Type: Master, Elective | Credit: 3 | ECTS Credit: 7.5
Digital Topographies of Form
Asst. Prof. Dr. Ayşegül Akçay Kavakoğlu – akcaysegul@gmail.com
Mondays 13.30-16.30
The course examines past and contemporary digital design theory and practice approaches to enable a critical discussion on the current state of digital design, computation, and representation concerning the quest of the form in design and architecture. It focuses on the evolving meanings of form by discussing the paradigmatic shifts in architecture that occurred via technological developments. The course covers critical discussions on the topics such as morphology, topology, computation, and aesthetics concerning form generation, representation, and production. Reading materials cover book chapters and research articles by architects, researchers, and designers. Workshops and guest speakers will support the course to foster the discussions.
ÖZGÜN BALABAN BIO
Type: Master, Elective | Credit: 3 | ECTS Credit: 7.5
ımage credits: Immanuel Koh - Phd Thesis
Machine Learning in Architecture
Dr. Özgün Balaban - ozgunbalaban@gmail.com
Tuesdays 13.30-16.30
Content: The course is an introduction to Machine Learning methods with examples from architectural design and creative coding. The course follows a hands on approach with many examples that will be developed during the course. The course includes topics from machine learning such as linear regression, unsupervised learning, supervised learning, reinforcement learning and finally neural networks.
Aims: To have students acquire practical knowledge on the tools of machine learning and different methodologies. To have students knowledge of applying these techniques to creative design process.
Conduct:
The first half of the term includes introduction to the various machine learning topics. In this phase there will be practical coding sessions and some assignments which will be graded. In the second half of the term we will focus on a group project which will be developed using neural networks. The grading for the course is as follows: hands-on practices, 50%; final group project 50%.
ÖZGÜN BALABAN BIO
Ozgun is currently an adjunct lecturer research at the Istanbul Technical University and MEF University. He was a PhD Researcher at Future Cities Laboratories, Singapore. He has a doctoral degree from Singapore University of Technology and Design (SUTD) and a MSc degree in Architectural Design Computing from Istanbul Technical University. He has a BSc in Electrical Engineering and A.A in Interior Architecture both from Bilkent University. His research interests include building information modeling, data analytics and machine learning for architecture and urban planning, use of game environments in design. More info at www.parametricfood.com/ozgunbalaban