In this multi-day workshop participants will learn about the basics of rope splicing and the role of this craft method in the work of artist Janet Echelman. The workshop will begin with a talk from artist Janet Echelman followed by a tutorial on rope splicing techniques. The remainder of the workshop will be focused on constructing a full-scale prototype of a fragment of a site-specific sculpture that is scheduled to be installed in the MIT Museum in the fall of 2025. The workshop will end with a test fit of the fragment on site in the MIT Museum.

Selection of thesis topic, definition of method of approach, and preparation of thesis proposal. Independent study supplemented by individual conference with faculty.

Selection of thesis topic, definition of method of approach, and preparation of thesis proposal. Independent study supplemented by individual conference with faculty.

Introduces advanced topics in building simulation for design and control of envelope and thermal systems for architects, engineers, environmental consultants, and beyond. Students will gain conceptual knowledge and technical skills to drive design decisions based on environmental performance. The focus of final design projects will be to reduce operational energy usage and carbon intensity. Course format will include a combination of traditional lectures, hands-on exercises, and design project development.

Selection of thesis topic, definition of method of approach, and preparation of thesis proposal. Independent study supplemented by individual conference with faculty.

Selection of thesis topic, definition of method of approach, and preparation of thesis proposal. Independent study supplemented by individual conference with faculty.

Focuses on applications of machine learning (ML) for creative design generation and data-informed design exploration, with an emphasis on visual and 3-D generative systems. Explores how recent advances in artificial intelligence, and specifically machine learning, can offer humans more natural, performance-driven design processes. Covers a wide range of machine learning algorithms and their applications to design, with topics including neural networks, generative adversarial networks, variational autoencoders, dimensionality reduction, geometric deep learning, and other ML techniques. Includes an open-ended, applied research or design project demonstrating an original, creative use of machine learning for design, architecture, engineering, or art. 

UG: 4.440, 1.056; Grad: 4.462

Introduces the design and behavior of large-scale structures and structural materials. Emphasizes the development of structural form and the principles of structural design. Presents design methods for timber, masonry, concrete and steel applied to long-span roof systems, bridges, and high-rise buildings. Includes environmental assessment of structural systems and materials. In laboratory sessions, students solve structural problems by building and testing simple models. 

Graduate and undergraduate students have separate lab sections.

GIR LAB (4.440)