Computational Design Exploration
Computational Design Exploration is a computational methodology within generative design optimization that systematically investigates and navigates the space of possible design solutions using algorithmic and simulation-driven processes to identify high-performing configurations according to predefined criteria.
228
Publications
10.9K
Citations
787
Authors
311
Institutions
Publications per year
2017–2026
106
228
Deep Generative Design: Integration of Topology Optimization and Generative Models
Sangeun Oh, Yongsu Jung, Seongsin Kim et al. · Journal of Mechanical Design · 2019 · 437 citations · Full text
Efficiently exploring architectural design spaces via predictive modeling
Engin İpek, Sally A. McKee, Rich Caruana et al. · 2006 · 323 citations
1–5 of 228
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311
Massachusetts Institute of Technology
Cambridge, United States
7 h-index
18 publications
785 citations
ETH Zurich
Zurich, Switzerland
7 h-index
16 publications
457 citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
17 publications
559 citations
Georgia Institute of Technology
Atlanta, United States
6 h-index
18 publications
764 citations

Delft University of Technology
Delft, The Netherlands
6 h-index
12 publications
1.2K citations

Lawrence Livermore National Laboratory
Livermore, United States
5 h-index
18 publications
1.3K citations
The University of Texas at Austin
Austin, United States
5 h-index
10 publications
445 citations

Cornell University
Ithaca, United States
4 h-index
12 publications
1.3K citations
1–8 of 311
9 publications · 704 citations
9
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IJAC · 7 publications · 180 citations
7
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7 publications · 227 citations
7
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TOG · 5 publications · 515 citations
5
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AIEDAM · 4 publications · 233 citations
4
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