Teaching Statement MS Bittermann
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Transcript of 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.
8/12/2019 Teaching Statement MS Bittermann
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8/12/2019 Teaching Statement MS Bittermann
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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.