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Cornell University

GENERATIVE AND RESPONSIVE DESIGN: THE EMERGENT

Abstract

dc:description.abstract

When I decided to choose Architecture+Representation as my territory of investigation, I had considerable interest and curiosity in the principles and potential of emerging technologies in the field of architecture. However, I was confused about their significance and goals. Because the theoretical support of the latest technologies in the field of architecture is being built and refined but with no commonly recognized knowledge, it was precisely the confusion that guided me and ultimately made my studies at MS AAD so rewarding.The degree book revolves around my interpretation of the definition of “emergent” in the context of generative design, i.e., a way of generating where the result is the superposition of a series of unpredictable processes. This book focuses on three projects I have completed at MSAAD that provide insight into architectural design’s unpredictability and complex interaction in terms of the generative process, the metabolic process, and the post-life.

Degree

thesis:*
Name thesis:degree_name
M.S., Architecture
Level thesis:degree_level
Master of Science
Discipline thesis:degree_discipline
Architecture
Grantor
Cornell University
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Geng, Xinyue
Committee member dc:contributor.committeemember
  • Sabin, Jenny

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • Attribution-NonCommercial-NoDerivatives 4.0 International
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
ProQuest Submission ID: 11641
ProQuest Publication ID: 30242945
OAI identifier oai:identifier
oai:ecommons.cornell.edu:1813/113015

Chain of custody

source
Harvested from
Cornell University
Base URL
ecommons.cornell.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Geng, Xinyue. GENERATIVE AND RESPONSIVE DESIGN: THE EMERGENT. Master of Science thesis, Cornell University, 2022. https://hdl.handle.net/1813/113015