Dissertation Title: Inverse Discrete Design

Abstract: 

In human history, no innovation has progressed as rapidly as digital technologies. Yet, it wasn't until the 2000s that we began to feel this impact on the physical world. With the rise of the Internet of Things, our built environment is becoming smarter, more dynamic, and more complex. Each year, the line between physical and digital blurs further. However, examining the history of computer-aided design (CAD), engineering (CAE), and manufacturing (CAM) tools reveals few radical advancements since the invention of "Sketchpad" in 1963—the first interactive CAD system. We urgently need these radical advances to faithfully model and respond to our complex environment, and to enable us to imagine and design a new world where the physical and digital are indistinguishable.

To achieve that, we need novel physical and digital tools that can handle complexity and grow reliability. Just as digitizing analog signals revolutionized and scaled communication and computing, applying discretization and error correction principles to the physical world unlocks the ability of the precise placement of functional materials with embedded electrical and mechanical properties. These “Digital Material” structures introduce digital programmability to the physical realm, mirroring the transformative impact seen in digital technologies. In my thesis, I introduce fully declarative and inverse workflows to design and build scalable Digital Material systems. Using these workflows the user can model and design systems that span scales (micro, meso, macro) and disciplines (electrical, mechanical, aerospace, architectural engineering) without being an expert in all—or any—of these fields.

Using principles of discretization, distributed computing, hierarchy, and error correction; the introduced workflows use domain knowledge as priors and universal design representations across all stages—simulation, optimization, fabrication, and control. These tools have been used to design a plethora of static and dynamic structures, ranging from bridges and shelters to aerospace structures, robots, and electronics.

Neil Gershenfeld
Director, The Center for Bits and Atoms, MIT

Katia Bertoldi
William and Ami Kuan Danoff Professor of Applied Mechanics, SEAS, Harvard University

Kirstin Petersen
Associate Professor, Electrical and Computer Engineering, Cornell University