ADAMS Lab
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Adaptive Design Algorithms, Models and Systems (ADAMS) Lab is a research lab in University at Buffalo, directed by Dr. Souma Chowdhury. in ADAMS Lab, we investigate new approaches that are founded on a fundamental notion of "adaptation". Adaptation is realized by bringing together nature inspired principles of computation, rigorous engineering design methods, and machine learning. Core areas of computational research in the ADAMS lab include: 1) Evolutionary & Social/Swarm-Intelligence Algorithms: mixed-integer optimization and autonomous multi-agent systems; 2) Surrogate Modeling and Computational Learning: model error estimation, automated model selection; 3) Multi-fidelity and Multidisciplinary Optimization (MDO): adaptive model refinement and switching. Major areas of application include: Unmanned Aerial Vehicles (UAVs), Cyber-Physical Systems, Wind Farm Design, Building Energy Efficiency, Product Platform Planning.
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PEMF cross-validation
PEMF is predictive (cross-validation type) approach to test surrogate models.
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