Adam Gaier

Autodesk (United States) — United States

Computer Science · Physical Sciences

8h-index303citations34works5.92yr avg
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Research Topics

Advanced Multi-Objective Optimization Algorithms(10), Artificial Intelligence in Games(6), Metaheuristic Optimization Algorithms Research(4), Evolutionary Algorithms and Applications(4), Machine Learning and Data Classification(4)

Publications34 total

Full Domain Analysis in Fluid Dynamics
Machine Learning and Knowledge Extraction·2025Open Access
Full Domain Analysis in Fluid Dynamics
arXiv (Cornell University)·2025Open Access
Seeing Inside Buildings: Leveraging generative AI and multimodal data to automate building material audits
Proceedings of the International Conference on Computer-Aided Architectural Design Research in Asia·2025· 1 cited
Language Model Crossover: Variation through Few-Shot Prompting
ACM Transactions on Evolutionary Learning and Optimization·2024· 41 cited
PlotMap: Automated Layout Design for Building Game Worlds
2024· 1 cited
Generative Design through Quality-Diversity Data Synthesis and Language Models
Proceedings of the Genetic and Evolutionary Computation Conference·2024· 8 citedOpen Access
Bayesian Optimization for Quality Diversity Search With Coupled Descriptor Functions
IEEE Transactions on Evolutionary Computation·2024· 8 citedOpen Access
TileGPT: Generative AI for Intuitive Design Exploration and Trade-Offs Navigation Title
2024
2D Airfoil Optimization
TIB Data Manager·2024Open Access
3D Aerodynamics Design
TIB Data Manager·2024Open Access
PlotMap: Automated Layout Design for Building Game Worlds
arXiv (Cornell University)·2023Open Access
Editorial to the “Evolutionary Reinforcement Learning” Special Issue
ACM Transactions on Evolutionary Learning and Optimization·2023
BOP-Elites, a Bayesian Optimisation Approach to Quality Diversity Search with Black-Box descriptor functions
arXiv (Cornell University)·2023· 3 citedOpen Access
Harnessing Game-Inspired Content Creation for Intuitive Generative Design and Optimization
2022· 2 cited
COIL: Constrained optimization in learned latent space
Proceedings of the Genetic and Evolutionary Computation Conference Companion·2022· 9 citedOpen Access
A discretization-free metric for assessing quality diversity algorithms
Proceedings of the Genetic and Evolutionary Computation Conference Companion·2022· 1 cited
T-DominO: Exploring Multiple Criteria with Quality-Diversity and the Tournament Dominance Objective
arXiv (Cornell University)·2022Open Access
COIL: Constrained Optimization in Learned Latent Space: Learning Representations for Valid Solutions
arXiv (Cornell University)·2022· 3 citedOpen Access
Evolving Through the Looking Glass: Learning Improved Search Spaces with Variational Autoencoders
Lecture notes in computer science·2022· 10 citedOpen Access
T-DominO
Lecture notes in computer science·2022· 4 citedOpen Access
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Frequent Co-authors

Alexander Asteroth(13), Jean-Baptiste Mouret(11), James Stoddart(6), Lorenzo Villaggi(6), Peter J. Bentley(5), Alexander Hagg(3), Soo Ling Lim(3), Juergen Branke(3), Linh Tran(2), Paul R. C. Kent(2), Jieliang Luo(2), Evan Atherton(2), Hilmar Koch(2), Dominik Wilde(2), Holger Foysi(2), Dirk Reith(2), David Ha(1), Elliot Meyerson(1), Mark Nelson(1), Herbie Bradley(1)