Search result: Catalogue data in Spring Semester 2020

Integrated Building Systems Master Information
Main Courses
Specialised Courses
NumberTitleTypeECTSHoursLecturers
363-1060-00LStrategies for Sustainable Business Restricted registration - show details
Limited number of participants.

Registration will only be effective once confirmed by email from the organizers.
W2 credits2SJ. Meuer
AbstractIn this course, students will learn to critically analyze strategies for sustainable business through exploring case studies on three main questions:
1. What is sustainability in business?
2. How do I design a sustainability strategy?
3. How do I implement a sustainability strategy?
ObjectiveAfter the course, you should be able to:

1. Understand and explain sustainability challenges companies are facing;
2. Critique sustainability and related strategies;
3. Evaluate decisions taken by managers;
4. Suggest alternative approaches;
5. Develop action plans;
6. Reflect on strategies for sustainability in their own organizations.

You will also learn to apply a range of strategy concepts to sustainability challenges, including leadership, stakeholder management, diversification, and organizational change.
ContentAlthough many companies nowadays report on their sustainability actions, only few successfully integrate sustainability into their business operations. In this seminar, we will cover three main questions that will help you to critically analyze and develop strategies for sustainable business:
1. What is sustainability in business?
2. How do I design a sustainability strategy?
3. How do I implement a sustainability strategy?

We teach the course with the case method developed at Harvard Business School. The case studies will allow us to explore from multiple perspectives the many tensions involved in developing strategies for sustainable business. We will distribute case study materials before the sessions, as well as guidelines on how best to efficiently and effectively prepare for case study discussions. You will need to read the materials and to submit short assignments before each class.

