Teaching

Sep - 24 - 2019

MOOC III – SMART CITIES

Sep - 24 - 2019

MOOC IV – RESPONSIVE CITIES

Sep - 24 - 2019

MOOC II – LIVABLE FUTURE CITIES

Sep - 24 - 2019

MOOC I – FUTURE CITIES

Feb - 18 - 2018

FS2018 | Digital Urban Simulation

A solid knowledge of computational methods is an increasingly important key competence for future architects or urban planners. In this course you will learn how to analyze and generate spatial configurations with advanced computational methods.

A solid knowledge of computational methods is an increasingly important key competence for future architects or urban planners.

In this course students analyze architectural and urban design using current computational methods. Based on these analyses the effects of planning can be simulated and understood. An important focus of this course is the interpretation of the analysis and simulation results and the application of these corresponding methods in early planning phases.

The students learn how the design and planning of cities can be evidence based by using scientific methods. The teaching unit conveys knowledge in state-of-the-art and emerging spatial analysis and simulation methods and equip students with skills in modern software systems. The course consists of lectures, associated exercises, workshops as well as of one integral project work.

In a series of theory lectures we explore how designing and planning of cities could become more evidence based by using scientific methods. Various exercises will provide training for your skills in working with state-of-the-art yet office-proven design tools (Rhino/Grasshopper and add-ons). In an integral project work, you will deepen your knowledge in spatial analysis and simulation methods such as Space Syntax using ConfigUrbanist and Decoding Spaces components packages and environmental analysis with the add-ons LadyBug and HoneyBee. In addition, you will acquire skills for using analysis methods for generative design processes. Therefore we introduce you into the parametric design software Grasshopper for Rhino 3D.

Based on the methods introduced during the semester, you will learn and understand different effects of planning and design interventions on urban life. At the end of the course you will be able to interpret analysis and simulation results, and to apply corresponding computational methods to your own planning projects.

 

Lecture, HIT F22 - Value Lab
Exercises, HIT H12

Course flyer

Teaching material is provided on moodle

.

Supervision:

Dr. Estefania Tapias

Dr. Peter Buš

 

 

Feb - 18 - 2018

FS2018 | Creative Data Mining

The students examine patterns of crowd-flows in an extraordinary urbanisation phenomena: festivals. Bottom-up urbanization you might recognize also on pictures from slums, (refugee/military/exploratory) camps etc. 
Learn how to simulate the flows of people and how to quantify the (real estate) value of stand locations. Caliente Festival, Zurich, will serve as an example.




The Creative Data Mining course aims to provide aspirants a hands-on experience on machine learning (ML) tools and techniques for data processing and data analysis. Since future technologies increasingly rely upon machine learning, urban systems and architecture shall adopt it and the aspirant should learn creative ways to apply ML to better understand urban systems. The course covers a wider range ML techniques including supervised and unsupervised learning methods for data analysis and pattern recognition that help to better understand urban system for improving urban life.

All methods taught in the course will be applied to a common project to evaluate various dynamics of the urban environment. Students will work with time-series and geo-referenced data including temperature, relative humidity, illuminance, noise, people density, and dust particulate matter. Subjective impression survey data will also be integrated into the student projects to further explore influencing factors of the urban environment on our perceptual experiences. A selected neighborhood in the city of Zurich will be used as the case study and each student will present the findings of their research question in a final project.

Additionally, there are two of non-architectural skills the participants can develop during this course. First is an introduction to programming where at a minimum they can successfully use code-snippets to customize the computational tools presented in the course. Second, how clustering methods like PCA or K-Means could be applied in an architectural context.

Where: HIT H 31.4 (Video wall)
When: Mondays 10:00 - 12:00

2 ECTS

Supervision:

Course Flyer

Sep - 18 - 2017

HS2017 | Digital Urban Simulation

A solid knowledge of computational methods is an increasingly important key competence for future architects or urban planners. In this course you will learn how to analyze and generate spatial configurations with advanced computational methods.

A solid knowledge of computational methods is an increasingly important key competence for future architects or urban planners.

In this course students analyze architectural and urban design using current computational methods. Based on these analyses the effects of planning can be simulated and understood. An important focus of this course is the interpretation of the analysis and simulation results and the application of these corresponding methods in early planning phases.

The students learn how the design and planning of cities can be evidence based by using scientific methods. The teaching unit conveys knowledge in state-of-the-art and emerging spatial analysis and simulation methods and equip students with skills in modern software systems. The course consists of lectures, associated exercises, workshops as well as of one integral project work.

