PhD Courses in Denmark

Designing is a complex process that involves the consideration of a plethora of aspects, such as different design criteria and performance aspects that often are at odds with each other. To tackle the multidimensionality of the performance-based design, designers either need to ponder simultaneously different aspects or resort to (semi)automated search procedures to examine better the potential trade-offs of a wide range of design solutions that compose the design space. For example, it is becoming common to use parametric design and multi-objective optimization techniques borrowed from other disciplines (e.g., computer science, artificial intelligence, mathematics, statistics, sociology) to explore the design space of a multi-criteria design problem more effectively. While the trade-offs of two performance/decision variables are easy to examine, the complexity of analyzing the output of parametric design explorations and multi-objective optimization processes exponentially increases along with the number of decision variables, thus hindering decision-making processes during the design process.

This course will examine the crucial role of data visualization in analysis and decision-making processes in complex multi-criteria design problems. Through a series of readings, lectures, workshops and practical exercises, it will explore different visualization methods to improve analysis tasks and statistical techniques to simplify the complexity of the problem (e.g., dimensionality reduction). Thus, the course requires a multidisciplinary view that involves the knowledge of different fields such as computer simulation, statistics, data visualization, and parametric and goal-oriented design. The goal is to develop better ways to steer the design of buildings or products that involve several performance indicators and enable students to fully address the complexity of multi-criteria performance-based design.