The sessions are interactive and allow you to step into the role of decision-makers as they face key challenges in integrating sustainability. For example, we will look at the challenges of Fairphone in combining both social and economic goals. Why and how would Patagonia want to encourage customers to buy less rather than more clothing? We also step into the shoes of RWE's CEO Peter Terium as he grapples with ensuring a profitable and sustainable future for the German utility. And using a change management simulation, you will experience why certain approaches to implementing a sustainability initiative in an organization are more successful than others. Our case discussions will help you to apply strategy concepts to real-world sustainability problems and will also serve as a basis for thinking about sustainability in your own company.
LiteratureWe will provide case study material and guidelines for analyzing cases to participants by email several weeks before the seminar.
Prerequisites / NoticeAfter signing up you will first be placed on the waiting list. We will contact all students on the waiting list by 1 March 2019 to confirm their participation in the seminar. If you have any questions, please don't hesitate to contact Johannes Meuer (jmeuer@ethz.ch).
252-0220-00LIntroduction to Machine Learning Information Restricted registration - show details
Limited number of participants. Preference is given to students in programmes in which the course is being offered. All other students will be waitlisted. Please do not contact Prof. Krause for any questions in this regard. If necessary, please contact studiensekretariat@inf.ethz.ch
W8 credits4V + 2U + 1AA. Krause
AbstractThe course introduces the foundations of learning and making predictions based on data.
ObjectiveThe course will introduce the foundations of learning and making predictions from data. We will study basic concepts such as trading goodness of fit and model complexitiy. We will discuss important machine learning algorithms used in practice, and provide hands-on experience in a course project.
Content- Linear regression (overfitting, cross-validation/bootstrap, model selection, regularization, [stochastic] gradient descent)
- Linear classification: Logistic regression (feature selection, sparsity, multi-class)
- Kernels and the kernel trick (Properties of kernels; applications to linear and logistic regression); k-nearest neighbor
- Neural networks (backpropagation, regularization, convolutional neural networks)
- Unsupervised learning (k-means, PCA, neural network autoencoders)
- The statistical perspective (regularization as prior; loss as likelihood; learning as MAP inference)
- Statistical decision theory (decision making based on statistical models and utility functions)
- Discriminative vs. generative modeling (benefits and challenges in modeling joint vy. conditional distributions)
- Bayes' classifiers (Naive Bayes, Gaussian Bayes; MLE)
- Bayesian approaches to unsupervised learning (Gaussian mixtures, EM)
LiteratureTextbook: Kevin Murphy, Machine Learning: A Probabilistic Perspective, MIT Press
Prerequisites / NoticeDesigned to provide a basis for following courses:
- Advanced Machine Learning
- Deep Learning
- Probabilistic Artificial Intelligence
- Seminar "Advanced Topics in Machine Learning"
151-0306-00LVisualization, Simulation and Interaction - Virtual Reality I Information W4 credits4GA. Kunz
AbstractTechnology 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).
ObjectiveThe 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.
ContentIntroduction 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 notesA complete version of the handout is also available in English.
Prerequisites / NoticeVoraussetzungen:
keine
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
063-0610-00LThe Digital in ArchitectureW2 credits1V + 2UF. Gramazio, M. Kohler
AbstractIn lecture series coupled with a series of taught exercises, the course establishes a conceptual framework of digital fabrication in architecture. The exercises focus on simple yet powerful methods of digital, computational and algorithmic design. Two seminar sessions open a debate on the digital as a driving force of a future building and architecture culture.
ObjectiveStudents develop an understanding of the digital and its concepts in architecture and of current developments in the field of digital fabrication. Students learn about design strategies based on digital methods and are able to relate these to their own design approach and its wider context at the Department of Architecture. In the exercises, they learn to use Rhino 5 / Grasshopper and write their first code in Python. The aim is to equip students with the necessary intellectual and technical skills that allow them to independently deepen their engagement with the digital in the chosen design studios.
ContentThe course consists of a lecture series coupled with a series of taught exercises. Departing from the work of Gramazio Kohler Research, the lectures establish a conceptual framework of the digital in architecture with special regard to digital fabrication. The exercises focus on simple yet powerful methods of digital, computational and algorithmic design. Two seminar sessions are dedicated to an open debate on the digital as a driving force of a future building and architecture culture.
Prerequisites / NoticePool Introduction Event:
Informationon event on all the courses offered by the ITA (Institute of Technology in Architecture):
Monday, 17th February 2020, 11-12 h, HIB Open Space!
376-1178-00LHuman Factors IIW3 credits2VM. Menozzi Jäckli, R. Huang, M. Siegrist
AbstractStrategies, abilities and needs of human at work as well as properties of products and systems are factors controlling quality and performance in everyday interactions. In Human Factors II (HF II), cognitive aspects are in focus therefore complementing the more physical oriented approach in HF I. A basic scientific approach is adopted and relevant links to practice are illustrated.
ObjectiveThe goal of the lecture is to empower students in designing products and systems enabling an efficient and qualitatively high standing interaction between human and the environment, considering costs, benefits, health, well-being, and safety as well. The goal is achieved in addressing a broad variety of topics and embedding the discussion in macroscopic factors such as the behavior of consumers and objectives of economy.
ContentCognitive factors in perception, information processing and action. Experimental techniques in assessing human performance and well-being, human factors and ergonomics in development of products and complex systems, innovation, decision taking, consumer behavior.
LiteratureSalvendy G. (ed), Handbook of Human Factors, Wiley & Sons, 2012
101-0523-00LIndustrialized Construction Restricted registration - show details W4 credits3GD. Hall
AbstractThis course offers an introduction and overview to Industrialized Construction, a rapidly-emerging concept in the construction industry. The course will present the driving forces, concepts, technologies, and managerial aspects of Industrialized Construction, with an emphasis on current industry applications and future entrepreneurial opportunities in the field.
ObjectiveBy the end of the course, students should be able to:
1. Describe the characteristics of the nine integrated areas of industrialized construction: planning and control of processes; developed technical systems; prefabrication; long-term relations; logistics; use of ICT; re-use of experience and measurements; customer and market focus; continuous improvement.
2. Assess case studies on successful or failed industry implementations of industrialized construction in Europe, Japan and North America.
3. Propose a framework for a new industrialized construction company for a segment of the industrialized construction market (e.g. housing, commercial, schools) including the company’s business model, technical platform, and supply chain strategy.
4. Identify future trends in industrialized construction including the use of design automation, digital fabrication, and Industry 4.0.
ContentThe application of Industrialized Construction - also referred to as prefabrication, offsite building, or modular construction – is rapidly increasing in the industry. Although the promise of industrialized construction has long gone unrealized, several market indicators show that this method of construction is quickly growing around the world. Industrialized Construction offers potential for increased productivity, efficiency, innovation, and safety on the construction site. The course will present the driving forces, concepts, technologies, and managerial aspects of Industrialized Construction. The course unpacks project-orientated vs. product-oriented approaches while showcasing process and technology platforms used by companies in Europe, the UK, Japan, and North America. The course highlights future business models and entrepreneurial opportunities for new industrialized construction ventures.

