teaching statement ms bittermann

8/12/2019 Teaching Statement MS Bittermann

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Teaching activities at Delft University of Technology, Faculty of Architecture

Michael S. Bittermann

The content of the research I have been carrying out I imparted to the students at Delft

University of Technology in the framework of the Bachelor education, and of the

Computational Architecture MSc Program, of which I am the coordinator and responsible

tutor. Under my supervision the students acquire knowledge and experience with thecomputational intelligence methods that I study. Next to the theoretical explanations, I

provide the students with the methods in a friendly CAD software environment, so that they

implement the advanced computations with ease and with minimal change in design

workflow. This way, architecture students handle the complexity of their design task with

scientific precision from on the early phase of design, i.e. they are able to systematically reach

solutions that satisfy multiple, conflicting objectives, they pursue, while some of which are

soft in nature, such as spatial, aesthetic, historic and cultural ones. This asset I deem as a

unique distinctive feature for the prosperous future of the students in their professional

careers, eventually impacting architectural practice in the direction of quality assured design.

Systematic complexity treatment, as I am teaching based on my research, is an essential

demanded asset in contemporary architectural design projects that are characterized by high

complexity. Next to that, through the understanding and use of the computational methods

they gain a better understanding of what design is and how it works. This is because the

methodology emulates human design process.

• In the BSc education of the chair of Design Informatics I have the following lectures:

- Designing by means of computational intelligence

Synopsis: Introduction to the design formalism, where design is regarded as intelligent

brain activity; defining what complexity is; distinguishing the different sources of

complexity in design, and which computational methodologies are suitable for their

treatment.- Evaluating and improving sustainability using computational intelligence

Synopsis: Addressing the soft nature of the sustainability concept, and appropriate ways

to deal with it; subjectivity and softness of information in complexity; critical assessment

of the concepts of bio-mimicry and cradle to cradle

- The role of parametric design in architectural design

Synopsis: Defining what parametric design is; identification of benefits and

shortcomings; pin-pointing the role of parametric design in computational design process.

• In the MSc program Computational Architecture I give the following courses:

- Visual perception modeling by probabilistic computation

Synopsis: Experiment on the uncertainty of vision as ‘overlooking’, as vision blur;

Introduction of probability concept, probability density; vision, attention, awareness, and

perception; perception in a basic geometric case; in general geometric case; perception

along a line in the environment; effect of distance on attention and perception;

conditional probability (Bayesian rule); blur in human vision; color; color perception.

Design studio with exercises: perception analysis of an urban environment

- Design performance analysis using fuzzy neural-tree modeling

Synopsis: introduction of fuzzy concept; antecedent and consequent space; fuzzymodeling; neural tree concept; fuzzy neural tree; architectural performance evaluation;

integration with design optimization.

Design studio with exercises: The students use the fuzzy neural tree method in a friendly

CAD software (Grasshopper-Rhino) to assess the performance of their designs.



Fig. 2 Second poster promoting in the Faculty of Architecture the MSc program MSc program

of which I have been the coordinator and main tutor.

teaching statement ms bittermann

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