Anahita Khodadadi, PhD
Anahita Khodadadi is an assistant professor of architecture who joined UB as part of its cross-disciplinary Learning Science Initiative.
Anahita Khodadadi is an assistant professor in the School of Architecture and Planning who collaborates with researchers across the Graduate School of Education, College of Arts and Sciences, and School of Engineering and Applied Sciences as a part of the campus-wide Learning Science Initiative.
A glimpse of four design exploration projects conducted by Khodadadi through a combination of a genetic algorithm and TRIZ.
Design exploration process using the ParaGen component of the GA+TRIZ method
Her research interests lie in three primary areas, an interdisciplinary scope that contributes contributes to both the fields of computer-aided design but also building science:
- Computation and design science, including form exploration methods, parametric modeling, application of a genetic algorithm in multi-objective design, creative design thinking, and innovative problem-solving
- Building science, including thermal and daylighting simulation, integrated design, structural and environmental analyses of the buildings, life cycle assessment
- Science education in architectural pedagogy, including inclusive teaching and active learning approaches.
Within the computation and design science field, her studies focus on the early phases of design and consideration of both quantitative performance-based and qualitative characteristics of design alternatives. Accordingly, most of her studies have attempted to expose designers to a wide diversity of suitable solutions rather than minimizing options in the interest of high performance. She received her doctorate in architecture (building technology) at the University of Michigan, where her dissertation was devoted to developing a computational form exploration method that considers the concepts and principles of creative and productive thinking. Her developed method is based on the application of a genetic algorithm (GA) and the Theory of Innovative Problem Solving (TRIZ).
Khodadadi joined UB in Fall 2022 from Portland State University, where she served as an assistant professor for three years and taught interconnected courses on building tectonics, building structures, building science, and design studios. She is a LEED Green Associate and has collaborated with several architecture firms in Oregon on research-based design projects to address sustainable design requirements and the climate change crisis. In addition, she has led multiple student teams in developing clean tech innovations and start-ups that earned funding and awards. She received the Excellence in Teaching Sustainability Award at Portland State University in 2021.
She earned her Bachelor of Architecture and Master of Architecture from the University of Tehran, which led her to practice architectural design as a registered architect in Tehran. She advocates for inclusive and equitable education through multi-model learning environments that support student learning outcomes. Khodadadi also contributes to open education initiatives by developing open-access textbooks and learning materials.
Selected work
Design exploration by using a genetic algorithm and the Theory of Inventive Problem Solving (TRIZ)
Published by Anahita Khodadai and Peter von Buelow in the Journal of Automation in Construction, Sept. 2022
This paper presents a computational design exploration method called GA+TRIZ, which aids designers in defining the design problem clearly, making a parametric model where pertinent variables are included, obtaining a series of suitable solutions, and resolving existing conflicts among design objectives. The goal is to include the designer's qualitative and performance-based quantitative design goals in the design process, while promoting innovative ideas for resolving contradictory design objectives.
The method employed is a Genetic Algorithm (GA), earlier implemented in an automated design exploration process called ParaGen, in combination with the Theory of Inventive Problem Solving (TRIZ), a novel methodology to assist architects and structural engineers in the conceptual phase of design. The GA+TRIZ method promotes automated design exploration, investigation of unexpected solutions, and continuous interaction with the computational generating system. Finally, this paper presents two examples that illustrate how the GA+TRIZ method assists designers in problem structuring, design exploration, and decision-making.
Computational form exploration of branching columns using concepts of formex algebra and the ParaGen method
Paper presented at IASS Annual Symposium 2020-21 and the 7th International Conference on Spatial Structures
A tension thread model with adjustable nodes used to study compression only geometries.
This study addresses the relationship between the geometry and structural performance of branching columns using an example case based on a square grid shell supported by four branching columns. The branching columns are configured with three levels of members, bifurcating into four members as each member branches upwards. A range of solutions is parametrically generated using the concepts of formex algebra and its associated software system, Formian 2.0. The form exploration uses the GA-based method, ParaGen which incorporates both quantitative structural performance and qualitative architectural considerations in the exploration process. Certain design constraints, as well as multiple objectives, are established including minimizing structural weight and deflection, and increasing vibration stiffness, in addition to the designer’s satisfaction with the visual appearance of the columns.
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