In a series of theory lectures we explore how designing and planning of cities could become more evidence based by using scientific methods. Various exercises will provide training for your skills in working with state-of-the-art yet office-proven design tools (Rhino/Grasshopper and add-ons). In an integral project work, you will deepen your knowledge in spatial analysis and simulation methods such as Space Syntax using ConfigUrbanist and Decoding Spaces components packages and environmental analysis with the add-ons LadyBug and HoneyBee. In addition, you will acquire skills for using analysis methods for generative design processes. Therefore we introduce you into the parametric design software Grasshopper for Rhino 3D.

Based on the methods introduced during the semester, you will learn and understand different effects of planning and design interventions on urban life. At the end of the course you will be able to interpret analysis and simulation results, and to apply corresponding computational methods to your own planning projects.

 

Lecture, HIT F22 - Value Lab
Exercises, HIT H12

Course flyer

Teaching material is provided on moodle

.

Supervision:

Dr. Estefania Tapias

Dr. Peter Buš

 

 

Sep - 18 - 2017

HS2017 | Creative Data Mining

The students examine patterns of crowd-flows in an extraordinary urbanisation phenomena: festivals. Bottom-up urbanization you might recognize also on pictures from slums, (refugee/military/exploratory) camps etc. 
Learn how to simulate the flows of people and how to quantify the (real estate) value of stand locations. Caliente Festival, Zurich, will serve as an example.




The Creative Data Mining course aims to provide aspirants a hands-on experience on machine learning (ML) tools and techniques for data processing and data analysis. Since future technologies increasingly rely upon machine learning, urban systems and architecture shall adopt it and the aspirant should learn creative ways to apply ML to better understand urban systems. The course covers a wider range ML techniques including supervised and unsupervised learning methods for data analysis and pattern recognition that help to better understand urban system for improving urban life.

All methods taught in the course will be applied to a common project to evaluate various dynamics of the urban environment. Students will work with time-series and geo-referenced data including temperature, relative humidity, illuminance, noise, people density, and dust particulate matter. Subjective impression survey data will also be integrated into the student projects to further explore influencing factors of the urban environment on our perceptual experiences. A selected neighborhood in the city of Zurich will be used as the case study and each student will present the findings of their research question in a final project.

Additionally, there are two of non-architectural skills the participants can develop during this course. First is an introduction to programming where at a minimum they can successfully use code-snippets to customize the computational tools presented in the course. Second, how clustering methods like PCA or K-Means could be applied in an architectural context.

Where: HIT H 31.4 (Video wall)
When: Mondays 10:00 - 12:00

2 ECTS

Supervision:

Course Flyer

Jan - 27 - 2017

FS2017 | Information Architecture and Future Cities: Smart Cities

The elective course ‘Information Architecture of Cities’ opens a holistic view on existing and new cities, with focus on Asia. The goal is to better understand the city by going beyond the physical appearance and by focusing on different representations, properties and impact factors of the urban system. As course requirement, there will be three short exercises.

 

What will happen when cities change from static configurations into responsive and dynamic structures? What does it mean for buildings that undergo the same changes? What is the impact on architectural and urban design education? How can citizens influence this development? The smart cities course will answer these questions and supply you with the necessary skills and knowledge to understand and design such dynamic structures. The intelligent use of data and information are at the core of this course. Data and information are new building materials of future cities. Citizens produce increasing amounts of data in their daily life, with stationary sensors and mobile smartphones. Using those data, citizens begin to influence the design of future cities and the re-design of existing ones. The course will be a first step towards the emerging citizen design science and cognitive design computing. Those will be the next generation of participatory design and design computing. The course will run parallel to the edX MOOC on Smart Cities.

Where: HIT H 31.4 (Video wall)
When: Mondays 13:00 - 14:00
2 ECTS

 

Supervision:

Prof. Dr. Gerhard Schmitt

Dr. Estefania Tapias

 

Course flyer

HS 13 Information Architecture of Cities - IBook
EdX MOOC on Future Cities

Presentation template: videowall_template

Jan - 27 - 2017

FS2017 | Creative Data Mining: Uncover and Evaluate

The students examine patterns of crowd-flows in an extraordinary urbanisation phenomena: festivals. Bottom-up urbanization you might recognize also on pictures from slums, (refugee/military/exploratory) camps etc. 
Learn how to simulate the flows of people and how to quantify the (real estate) value of stand locations. Caliente Festival, Zurich, will serve as an example.




The participants of this course learn how to collect, process, analyze and interpret real spatial and temporal data in order to work with quantifiable qualities in urban planning. This is achieved by using actual data from a recent study and analysing it with different data processing and machine learning techniques.