The course is organized around a group project carried out in teams of 3-4. The project begins in week 6 of the course, and collaborative group work will occur during the Wednesday sessions. Teams will be required to propose a framework for a new industrialized construction venture including the company’s product offering, business model, technical platform, and supply chain strategy.

The planned course activities include a 1/2 day factory visit (UPDATE confirmed date is Friday, March 20), a tour of the NCCR dfab laboratory, and five reflection assignments. Students who are unable to attend the visits can make up participation through independent research and the writing of a short paper.
LiteratureA full list of required readings will be made available to the students via Moodle.
063-0640-00LAdvanced Computational Design
Limited number of participants.
W3 credits3GB. Dillenburger
AbstractIn this course we will discuss how strategies of Artificial Intelligence such as Machine Learning or Evolutionary Strategies can be used in the design process. Principal concepts of computational geometry for architecture will be connected with methods to automatically generate, evaluate and search for design solutions.
ObjectiveStudents will understand programming basics, and will learn how to control geometry using code. They will learn to translate a design concept into an algorithmic approach - or vice versa - and will obtain an awareness of potentials and limitations of AI in the design phase. Students will deepen their knowledge in customizing existing CAD software such as Rhino using scripting.
ContentIn this course we will discuss how concepts of Artificial Intelligence can be used in the design process. In tutorials and exercises, we will explore the use strategies such as Machine Learning or Evolutionary Strategies to turn the computer from a drawing instrument into an active partner in design, extending both the imagination and the intuition of the designer.
Prerequisites / NoticeSuccessful completion of the course "Structural Design VI" (063-0606-00L), "Design III" (052-0541/43/45) or "Das Digitale in der Architektur" (063-0610-00L) are recommended
103-0448-01LTransformation of Urban Landscapes
Only for masters students, otherwise a special permit of the lecturer is necessary.
W3 credits2GJ. Van Wezemael, A. Gonzalez Martinez
AbstractThe lecture course addresses the transformation of urban landscapes towards sustainable inward development. The course reconnects two largely separated complexity approaches in «spatial planning» and «urban sciences» as a basic framework to look at a number of spatial systems considering economic, political, and cultural factors. Focus lies on participation and interaction of students in groups.
Objective- Understand cities as complex adaptive systems
- Understand planning in a complex context and planning competitions as decision-making
- Seeing cities through big data and understand (Urban) Governance as self-organization
- Learn Design-Thinking methods for solving problems of inward development
- Practice presentation skills
- Practice argumentation and reflection skills by writing critiques
- Practice writing skills in a small project
- Practice teamwork
ContentStarting point and red thread of the lecture course is the transformation of urban landscapes as we can see for example across the Swiss Mittelland - but in fact also globally. The lecture course presents a theoretical foundation to see cities as complex systems. On this basis it addresses practical questions as well as the complex interplay of economic, political or spatial systems.

While cities and their planning were always complex the new era of globalization exposed and brought to the fore this complexity. It created a situation that the complexity of cities can no longer be ignored. The reason behind this is the networking of hitherto rather isolated places and systems across scales on the basis of Information and Communication Technologies. «Parts» of the world still look pretty much the same but we have networked them and made them strongly interdependent. This networking fuels processes of self-organization. In this view regions emerge from a multitude of relational networks of varying geographical reach and they display intrinsic timescales at which problems develop. In such a context, an increasing number of planning problems remain unaffected by either «command-and-control» approaches or instruments of spatial development that are one-sidedly infrastructure- or land-use orientated. In fact, they urge for novel, more open and more bottom-up assembling modes of governance and a «smart» focus on how space is actually used. Thus, in order to be effective, spatial planning and governance must be reconceptualised based on a complexity understanding of cities and regions, considering self-organizing and participatory approaches and the increasingly available wealth of data.
LiteratureA reader with original papers will be provided via the ILIAS system.
Prerequisites / NoticeOnly for masters students, otherwise a special permit of the lecturer is necessary.
252-0834-00LInformation Systems for Engineers Information
Wird ab HS20 nur in Herbstsemester angeboten.
W4 credits2V + 1UG. Fourny
AbstractThis course provides the basics of relational databases from the perspective of the user.

