Our Publications
INSANE promotes AI-enabled interdisciplinary alliances by providing mentoring and guidance to scientists, researchers, and professionals, while also acting as a liaison between different fields of study and knowledge.
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Navigating materials design spaces with efficient Bayesian optimization: a case study in functionalized nanoporous materials
Panagiotis Krokidas, Vassilis Gkatsis, John Theocharis, George Giannakopoulos
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Density-Aware Active Learning for Materials Discovery: A Case Study on Functionalized Nanoporous Materials
Vassilis Gkatsis, Petros Maratos, Christoforos Rekatsinas, George. Giannakopoulos and Panagiotis Krokidas
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A data-lean machine learning approach for damage extent estimation and classification in composite structures under multiple failure modes
Dimitrios Iason Papadopoulos, George Giannakopoulos, Vangelis Karkaletsis and Christoforos Rekatsinas
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Molecular Simulation of Coarse-grained Systems using Machine Learning
Dimitrios-Paraskevas Gerakinis, Eleonora Ricci, George Giannakopoulos, Vangelis Karkaletsis, Doros N. Theodorou, Niki Vergadou,
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Self-Adaptive Optimization of Coefficients in Multi-Objective Loss Functions
Spillios Delis, Eleonora Ricci, Dimitrios-Paraskevas Gerakinis, Niki Vergadou, George Giannakopoulos
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Multi-fidelity Bayesian Optimization for Efficiently Sampling the Design Space of Functionalized Nanoporous Materials
Ioannis Theocharis, Panagiotis Krokidas, Vassilis Gkatsis, George Giannakopoulos
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Solving Linear Elasticity Problems using Physics-Informed Neural Networks
Petros Kafkas, George Giannakopoulos, Christoforos Rekatsinas
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Inverse design of ZIFs through artificial intelligence methods
Panagiotis Krokidas, Michael Kainourgiakis, Theodore Steriotis, George Giannakopoulos
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Bio-inspired discontinuous composite materials with a machine learning optimized architecture
Theodoros Loutas, Athanasios Oikonomou, Christoforos Rekatsinas