The goal of the course is to explore a specific research question about the urban environment and test the stated hypothesis using different techniques presented in the course, thus preparing students with a skill-set to further support their design and decision making processes.

The course focuses on creating deeper insights to critically evaluate design alternatives for urban planning projects. Students will work with time-series and geo-referenced data including temperature, relative humidity, illuminance, noise, people density, and dust particulate matter. Subjective impression survey data will also be integrated into the student projects to further explore influencing factors of the urban environment on our perceptual experiences. Non-architectural skills the participants can develop during this course are 1) an introduction to programming 2) how clustering methods like PCA or K-Means could be applied in an architectural context.


Where: HIT H 31.4 (Video wall)
When: Mondays 10:00 - 12:00


2 ECTS Supervision:

 

Jan - 27 - 2017

FS2017 | Digital Urban Simulation

A solid knowledge of computational methods is an increasingly important key competence for future architects or urban planners. In this course you will learn how to analyze and generate spatial configurations with advanced computational methods.

A solid knowledge of computational methods is an increasingly important key competence for future architects or urban planners. In this course you will learn how to analyze and generate spatial configurations with advanced computational methods.

In a series of theory lectures we explore how designing and planning of cities could become more evidence based by using scientific methods. Various exercises will provide training for your skills in working with state-of-the-art yet office-proven design tools (Rhino/Grasshopper and add-ons). In an integral project work, you will deepen your knowledge in spatial analysis and simulation methods such as Space Syntax using ConfigUrbanist and Decoding Spaces components packages and environmental analysis with the add-ons LadyBug and HoneyBee. In addition, you will acquire skills for using analysis methods for generative design processes. Therefore we introduce you into the parametric design software Grasshopper for Rhino 3D.

Based on the methods introduced during the semester, you will learn and understand different effects of planning and design interventions on urban life. At the end of the course you will be able to interpret analysis and simulation results, and to apply corresponding computational methods to your own planning projects.

Lecture, HIT F22 - Value Lab
Exercises, HIT H12

Course flyer

Teaching material is provided on moodle

.

Supervision:

Dr. Estefania Tapias

Dr. Peter Buš

 

 

Aug - 23 - 2016

HS2016 | Digital Urban Visualisation – People as Flows

The students examine patterns of crowd-flows in an extraordinary urbanisation phenomena: festivals. Bottom-up urbanization you might recognize also on pictures from slums, (refugee/military/exploratory) camps etc. 
Learn how to simulate the flows of people and how to quantify the (real estate) value of stand locations. Caliente Festival, Zurich, will serve as an example.




The students examine patterns of crowd-flows in an extraordinary urbanisation phenomena: festivals. They will learn how to program simulations using Processing/Java. Previous programming knowledge is not necessary. Furthermore they will gain insights into other analysis methods and learn about their significance, strengths and weaknesses.

Students will look at those patterns from two sides. One being the view of a planner asking to find bottle necks or the ideal place for amenities such as booths, toilets etc. Another being the view of visitors. Students will program different behaviours that should compete against each other in order to compare different strategies. Caliente Festival in Zurich will be used as a case study.

Where: HIT H 31.4 (Video wall)
When: Mondays 10:00 - 12:00
2 ECTS

Supervision:

Dani Zünd

zuend@arch.ethz.ch

Lukas Treyer

treyer@arch.ethz.ch

Artem Chirkin

chirkin@arch.ethz.ch

Aug - 23 - 2016

HS2016 | Information Architecture and Future Cities: Smart Cities

The elective course ‘Information Architecture of Cities’ opens a holistic view on existing and new cities, with focus on Asia. The goal is to better understand the city by going beyond the physical appearance and by focusing on different representations, properties and impact factors of the urban system. As course requirement, there will be three short exercises.

 

With the city becoming the predominant living and working environment of humanity, livability or quality of life in the city becomes crucial. In this course, we explore the impact of information and information architecture on the livability of cities. After the introduction to affordable livability and its measurable criteria, we explore possibilities of participatory urban design by future citizens, leading towards the development of a citizen design science. By week four, we give special attention to 4 crucial urban stocks and flows for urban design: water, energy, the local climate, and mobility. During the following lectures, we bring together the previous topics to explore how these stocks and flows affect the livability of the city. By the end of the course, students will be able to recognize the different measurable criteria for the assessment of livability, and how to influence the design of livable cities. The edX MOOC on Quality of Life: Livability in Future Cities is a good overview and starting point for this course.