We will discover why tables are so incredibly powerful to express relations, learn the SQL query language, and how to make the most of it. The course also covers support for data cubes (analytics).
ObjectiveThis lesson is complementary with Big Data for Engineers as they cover different time periods of database history and practices -- you can even take both lectures at the same time.

After visiting this course, you will be capable to:

1. Explain, in the big picture, how a relational database works and what it can do in your own words.

2. Explain the relational data model (tables, rows, attributes, primary keys, foreign keys), formally and informally, including the relational algebra operators (select, project, rename, all kinds of joins, division, cartesian product, union, intersection, etc).

3. Perform non-trivial reading SQL queries on existing relational databases, as well as insert new data, update and delete existing data.

4. Design new schemas to store data in accordance to the real world's constraints, such as relationship cardinality

5. Explain what bad design is and why it matters.

6. Adapt and improve an existing schema to make it more robust against anomalies, thanks to a very good theoretical knowledge of what is called "normal forms".

7. Understand how indices work (hash indices, B-trees), how they are implemented, and how to use them to make queries faster.

8. Access an existing relational database from a host language such as Java, using bridges such as JDBC.

9. Explain what data independence is all about and didn't age a bit since the 1970s.

10. Explain, in the big picture, how a relational database is physically implemented.

11. Know and deal with the natural syntax for relational data, CSV.

12. Explain the data cube model including slicing and dicing.

13. Store data cubes in a relational database.

14. Map cube queries to SQL.

15. Slice and dice cubes in a UI.

And of course, you will think that tables are the most wonderful object in the world.
ContentUsing a relational database
=================
1. Introduction
2. The relational model
3. Data definition with SQL
4. The relational algebra
5. Queries with SQL

Taking a relational database to the next level
=================
6. Database design theory
7. Databases and host languages
8. Databases and host languages
9. Indices and optimization
10. Database architecture and storage

Analytics on top of a relational database
=================
12. Data cubes

Outlook
=================
13. Outlook
Literature- Lecture material (slides).

- Book: "Database Systems: The Complete Book", H. Garcia-Molina, J.D. Ullman, J. Widom
(It is not required to buy the book, as the library has it)
Prerequisites / NoticeFor non-CS/DS students only, BSc and MSc
Elementary knowledge of set theory and logics
Knowledge as well as basic experience with a programming language such as Pascal, C, C++, Java, Haskell, Python
051-0912-20LSeminar Week Spring Semester 2020 Information Restricted registration - show details
Im FS20 darf nur eine Seminarwoche belegt werden 051-0912-20L oder 051-0914-20L.
W2 credits3ALecturers
AbstractThe seminar week is obligatory for students of all semesters. There are many and varied study contents - the programs are listed at the beginning of each semester.
ObjectiveThe students will be enabled to discuss narrowly formulated factual questions in small groups and in direct contact with the professors.
ContentThe seminar week is obligatory for students of all semesters. There are many and varied study contents - the programs are listed at the beginning of each semester.
052-0568-00LRoom Acoustics (FS) Information W2 credits2GK. Eggenschwiler
AbstractInfluence of form and material on speech and music within spaces. Special requirements of acoustically sensitive spaces such as school rooms, music rooms, theaters, concert halls, opera buildings and churches (historical and modern buildings). Scientific ways of calculating and assessing acoustics. Basic introduction to sound systems for speech.
ObjectiveThe students learn to recognise the importance of acoustic factors and to design spaces with appropriate acoustical properties.
ContentWe will begin by focusing on the acoustic dimension of space without excluding the other non-auditory senses. Following this, the influence of form and material on hearing and the characteristics of the spoken word and music within spaces will be explored by means of examples and with the aid of the special instruments of acoustic science. We will then discuss the special requirements of acoustically sensitive spaces such as school rooms, music rooms, theaters, concert halls, opera buildings, and churches. This study takes the form of both theory, and real examples of historical and modern buildings. Scientific ways of calculating and assessing acoustics is presented and a basic introduction to the sound system
design for speech is made.
Lecture notesScript in German
252-3900-00LBig Data for Engineers Information
This course is not intended for Computer Science and Data Science MSc students!
W6 credits2V + 2U + 1AG. Fourny
AbstractThis course is part of the series of database lectures offered to all ETH departments, together with Information Systems for Engineers. It introduces the most recent advances in the database field: how do we scale storage and querying to Petabytes of data, with trillions of records? How do we deal with heterogeneous data sets? How do we deal with alternate data shapes like trees and graphs?
ObjectiveThis lesson is complementary with Information Systems for Engineers as they cover different time periods of database history and practices -- you can even take both lectures at the same time.

