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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An Explainable Physics-Informed Neural Frequency-Response Framework for Shunt-Parameter Identification in Semi-Active Piezoelectric Tuned Mass Dampers
Andreas Georgiou, Vasileios Gkatsis, Vasileios Sioros, George Giannakopoulos, Nikolaos Chrysochoidis, Christoforos Rekatsinas
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Towards trajectory-unsupervised physics-informed neural solvers for molecular dynamics
Petros Triantafyllos, Panagiotis Krokidas, Christoforos Rekatsinas
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Active Learning Guided Design Space Refinement for Scalable Multi-Objective Bayesian Optimization in Materials Discovery
Alexandros Ntagiantas, Panagiotis Tsilimidos, George Giannakopoulos, Christoforos Rekatsinas, Panagiotis Krokidas
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A Physics Constrained Machine Learning Pipeline for Young’s Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos
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Frugal Bayesian Optimization: Scalable Surrogates for Data-and Resource-Limited Discovery
Panagiotis Krokidas, Christoforos Rekatsinas, Vassilis Sioros, Grigorios M Chatziathanasiou, Efi-Maria Papia, George Giannakopoulos
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Probabilistic Physics-Informed Neural Solvers for Woods-Saxon Parameter Identification: A Coupled Forward- Inverse Approach
Iraklis Spyrou, Christos Tsepas, Vaia Prassa, Christoforos Rekatsinas
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Physics-Informed Neural Networks without Loss Balancing: A Direct Term Scaling Approach for Nonlinear 1D Problems
Theodosios Theodosiou, Christoforos Rekatsinas
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Molecular Simulation of Hydrogen Systems: From Properties and Methods to Applications and Future Directions
Ahmadreza Rahbari, Thejas Hulikal Chakrapani, Fei Shuang, Panagiotis Krokidas , Parsa Habibi, V. Jelle Lagerweij, Mahinder Ramdin, Thijs J. H. Vlugt, Hadi Hajibeygi, Poulumi Dey, Ioannis N. Tsimpanogiannis, Othonas A. Moultos
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A machine learning framework for predicting moisture effects on active sensory piezoelectric flax composite laminates
Antigoni Barouni, Vasileios Gkatsis, Nikolaos Chrysochoidis, Georgios Giannakopoulos, Christoforos Rekatsinas