Where: HIT H 31.4 (Video wall)
When: Mondays 13:00 - 14:00
2 ECTS

 

Supervision:

Prof. Dr. Gerhard Schmitt

Estefania Tapias

 

Poster

HS 13 Information Architecture of Cities - IBook
EdX MOOC on Future Cities

Presentation template: videowall_template

Aug - 23 - 2016

HS2016 | Digital Urban Simulation

A solid knowledge of computational methods is an increasingly important key competence for future architects or urban planners. In this course you will learn how to analyze and generate spatial configurations with advanced computational methods.

A solid knowledge of computational methods is an increasingly important key competence for future architects or urban planners. In this course you will learn how to analyze and generate spatial configurations with advanced computational methods.

In a series of theory lectures we explore how designing and planning of cities could become more evidence based by using scientific methods. Various exercises will provide training for your skills in working with state-of-the-art yet office-proven design tools (Depthmap, Ecotect, and Rhino/Grasshopper). In an integral project work, you will deepen your knowledge in spatial analysis and simulation methods such as Space Syntax using Depthmap software and environmental analysis with the program Ecotect. In addition you will acquire skills for using analysis methods for generative design processes. Therefore we introduce you into the parametric design software Grasshopper for Rhino 3D.

Based on the methods introduced during the semester, you will learn and understand different effects of planning and design interventions on urban life. At the end of the course you will be able to interpret analysis and simulation results, and to apply corresponding computational methods to your own planning projects.

Lecture, HIT F22 - Value Lab
Exercises, HIT H12

flyer

Teaching material is provided on moodle

.

Supervision:

Peter Buš

Estefania Tapias

 

Jan - 15 - 2016

HS2016 | Information Architecture and Future Cities: Smart Cities

The elective course ‘Information Architecture of Cities’ opens a holistic view on existing and new cities, with focus on Asia. The goal is to better understand the city by going beyond the physical appearance and by focusing on different representations, properties and impact factors of the urban system. As course requirement, there will be three short exercises.

 

With the city becoming the predominant living and working environment of humanity, livability or quality of life in the city becomes crucial. In this course, we explore the impact of information and information architecture on the livability of cities. After the introduction to affordable livability and its measurable criteria, we explore possibilities of participatory urban design by future citizens, leading towards the development of a citizen design science. By week four, we give special attention to 4 crucial urban stocks and flows for urban design: water, energy, the local climate, and mobility. During the following lectures, we bring together the previous topics to explore how these stocks and flows affect the livability of the city. By the end of the course, students will be able to recognize the different measurable criteria for the assessment of livability, and how to influence the design of livable cities. The edX MOOC on Quality of Life: Livability in Future Cities is a good overview and starting point for this course.

Where: HIT H 31.4 (Video wall)
When: Mondays 13:00 - 14:00
2 ECTS

 

Supervision:

Prof. Dr. Gerhard Schmitt

Estefania Tapias

 

course flyer

HS 13 Information Architectur of Cities - IBook

EdX MOOC on Future Cities

 

Presentation template: videowall_template

Jan - 15 - 2016

FS2016 | Digital Urban Simulation

In this course students analyze architectural and urban design using current computational methods. Based on these analyses the effects of planning can be simulated and understood.

In this course students analyze architectural and urban design using current computational methods. Based on these analyses the effects of planning can be simulated and understood.

An important focus of this course is the interpretation of the analysis and simulation results and the application of these corresponding methods in early planning phases.

The students learn how the design and planning of cities can be evidence based by using scientific methods. The teaching unit convey knowledge in state-of-the-art and emerging spatial analysis and simulation methods and equip students with skills in modern software systems. The course consists of lectures, associated exercises, workshops as well as of one integral project work.

HIT H 31.4 (Video wall)

Course flyer

Teaching material is provided on moodle.

Documentation of past courses

Supervision:

Jun.-Prof. Dr. Reinhard König

Estefania Tapias

 

Jan - 15 - 2016

FS2016 | Creative Data Mining

It is increasingly important to know how to work with big amounts of data - especially in such highly complex fields like architecture and urban planning. Thus participants will learn how to to create whole landscapes of designs in a semi-automatic manner.

Intuitively Analysing Design Ideas

The goal of this course is to introduce various data mining techniques for design and urban planning applications.  Students will learn how to select relevant data sources and collect their own data using a “sensor backpack”. Various methods will be applied to a common project to evaluate the predominant influencing factors of the urban environment on our perceptual experiences.  A select neighborhood in the city will be used as a case study. Final results will be presented in the last class.