The key challenge of the information society is to turn data into information, information into knowledge, knowledge into value. This has become increasingly complex. Data comes in larger volumes, diverse shapes, from different sources. Data is more heterogeneous and less structured than forty years ago. Nevertheless, it still needs to be processed fast, with support for complex operations.

This combination of requirements, together with the technologies that have emerged in order to address them, is typically referred to as "Big Data." This revolution has led to a completely new way to do business, e.g., develop new products and business models, but also to do science -- which is sometimes referred to as data-driven science or the "fourth paradigm".

Unfortunately, the quantity of data produced and available -- now in the Zettabyte range (that's 21 zeros) per year -- keeps growing faster than our ability to process it. Hence, new architectures and approaches for processing it were and are still needed. Harnessing them must involve a deep understanding of data not only in the large, but also in the small.

The field of databases evolves at a fast pace. In order to be prepared, to the extent possible, to the (r)evolutions that will take place in the next few decades, the emphasis of the lecture will be on the paradigms and core design ideas, while today's technologies will serve as supporting illustrations thereof.

After visiting this lecture, you should have gained an overview and understanding of the Big Data landscape, which is the basis on which one can make informed decisions, i.e., pick and orchestrate the relevant technologies together for addressing each business use case efficiently and consistently.
ContentThis course gives an overview of database technologies and of the most important database design principles that lay the foundations of the Big Data universe.

It targets specifically students with a scientific or Engineering, but not Computer Science, background.

We take the monolithic, one-machine relational stack from the 1970s, smash it down and rebuild it on top of large clusters: starting with distributed storage, and all the way up to syntax, models, validation, processing, indexing, and querying. A broad range of aspects is covered with a focus on how they fit all together in the big picture of the Big Data ecosystem.

No data is harmed during this course, however, please be psychologically prepared that our data may not always be in normal form.

- physical storage: distributed file systems (HDFS), object storage(S3), key-value stores

- logical storage: document stores (MongoDB), column stores (HBase)

- data formats and syntaxes (XML, JSON, RDF, CSV, YAML, protocol buffers, Avro)

- data shapes and models (tables, trees)

- type systems and schemas: atomic types, structured types (arrays, maps), set-based type systems (?, *, +)

- an overview of functional, declarative programming languages across data shapes (SQL, JSONiq)

- the most important query paradigms (selection, projection, joining, grouping, ordering, windowing)

- paradigms for parallel processing, two-stage (MapReduce) and DAG-based (Spark)

- resource management (YARN)

- what a data center is made of and why it matters (racks, nodes, ...)

- underlying architectures (internal machinery of HDFS, HBase, Spark)

- optimization techniques (functional and declarative paradigms, query plans, rewrites, indexing)

- applications.

Large scale analytics and machine learning are outside of the scope of this course.
LiteraturePapers from scientific conferences and journals. References will be given as part of the course material during the semester.
Prerequisites / NoticeThis course is not intended for Computer Science and Data Science students. Computer Science and Data Science students interested in Big Data MUST attend the Master's level Big Data lecture, offered in Fall.

Requirements: programming knowledge (Java, C++, Python, PHP, ...) as well as basic knowledge on databases (SQL). If you have already built your own website with a backend SQL database, this is perfect.

Attendance is especially recommended to those who attended Information Systems for Engineers last Fall, which introduced the "good old databases of the 1970s" (SQL, tables and cubes). However, this is not a strict requirement, and it is also possible to take the lectures in reverse order.
Project Courses
NumberTitleTypeECTSHoursLecturers
363-1056-00LInnovation Leadership Restricted registration - show details
Up to four slots are available for students in architecture or civil engineering (Master level) or for D-MTEC MAS/MSc students with architecture or civil engineering background.

