will be covered where appropriate. Background reading on datacenter networks and software defined networks is also included. The seminar attempts to strike a balance between understanding the fundamentals and keeping up with novel developments. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 252-4225-00L | Presenting Theoretical Computer Science Number of participants limited to 24. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | B. Gärtner, R. Kyng, A. Steger, D. Steurer, E. Welzl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Students present current or classical results from theoretical computer science. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students learn to read, understand and present results from theoretical computer science. The main focus and deliverable is a good presentation of 45 minutes that can easily be followed and understood by the audience. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Students present current or classical results from theoretical computer science. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The seminar takes place as a block seminar on two Saturdays in April and/or May. Each presentation is jointly prepared and given by two students (procedure according to the seminar's Moodle page). All students must attend all presentations. Participation requires successful completion of the first year, or instructor approval. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-4910-00L | Randomized Algorithms The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. Number of participants limited to 24. | W | 2 credits | 2S | H.‑J. Böckenhauer, R. Kralovic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | We look into randomized approaches for dealing with computational problems. A randomized algorithm uses random decisions to guide its computation. Its quality is measured in a worst-case manner over all instances by a probability distribution over the taken random decisions. We analyze different design methods and error models. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | To systematically acquire an overview of the methods for designing randomized algorithms. To get deeper knowledge of the classification of randomized algorithms according to error models. To learn how to analyze the error probability of randomized algorithms.To learn about typical applications for randomized computations. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | In this seminar, we discuss how randomization can help to speed up algorithms for various computational problems. In the kick-off meeting, we will give a brief overview of modeling and classifying randomized algorithms. Then, each participant will study one aspect of this topic, following a specific scientific publication, and will give a presentation about this topic. The topics will include design methods for randomized algorithms like fingerprinting, foiling an adversary, random sampling, randomized rounding as well as the classification of randomized algorithms according to their error (e.g., Las Vegas vs. Monte Carlo algorithms). The considered problems will include, among others, hashing, primality testing, communication protocols, maximum satisfiability. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | The literature will consist of textbook chapters and original research papers and will be provided during the kick-off meeting. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The participants should be familiar with the content of the lectures "Algorithmen und Datenstrukturen" (252-0026-00) and "Theoretische Informatik" (252-0057-00). The presentations will be given in the form of a block course in the second week of June 2022. The language can be mixed in German and English in the following sense: The teaching material will be in English, but it will be possible for at least half of the participants to give their presentations and hand in their written summaries in German. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-2211-00L | Seminar in Computer Architecture Number of participants limited to 22. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | O. Mutlu, M. H. K. Alser, J. Gómez Luna | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This seminar course covers fundamental and cutting-edge research papers in computer architecture. It has multiple components that are aimed at improving students' (1) technical skills in computer architecture, (2) critical thinking and analysis abilities on computer architecture concepts, as well as (3) technical presentation of concepts and papers in both spoken and written forms. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The main objective is to learn how to rigorously analyze and present papers and ideas on computer architecture. We will have rigorous presentation and discussion of selected papers during lectures and a written report delivered by each student at the end of the semester. This course is for those interested in computer architecture. Registered students are expected to attend every meeting, participate in the discussion, and create a synthesis report at the end of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Topics will center around computer architecture. We will, for example, discuss papers on hardware security; accelerators for key applications like machine learning, graph processing and bioinformatics; memory systems; interconnects; processing in memory; various fundamental and emerging paradigms in computer architecture; hardware/software co-design and cooperation; fault tolerance; energy efficiency; heterogeneous and parallel systems; new execution models; predictable computing, etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | All materials will be posted on the course website: https://safari.ethz.ch/architecture_seminar/ Past course materials, including the synthesis report assignment, can be found in the Fall 2020 website for the course: https://safari.ethz.ch/architecture_seminar/fall2020/doku.php | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Key papers and articles, on both fundamentals and cutting-edge topics in computer architecture will be provided and discussed. These will be posted on the course website. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Design of Digital Circuits. Students should (1) have done very well in Design of Digital Circuits and (2) show a genuine interest in Computer Architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 101-0531-00L | Digitalization for Circular Construction (D4C^2) All students who register go onto a waiting list and 25 of them will be selected by the lecturer | W | 4 credits | 9P | C. De Wolf | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Students will learn about digital innovations for circular construction (e.g. reuse of materials) through hands-on learning: they will be accompanied on demolition sites to recover and reclaim building materials, they will learn how to use computational tools to design structures with an available stock of materials, and they will use digital fabrication techniques to build a dome on campus. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The project has several goals: •Teach students about the challenges of reuse in the built environment and how to overcome them in order to transition the construction sector from a linear to a circular economy – this can only be done through the proposed industry collaboration and hands-on, on-site learning. •Show students how to design and built from A to Z: many engineering and architecture students end up acquiring amazing design skills, but have never been on a demolition site to disassemble the structure themselves – this course will offer this experience to them. •Demonstrate how we can bring together two worlds that are often too distinct: low-impact construction and digital innovation – this course will explore which digital tools already used in other sectors could be beneficial for reuse and low-carbon construction. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | This is a workshop-based course on circular construction on-site. During the first workshop, students will use photogrammetry from drone imagery and LiDAR scanning to capture data on building materials; Scan-to-BIM techniques for geometric reconstruction based on point-clouds; and computer-vision techniques for identifying material geometries, types, and conditions in order to make an inventory of available materials. During the second workshop, my industry partners (e.g., Baubüro in situ, Materiuum, Rotor) and I will work with the students on the disassembly of the building in a non-destructive way. During the third workshop, students will learn to use computational design tools to structurally optimize their structure’s shape with the available stock of materials. Finally, during the fourth workshop, students will build a dome structure with the reclaimed materials on the ETH campus. This class will enable students to explore all digital tools available (assessment, disassembly, design, and reassembly) for circular construction on a real-world case study. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Workshop-based course & hands-on learning. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Sustainability – Circular Economy in the Digital Age special issue Çetin, S., De Wolf, C., Bocken, N. “Circular Digital Built Environment: An Emerging Framework.” 13, 6348, DOI: 10.3390/su13116348 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Interest in Digitalisation and Construction. MIBS students: 3rd semester on higher are eligible to apply. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 151-0854-00L | Autonomous Mobile Robots | W | 5 credits | 4G | R. Siegwart, M. Chli, N. Lawrance | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The objective of this course is to provide the basics required to develop autonomous mobile robots and systems. Main emphasis is put on mobile robot locomotion and kinematics, environment perception, and probabilistic environment modeling, localization, mapping and navigation. Theory will be deepened by exercises with small mobile robots and discussed across application examples. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The objective of this course is to provide the basics required to develop autonomous mobile robots and systems. Main emphasis is put on mobile robot locomotion and kinematics, environment perception, and probabilistic environment modeling, localization, mapping and navigation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | This lecture is enhanced by around 30 small videos introducing the core topics, and multiple-choice questions for continuous self-evaluation. It is developed along the TORQUE (Tiny, Open-with-Restrictions courses focused on QUality and Effectiveness) concept, which is ETH's response to the popular MOOC (Massive Open Online Course) concept. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | This lecture is based on the Textbook: Introduction to Autonomous Mobile Robots Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza, The MIT Press, Second Edition 2011, ISBN: 978-0262015356 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-0075-00L | Electrical Engineering I | W | 3 credits | 2V + 2U | J. Leuthold | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Basic course in electrical engineering with the following topics: Concepts of voltage and currents; Analyses of dc and ac networks; Series and parallel resistive circuits, circuits including capacitors and inductors; Kirchhoff's laws and other network theorems; Transient responses; Basics of electrical and magnetic fields; | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Understanding of the basic concepts in electrical engineering with focus on network theory. The successful student knows the basic components of electrical circuits and the network theorems after attending the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Diese Vorlesung vermittelt Grundlagenkenntnisse im Fachgebiet Elektrotechnik. Ausgehend von den grundlegenden Konzepten der Spannung und des Stroms wird die Analyse von Netzwerken bei Gleich- und Wechselstrom behandelt. Dabie werden folgende Themen behandelt: Kapitel 1 Das elektrostatische Feld Kapitel 2 Das stationäre elektrische Strömungsfeld Kapitel 3 Einfache elektrische Netzwerke Kapitel 4 Halbleiterbauelemente (Dioden, der Transistor) Kapitel 5 Das stationäre Magnetfeld Kapitel 6 Das zeitlich veränderliche elektromagnetische Feld Kapitel 7 Der Übergang zu den zeitabhängigen Strom- und Spannungsformen Kapitel 8 Wechselspannung und Wechselstrom | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Die Vorlesungsfolien werden auf Moodle bereitgestellt. Als ausführliches Skript wird das Buch "Manfred Albach. Elektrotechnik, Person Verlag, Ausgabe vom 1.8.2011" empfohlen. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Für das weitergehende Studium werden in der Vorlesung verschiedene Bücher vorgestellt. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-0123-00L | Mechatronics | W | 6 credits | 4G | T. M. Gempp | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Introduction into mechatronics. Sensors and actors. Electronic and hydraulic power amplifiers. Data processing and basics of real-time programming, multitasking, and multiprocessing. Modeling of mechatronical systems. Geometric, kinematical, and dynamic elements. Fundamentals of the systems theory. Examples from industrial applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Introduction into the basics and technology of mechatronical devices. Theoretical and practical know-how of the basic elements of a mechatronical system. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Introduction into mechatronics. Sensors and actors. Electronic and hydraulic power amplifiers. Data processing and basics of real-time programming, multitasking, and multiprocessing. Modeling of mechatronical systems. Geometric, kinematical, and dynamic elements. Fundamentals of the systems theory. Examples from industrial applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Recommendation of textbook. Additional documentation to the individual topics. Documentation from industrial companies. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Basic knowledge in electrical engineering and mechanics | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-0707-00L | Optimization Methods for Engineers | W | 3 credits | 2G | J. Smajic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | First half of the semester: Introduction to the main methods of numerical optimization with focus on stochastic methods such as genetic algorithms, evolutionary strategies, etc. Second half of the semester: Each participant implements a selected optimizer and applies it on a problem of practical interest. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Numerical optimization is of increasing importance for the development of devices and for the design of numerical methods. The students shall learn to select, improve, and combine appropriate procedures for efficiently solving practical problems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Typical optimization problems and their difficulties are outlined. Well-known deterministic search strategies, combinatorial minimization, and evolutionary algorithms are presented and compared. In engineering, optimization problems are often very complex. Therefore, new techniques based on the generalization and combination of known methods are discussed. To illustrate the procedure, various problems of practical interest are presented and solved with different optimization codes. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | PDF of a short skript (39 pages) plus the view graphs are provided | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Lecture only in the first half of the semester, exercises in form of small projects in the second half, presentation of the results in the last week of the semester. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-0803-00L | Energy, Resources, Environment: Risks and Prospects | W | 6 credits | 4G | O. Zenklusen, T. Flüeler | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Multidisciplinary, interactive course focusing on the complexity of environmental and energy problems. Concepts of risk theory, decision science, long-term governance and environmental economics are applied to case studies related to energy transition and climate change. The course is designed for a multidisciplinary audience and as a training ground for critical thinking. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Develop capacities for addressing environmental problems, scrutinising proposed solutions and contributing to debates across disciplines. Analyse complex issues from different perspectives. Understand interactions between the environment, science and technology, society and economy. Develop skills in critical thinking, scientific writing and presenting. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Following a multidisciplinary outline of current issues in environmental and energy policy as well as the concept of "messy problems”, the course introduces theoretical and analytical approaches including risk, sustainability, as well as elements of institutional design and environmental economics. Large parts of the course are dedicated to case studies and contributions from participants. These serve for applying concepts to concrete challenges and as starting points for debates. Topics include: energy transition, innovation, the potential of renewable energy, carbon markets, the future of nuclear energy, climate change and development policy, long-term issues in various fields, disaster risk, the use of non-renewable resources, as well as visions such as 2000-watt society. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Presentations and reader provided in electronic formats. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Reader provided in electronic formats. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | - | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-0945-10L | Cell and Molecular Biology for Engineers II This course is part II of a two-semester course. Knowledge of part I is required. | W | 3 credits | 2G | C. Frei | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course gives an introduction into cellular and molecular biology, specifically for students with a background in engineering. The focus will be on the basic organization of eukaryotic cells, molecular mechanisms and cellular functions. Textbook knowledge will be combined with results from recent research and technological innovations in biology. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | After completing this course, engineering students will be able to apply their previous training in the quantitative and physical sciences to modern biology. Students will also learn the principles how biological models are established, and how these models can be tested. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Lectures will include the following topics (part I and II): DNA, chromosomes, genome engineering, RNA, proteins, genetics, synthetic biology, gene expression, membrane structure and function, vesicular traffic, cellular communication, energy conversion, cytoskeleton, cell cycle, cellular growth, apoptosis, autophagy, cancer and stem cells. In addition, 4 journal clubs will be held, where recent publications will be discussed (2 journal clubs in part I and 2 journal clubs in part II). For each journal club, students (alone or in groups of up to three students) have to write a summary and discussion of the publication. These written documents will be graded and count as 40% for the final grade. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Scripts of all lectures will be available. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | "Molecular Biology of the Cell" (6th edition) by Alberts, Johnson, Lewis, Morgan, Raff, Roberts, and Walter. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-1046-00L | Computer Simulations of Sensory Systems Does not take place this semester. | W | 3 credits | 3G | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course deals with computer simulations of the human auditory, visual, and balance system. The lecture will cover the physiological and mechanical mechanisms of these sensory systems. And in the exercises, the simulations will be implemented with Python. The simulations will be such that their output could be used as input for actual neuro-sensory prostheses. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Our sensory systems provide us with information about what is happening in the world surrounding us. Thereby they transform incoming mechanical, electromagnetic, and chemical signals into “action potentials”, the language of the central nervous system. The main goal of this lecture is to describe how our sensors achieve these transformations, how they can be reproduced with computational tools. For example, our auditory system performs approximately a “Fourier transformation” of the incoming sound waves; our early visual system is optimized for finding edges in images that are projected onto our retina; and our balance system can be well described with a “control system” that transforms linear and rotational movements into nerve impulses. In the exercises that go with this lecture, we will use Python to reproduce the transformations achieved by our sensory systems. The goal is to write programs whose output could be used as input for actual neurosensory prostheses: such prostheses have become commonplace for the auditory system, and are under development for the visual and the balance system. For the corresponding exercises, at least some basic programing experience is required!! | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The following topics will be covered: • Introduction into the signal processing in nerve cells. • Introduction into Python. • Simplified simulation of nerve cells (Hodgkins-Huxley model). • Description of the auditory system, including the application of Fourier transforms on recorded sounds. • Description of the visual system, including the retina and the information processing in the visual cortex. The corresponding exercises will provide an introduction to digital image processing. • Description of the mechanics of our balance system, and the “Control System”-language that can be used for an efficient description of the corresponding signal processing (essentially Laplace transforms and control systems). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | For each module additional material will be provided on the e-learning platform "moodle". The main content of the lecture is also available as a wikibook, under http://en.wikibooks.org/wiki/Sensory_Systems | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Open source information is available as wikibook http://en.wikibooks.org/wiki/Sensory_Systems For good overviews of the neuroscience, I recommend: • Principles of Neural Science (5th Ed, 2012), by Eric Kandel, James Schwartz, Thomas Jessell, Steven Siegelbaum, A.J. Hudspeth ISBN 0071390111 / 9780071390118 THE standard textbook on neuroscience. NOTE: The 6th edition will be released on February 5, 2021! • L. R. Squire, D. Berg, F. E. Bloom, Lac S. du, A. Ghosh, and N. C. Spitzer. Fundamental Neuroscience, Academic Press - Elsevier, 2012 [ISBN: 9780123858702]. This book covers the biological components, from the functioning of an individual ion channels through the various senses, all the way to consciousness. And while it does not cover the computational aspects, it nevertheless provides an excellent overview of the underlying neural processes of sensory systems. • G. Mather. Foundations of Sensation and Perception, 2nd Ed Psychology Press, 2009 [ISBN: 978-1-84169-698-0 (hardcover), oder 978-1-84169-699-7 (paperback)] A coherent, up-to-date introduction to the basic facts and theories concerning human sensory perception. • The best place to get started with Python programming are the https://scipy-lectures.org/ On signal processing with Python, my upcoming book • Hands-on Signal Analysis with Python (Due: January 13, 2021 ISBN 978-3-030-57902-9, https://www.springer.com/gp/book/9783030579029) will contain an explanation to all the required programming tools and packages. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | • Since I have to gravel from Linz, Austria, to Zurich to give this lecture, I plan to hold this lecture in blocks (every 2nd week). • In addition to the lectures, this course includes external lab visits to institutes actively involved in research on the relevant sensory systems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-5053-00L | What Kind of AI Do We Want? Bringing Artistic and Technological Practices Together | W | 2 credits | 3S | N. Gräfin von Reischach, A. C. Notz | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | In this seminar we look at "artificial intelligence" (AI) as a historical-material practice. That is, we understand AI as shaped by the concrete conditions of its development and use. We will address the current discourse within our democratically shaped society around trustworthy AI and look at decolonial and indigenous approaches to AI. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The students get to know a completely new field (art ←→ computer science). They have tested how inspiring interdisciplinary collaboration can be and applied their newly acquired knowledge by designing a practice-oriented project/ AI+Art prototype in mixed groups. In addition, they take away with them the social contribution that can be made with ML. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The seminar consists of presentations (lectures) covering the topics listed below. The presentations will be discussed in depth and key publications from computer science and art/theory will be read and discussed. Experts from the various fields and artists will be invited and selected works of art will be discussed. Invited experts and artists: - Dr. Tiara Roxanne, (researcher and artist, Post-Doc fellow Data&Society NYC) - Aparna Rao (researcher and artist, ETH) - PD Dr. Alexander Ilic (executive director, ETH AI Center) - Dr. Menna El-Assady (Post-Doc Fellow ETH AI Center) - Prof. Hoda Heidari (CMU) At the end of the seminar, interdisciplinary teams will develop concepts for joint practice-related projects. - History Art+Science - Machine Learning for Artists - Bias & Digital Colonialism - Trustworthy AI - Indigenous AI | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Structure, program and references can be found here: https://wiki.zhdk.ch/fs/doku.php?id=what_kind_of_ai_do_we_want | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 351-0578-00L | Introduction to Economic Policy Not for students belonging to D-MTEC! | W | 2 credits | 1V | H. Mikosch | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | First approach to the theory of economic policy. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | First approach to the theory of economic policy. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Wirtschaftspolitik ist die Gesamtheit aller Massnahmen von staatlichen Institutionen mit denen das Wirtschaftsgeschehen geregelt und gestaltet wird. Die Vorlesung bietet einen ersten Zugang zur Theorie der Wirtschaftspolitik. Gliederung der Vorlesung: 1.) Wohlfahrtsökonomische Grundlagen: Wohlfahrtsfunktion, Pareto-Optimalität, Wirtschaftspolitik als Mittel-Zweck-Analyse u.a. 2.) Wirtschaftsordnungen: Geplante und ungeplante Ordnung 3.) Wettbewerb und Effizienz: Hauptsätze der Wohlfahrtsökonomik, Effizienz von Wettbewerbsmärkten 4.) Wettbewerbspolitik: Sicherstellung einer wettbewerblichen Ordnung Gründe für Marktversagen: 5.) Externe Effekte 6.) Öffentliche Güter 7.) Natürliche Monopole 8.) Informationsasymmetrien 9.) Anpassungskosten 10.) Irrationalität 11.) Wirtschaftspolitik und Politische Ökonomie Die Vorlesung beinhaltet Anwendungsbeispiele und Exkurse, um eine Verbindung zwischen Theorie und Praxis der Wirtschaftspolitik herzustellen. Z. B. Verteilungseffekte von wirtschaftspolitischen Massnahmen, Kartellpolitik am Ölmarkt, Internalisierung externer Effekte durch Emissionshandel, moralisches Risiko am Finanzmarkt, Nudging, zeitinkonsistente Präferenzen im Bereich der Gesundheitspolitik | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Ja (in Form von Vorlesungsslides). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 351-1138-00L | PRISMA 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: https://mtecethz.qualtrics.com/jfe/form/SV_cx4ZghhYhQAY3nT Participation is subject to successful selection through this sign-up process. Not for students belonging to D-MTEC! | W | 4 credits | 4V | A. Cabello Llamas | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | In 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The 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. (https://www.prisma.ethz.ch/). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Bachelor students get preferential access to this course. All interested students must apply through a separate application process at: https://mtecethz.qualtrics.com/jfe/form/SV_cx4ZghhYhQAY3nT Participation is subject to successful selection through this sign-up process. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 363-1038-00L | Sustainability Start-Up Seminar Number of participants limited to 30. | W | 3 credits | 2G | A. H. Sägesser | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Participants are lead through a venturing process inspired by Lean and Design Thinking and social innovation methodologies. The course contains problem identification, idea generation and evaluation, team formation, and the development of one entrepreneurial idea per team. Starting points for entrepreneurial ideas are the climate crisis and biodiversity loss. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | 1. Students have experienced and know how to take the first steps towards co-creating a venture and potentially company 2. Students reflect deeply on sustainability issues (with a focus on climate change & biodiversity) and can formulate a problem statement 3. Students believe in their ability to bring change to the world with their own ideas 4. Students are able to apply entrepreneurial practices such as e.g. the lean startup approach 5. Students have built a first network and know how to proceed and who to approach in case they would like to take their ventures further. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | This course is aimed at people with a keen interest to address sustainability issues (with a focus on climate crisis and biodiversity loss), with a curious mindset, and potentially first ideas for entrepreneurial action! The seminar consists of a mix of lectures, workshops, individual working sessions, teamwork, and student presentations/pitches. This class is taught by a reflective practitioner of entrepreneurial action for societal transformation. Real-world climate entrepreneurs and experts from the Swiss start-up and sustainability community will be invited to support individual sessions. All course content is based on latest international entrepreneurship practices and contains continuous processes of self- and world making. The seminar starts with an introduction to sustainability (with a special focus on climate change & biodiversity) and entrepreneurship. Students are asked to self-select into an area of their interest in which they will develop entrepreneurial ideas throughout the course. The first part of the course then focuses on deeply understanding sustainability problems within the area of interest. Through workshops and self-study, students will identify key design challenges, generate ideas, as well as provide systematic and constructive feedback to their peers. In the second part of the course, students will form teams around their generated ideas. In these teams they will develop a business model and, following the lean start-up process, conduct real-life testing, as well as pivoting of these business models. In the final part of the course, students present their insights gained from the lean start-up process, as well as pitch their entrepreneurial ideas and business models to an expert jury. The course will conclude with a session that provides students with a network and resources to further pursue their entrepreneurial journey. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | All material used will be made available to the participants. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | No pre-reading required. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Prerequisite: Interest in sustainability & entrepreneurship and readiness to open up, share and reflect deeply. Notes: 1. It is not required that participants already have an idea for entrepreneurial action at the beginning of the course. 2. Focus is on entrepreneurial action which can take many forms. Eg. startup, SME, campaign, intrapreneurial action, non-profit, ... 2. No legal entities (e.g. GmbH, Association, AG) need to be founded for this course. Target participants: PhD students, Msc students and MAS students from all departments. The number of participants is limited to max.24. Waiting list: After subscribing you will be added to the waiting list. The lecturer will contact you a few weeks before the start of the seminar to confirm your interest and to ensure a good mixture of study backgrounds, only then you're accepted to the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 363-1122-00L | From Entrepreneurial Thinking to Market Relevance - How Startups Scale Number of participants limited to 40. All interested students are invited to apply for this course by sending a short motivation letter to Anil Sethi: anilsethi@ethz.ch. Additionally please enroll via mystudies. | W | 3 credits | 2G | A. Sethi | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This elective is relevant if you’re planning to join or start a startup in the near future. It will help you recognise how value is created and captured. This includes go-to market, marketing & visibility across verticals & across the supply chain for sustained value capture & business model sustainability. In short, it’s the journey of how to create a billion dollar startup. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | At the conclusion of the course, the students are able to: 1. The difference between technology and market relevance 2. Recognise challenges that startups face when they move from technology to commercialisation 3. Addressing the failures of startups in scaling, and how early decisions limit scaling and value capture 4. How recognising market need can help startups to create value and strengthen valuation with investors | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Technology startups face challenges in identifying market relevance in the course of commercialisation. Additionally, once they have matched their offering with market needs, they face additional challenges when scaling up since they get locked in early. Due to this, technology startups plateau off as niche. Platform startups, on the other hand, struggle with retaining relevance. Due to these aspects, failure rates are very high. This course addresses students who want to become entrepreneurs or want to join startups. They may come from business or science & technology backgrounds. The course will enable the students to identify the relevance of seeing the technology from an early stage startup from the market relevance perspective and use this to help the company drive revenue and relevance. The students will also get an overview of how platform startups can retain relevance. The students will have exposure to investors and entrepreneurs (with a focus on ETH spin-offs) through the course, to gain insight to commercialisation and subsequent scaling up of the technology. Topics cover idea validation, technology and market size validation and assessment of market relevance, assessing time-to-market, customer focus, perceived value for customers, and finally, opportunities of maximising relevance of technology idea into sustained market traction. There is a particular emphasis on market validation on each step of the journey, to ensure relevance. The course comprises lectures and talks from invited investors / entrepreneurs regarding the aforementioned elements. Additionally, students will form teams and will support an existing startup over the course of the semester. This will allow them to gain first-hand experience and insights into the dynamics of a early stage company. By having such real-life exposure, the course content will be transferred from theory to practice. Grading of the course will be based on in-class presentations as well as the student teams' performance and support of their selected startups. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | “From Science to Startup” by A. Sethi | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-0210-00L | Biomechatronics Primarily designed for Health Sciences and Technology students. The Biomechatronics lecture is not appropriate for students who already attended the lecture "Physical Human-Robot Interaction"(376-1504-00L), because it covers similar topics. Matlab skills are beneficial-> online Tutorial http://www.imrtweb.ethz.ch/matlab/ | W | 4 credits | 3G | R. Riener, N. Gerig, O. Lambercy | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Development of mechatronic systems (i.e. mechanics, electronics, computer science and system integration) with inspiration from biology and application in the living (human) organism. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The objective of this course is to give an introduction to the fundamentals of biomechatronics, through lectures on the underlying theoretical/mechatronics aspects and application fields. In the exercises, these concepts will be intensified and trained on the basis of specific examples. The course will guide students through the design and evaluation process of such systems, and highlight a number of applications. By the end of this course, you should understand the critical elements of biomechatronics and their interaction with biological systems, both in terms of engineering metrics and human factors. You will be able to apply the learned methods and principles to the design, improvement and evaluation of safe and efficient biomechatronics systems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course will cover the interdisciplinary elements of biomechatronics, ranging from human factors to sensor and actuator technologies, real-time signal processing, system kinematics and dynamics, modeling and simulation, controls and graphical rendering as well as safety/ethical aspects, and provide an overview of the diverse applications of biomechatronics technology. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Slides will be distributed through moodle before the lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Brooker, G. (2012). Introduction to Biomechatronics. SciTech Publishing. Riener, R., Harders, M. (2012) Virtual Reality in Medicine. Springer, London. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | None | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 401-0302-10L | Complex Analysis | W | 4 credits | 3V + 1U | A. Iozzi | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Basics of complex analysis in theory and applications, in particular the global properties of analytic functions. Introduction to the integral transforms and description of some applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Erwerb von einigen grundlegenden Werkzeuge der komplexen Analysis. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Examples of analytic functions, Cauchy‘s theorem, Taylor and Laurent series, singularities of analytic functions, residues. Fourier series and Fourier integral, Laplace transform. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | J. Brown, R. Churchill: "Complex Analysis and Applications", McGraw-Hill 1995 T. Needham. Visual complex analysis. Clarendon Press, Oxford. 2004. M. Ablowitz, A. Fokas: "Complex variables: introduction and applications", Cambridge Text in Applied Mathematics, Cambridge University Press 1997 E. Kreyszig: "Advanced Engineering Analysis", Wiley 1999 J. Marsden, M. Hoffman: "Basic complex analysis", W. H. Freeman 1999 P. P. G. Dyke: "An Introduction to Laplace Transforms and Fourier Series", Springer 2004 A. Oppenheim, A. Willsky: "Signals & Systems", Prentice Hall 1997 M. Spiegel: "Laplace Transforms", Schaum's Outlines, Mc Graw Hill | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Prerequisites: Analysis I and II | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 402-0810-00L | Computational Quantum Physics Special Students UZH must book the module PHY522 directly at UZH. | W | 8 credits | 2V + 2U | K. Pakrouski | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course provides an introduction to simulation methods for quantum systems. Starting from the one-body problem, a special emphasis is on quantum many-body problems, where we cover both approximate methods (Hartree-Fock, density functional theory) and exact methods (exact diagonalization, matrix product states, and quantum Monte Carlo methods). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Through lectures and practical programming exercises, after this course: Students are able to describe the difficulties of quantum mechanical simulations. Students are able to explain the strengths and weaknesses of the methods covered. Students are able to select an appropriate method for a given problem. Students are able to implement basic versions of all algorithms discussed. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | A script for this lecture will be provided. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | A list of additional references will be provided in the script. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | A basic knowledge of quantum mechanics, numerical tools (numerical differentiation and integration, linear solvers, eigensolvers, root solvers, optimization), and a programming language (for the teaching assignments, you are free to choose your preferred one). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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