The course will start with an initial overview to data mining and the relevant mathematics as well as an introduction to the programming tool (RStudio). Then students will learn how to use and interpret results from a machine-learning tool to cluster self-made design sketches, which automatically generate qualitative collages. Finally, students will collect data using a “sensor backpack” with environmental sensors such as noise, temperature, illuminance, and air particulates. Students will also generate the data for perceptual quality in this neighborhood through time-stamped and geo-referenced surveys and biofeedback wristbands.  Students will be given a work-flow to collect, process, analyze and interpret this data which may be used in their final projects.

Room & Timeslot:

HIT H12 on Mondays from 10:00 to 12:00

Supervision:

Danielle Griego

Matthias Standfest

Requirement: Former knowledge of any digital tool or coding language is most welcome but NOT required at all. You only need to provide  a reasonable amount of motivation and of course a notebook.

course flyer

Aug - 17 - 2015

HS2015 | Information Architecture and Future Cities: Smart Cities

What will happen when cities change from static configurations into responsive and dynamic structures? What does it mean for buildings that undergo the same changes? What is the impact on architectural and urban design education? How can citizens influence this development? The Smart Cities course will answer these questions.

What will happen when cities change from static configurations into responsive and dynamic structures? What does it mean for buildings that undergo the same changes? What is the impact on architectural and urban design education? How can citizens influence this development? The Smart Cities course will answer these questions and supply you with the necessary skills and knowledge to understand and design such dynamic structures. The intelligent use of data and information are at the core of this course. Data and information are new building materials of future cities. Citizens produce increasing amounts of data in their daily life, with stationary sensors and mobile smartphones. Using those data, citizens begin to influence the design of future cities and the re-design of existing ones. The course will be a first step towards the emerging citizen design science and cognitive design computing. Those will be the next generation of participatory design and design computing.

Where: HIT H 31.4 (Video wall)
When: Mondays 13:00 - 14:00
2 ECTS

 

Supervision:

Prof. Dr. Gerhard Schmitt

gerhard.schmitt@arch.ethz.ch

Danielle Griego

griego@arch.ethz.ch

Flyer_HS_Future Cities

HS 13 Information Architectur of Cities IBook

Aug - 14 - 2015

HS2015 | Digital Urban Simulation

In this course students analyze architectural and urban design using current computational methods. Based on these analyses the effects of planning can be simulated and understood.

In this course students analyze architectural and urban design using current computational methods. Based on these analyses the effects of planning can be simulated and understood.

An important focus of this course is the interpretation of the analysis and simulation results and the application of these corresponding methods in early planning phases.

The students learn how the design and planning of cities can be evidence based by using scientific methods. The teaching unit convey knowledge in state-of-the-art and emerging spatial analysis and simulation methods and equip students with skills in modern software systems. The course consists of lectures, associated exercises, workshops as well as of one integral project work.

HIT H 31.4 (Video wall)

Flyer_HS_Digital Urban Simulation

 

Teaching material is provided on moodle.

Supervision:

Dr. Reinhard König

Estefania Tapias

 

Jun - 03 - 2015

Crowd Simulation – People as Flows

The students examine patterns of crowd-flows in an extraordinary urbanisation phenomena: festivals. Bottom-up urbanization you might recognize also on pictures from slums, (refugee/military/exploratory) camps etc. 
Learn how to simulate the flows of people and how to quantify the (real estate) value of stand locations. Caliente Festival, Zurich, will serve as an example.




The students examine patterns of crowd-flows in an extraordinary urbanisation phenomena: festivals. Festivals are comparable to urbanization in the their attitude of buttom-up organization of space comparable to situations in slums or camps (military/exploratory/refugee camps). Students will learn how to program simulations using Processing/Java. Previous programming knowledge is not necessary. Furthermore they will be given an overview on different kinds of simulation and analysis methods and learn about their significance, strengths and weaknesses.

Students will look at the mentioned urbanization patterns from two sides. One being the view of a planner asking to find bottle necks or the ideal place for amenities such as food stalls, medical services, toilets etc. Another being the view of visitors. Students will program different behaviours that should compete against each other in order to compare different strategies to achieve goals like passing through the area quickly or get the preferred food as quickly as possible. Caliente Festival in Zurich will be used as a case study.

Where: HIT H 31.4 (Video wall)
When: Mondays 10:00 - 12:00
2 ECTS

Supervision:

Dani Zünd

zuend@arch.ethz.ch

Lukas Treyer

treyer@arch.ethz.ch

Flyer_HS_Crowd Simulation