If you are NOT a student in Integrated Building Systems, you need to apply with motivation letter (max. 1 page), CV and a transcript of records no later than 31 January 2020. Please send your application to Zorica Zagorac (zzagorac@ethz.ch).
W6 credits3SD. Laureiro Martinez, C. P. Siegenthaler, Z. Zagorac-Uremovic
AbstractThis course provides participants with the challenging opportunity of working on an innovation project of a leading company in the Swiss building industry.
ObjectiveStudents work in teams, on a concrete innovation project that is currently affecting the strategic agenda of the top management team of a leading company in the Swiss building industry. Students conduct interviews with internal and external experts, as well as company clients. By doing so, students gain first-hand experience on the competitive dynamics of the construction industry and as a group, work on proposing a solution to the company’s innovation project.
The course emphasizes the use and development of self-directedness and critical thinking abilities. In parallel to working on the innovation project, students work on their own learning goals. Students first define their very own learning goals and then are assessed and graded on whether they have progressed towards achieving such learning goals.
Students learn to:
• Reflect and explore personal learning goals and discover new aspects of their leadership abilities
• Learn to work in an unknown direction with no certain outcome
• Explore how a project with internal and external stakeholders works when people have conflicting interests, that might also vary according to the different time perspectives that are taken into account
• Use design thinking and solution-oriented coaching techniques
ContentThe course uses participant-centered tools that encourage students' reflection and boost their personal development, their creative output and help them to discover their own approach to leadership. The course offers multiple opportunities to learn about technical aspects in a real corporate environment. The setup is a social environment in which trial-and-error learning is encouraged. The course focuses on three areas of development: Project management, innovation and leadership.
Project Management: Students learn to self-manage their project while being supported by numerous project management techniques, coaching exercises, and individual feedback through learning diaries. An additional focus is given to design thinking methods and prototyping tools.

Innovation: Students learn about specific topics related to current innovation in the building sector in Switzerland. They learn to understand technology changes with an ecosystems view and think about the impact of new technologies in the building industry company (e.g. the commercialization of Building Information Modelling, BIM).
Leadership: Students conduct a project with diverse stakeholders requiring them to take managerial, technical, and personal responsibility for the company case. This high-pressure environment leads to an intense self-reflection journey, team experience and fosters proactive behaviors towards the client.
- On the individual level, students have to identify and achieve their very own authentic learning goals. Coaching tools involve a learning diary, which questions evolve during the semester, and a self-assessment of individual abilities and traits, which complements the reflective journey.
- On the team level, students are teamed up to deliver a solution proposal to the company’s project. The teams are diverse and the students’ work focuses on cooperativeness and how to be effective team members. Teaching tools involve peer-to-peer feedback, coaching and open space workshops.
- On the company level, students learn how to deal with different stakeholders and how to create impactful and sustainable solutions for their client.
Prerequisites / NoticeUp to four slots are available for students in architecture or civil engineering (Master level) or for D-MTEC MAS/MSc students with architecture or civil engineering background.

If you are NOT a student in Integrated Building Systems, you need to apply with motivation letter (max. 1 page), CV and a transcript of records no later than 31 January 2020. Please send your application to Zorica Zagorac (zzagorac@ethz.ch). Incomplete or late applications will not be considered.
Semester Project
NumberTitleTypeECTSHoursLecturers
066-0431-00LSemester Project MBS Restricted registration - show details
Semester projects are supervised and reviewed by one or several professors and possibly by other persons at the same time. At least one professor has to be a member of a department involved in the study programme (article 2). This regulation is also valid for semester projects taking place outside ETH Zurich.

You can choose the mentoring professor of your semester project MBS:
Jan CARMELIET
Stefano BRUSONI
Guillaume HABERT
Daniel HALL
John LYGEROS
Marco MAZZOTTI
Arno SCHLÜTER
Roy SMITH
O6 credits13AProfessors
AbstractThe semester project focuses in solving specific research questions in the field of integrated building systems.
ObjectiveThe semester project is designed to train students in solving specific research questions in the field of integrated building systems. The goal is to apply acquired knowledge which is gained throughout the first year of the master's program. The semester project is advised by a professor who is affiliated with one of the partner departments of the Master program "Integrated building systems".
ContentThe semester project is designed to train students in solving specific research questions in the field of integrated building systems. The goal is to apply acquired knowledge which is gained throughout the first year of the master's program. The semester project is advised by a professor who is affiliated with one of the partner departments of the Master program "Integrated building systems".
GESS Science in Perspective
NumberTitleTypeECTSHoursLecturers
» see Science in Perspective: Type A: Enhancement of Reflection Capability
» Recommended Science in Perspective (Type B) for D-ARCH.
» see Science in Perspective: Language Courses ETH/UZH
851-0107-00LScience and the Public: A Problem of Mediation that the Media Have to Solve? Restricted registration - show details W3 credits2SU. J. Wenzel
AbstractWhat can, what should, what do "laymen" want to know and understand from scientific findings? How and what is "conveyed" in reporting on science? Does science journalism have to follow scientific criteria? How do the natural sciences differ from the humanities and social sciences in terms of "comprehensibility" and public visibility?
ObjectiveGaining insights into the relationship between the sciences, the public and the media, into their historical development and current problems - with particular reference to the "Wissenschaftsfeuilleton".
ContentThe feuilleton of the «Frankfurter Allgemeine Zeitung» of 27 June 2000 has gone down in the annals of recent media history. The last sequences of the fully mapped human genetic code were printed on six large-format pages: the letters A, G, C and T in various combinations and sequences - a «readable » but incomprehensible jumble of letters. What at the time was astounding journalistic coup and met with enthusiasm as well as head shaking can (also) be read as an allegory of the tense relationship between science and the public. What can, what should, what do «laymen» want to know and understand from scientific findings? What role do the media play, does science journalism play in this? How and what is «conveyed» in reporting on scientific findings? And does science journalism have to follow scientific criteria in such reporting? How do the natural sciences, medicine and technology differ from the humanities and social sciences in terms of «comprehensibility» and public awareness? Are we really dealing with two diverging «science cultures» - and two different ways of presenting them in the media?
These questions will be explored on some excursions into recent and also older media, scientific and cultural history.
851-0006-00LWater in the Early Modern Period: A Material and Environmental History Restricted registration - show details W3 credits2ST. Asmussen
AbstractThe seminar deals with questions of how water was perceived, used and appropriated in medieval and early modern societies. We examine water as a livelihood (drinking water, irrigation resource), energy source, transport medium, infrastructure and threat between 1400 and 1800.
ObjectiveThe students acquire historical knowledge of how pre-modern societies appropriated the natural substance water and how they themselves were formed and changed by the interactions with the liquid element. Students are expected to read original German, French and English sources.
ContentThe seminar examines the history of the substance and uses of water from the late Middle Ages to the 18th century. Using text and image sources, we will examine the physical, cultural, economic and scientific-technical implications of the relationship between man and water in plenary sessions and groups.
We deal with (al-)chemical analyses of water in the context of medical treatises and spas, the expansion and challenges of the water infrastructure ( fountains, sewage canals, irrigation canals, inland waterways), the associated changes of landscapes as well as with water as a threat (floods).
851-0109-00LPublic Images of ScienceW3 credits2VM. Bucchi
AbstractThe course will analize in a historical and sociological approach the public images of science and scientists and their major changes.
ObjectiveIn particular, we will explore the following subjects: the role of the visual element in the communication of science and its public representation; the role of ‘visible scientists’, with particular consideration of Nobel Prize winners; events and affairs that have shaped the public perception of science and the relationship between science and society.
ContentThe course will analize in a historical and sociological approach the public images of science and scientists and their major changes.
In particular, we will explore the following subjects: the role of the visual element in the communication of science and its public representation; the role of ‘visible scientists’, with particular consideration of Nobel Prize winners; events and affairs that have shaped the public perception of science and the relationship between science and society.
Various examples will be quoted and discussed, and will illustrate the Italian science and its relationship to society and to the various cultural fields (literature, visual arts, gastronomy), with particular reference to the period from the second half of the 19th century until the end of the 20th century.
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