| Learning black-and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data S Lee, YM Psarellis, CI Siettos, IG Kevrekidis Journal of Mathematical Biology 87 (1), 15, 2023 | 19 | 2023 |
| Investigation of reaction mechanisms in the chemical vapor deposition of al from DMEAA GM Psarellis, IG Aviziotis, T Duguet, C Vahlas, ED Koronaki, ... Chemical Engineering Science 177, 464-470, 2018 | 19 | 2018 |
| Physics-agnostic and physics-infused machine learning for thin films flows: modelling, and predictions from small data CP Martin-Linares, YM Psarellis, G Karapetsas, ED Koronaki, ... Journal of Fluid Mechanics 975, A41, 2023 | 8 | 2023 |
| Data-driven Discovery of Chemotactic Migration of Bacteria via Machine Learning YM Psarellis, S Lee, T Bhattacharjee, SS Datta, JM Bello-Rivas, ... arXiv preprint arXiv:2208.11853, 2022 | 8 | 2022 |
| Writing the Programs of Programmable Catalysis YM Psarellis, ME Kavousanakis, PJ Dauenhauer, IG Kevrekidis ACS Catalysis 13, 7457-7471, 2023 | 7 | 2023 |
| From partial data to out-of-sample parameter and observation estimation with diffusion maps and geometric harmonics ED Koronaki, N Evangelou, YM Psarellis, AG Boudouvis, IG Kevrekidis Computers & Chemical Engineering 178, 108357, 2023 | 6 | 2023 |
| Limits of entrainment of circadian neuronal networks YM Psarellis, M Kavousanakis, MA Henson, IG Kevrekidis Chaos: An Interdisciplinary Journal of Nonlinear Science 33 (1), 2023 | 2 | 2023 |
| Equation-free computations as DDDAS protocols for bifurcation studies: a granular chain example MO Williams, YM Psarellis, D Pozharskiy, C Chong, F Li, J Yang, ... Handbook of Dynamic Data Driven Applications Systems: Volume 2, 123-146, 2023 | 1 | 2023 |
| Note on the Control of Processes Exhibiting Input Multiplicity RJ Lovelett, YM Psarellis, IG Kevrekidis, M Morari Industrial & Engineering Chemistry Research 62 (5), 2138-2143, 2022 | 1 | 2022 |
| Χημική απόθεση αλουμινίου από ατμό από την πρόδρομη ένωση DMEAA: Διερεύνηση μηχανισμών χημείας και κινητικής Γ Ψαρέλλης | 1 | 2017 |
| Programmable Catalytic Ammonia Synthesis and Its Optimization A Manoj, A Georgiou, G Psarellis, M Kavousanakis, PJ Dauenhauer, ... 2023 AIChE Annual Meeting, 2023 | | 2023 |
| From Navier-Stokes simulations for thin films to amplitude equations and back via physics-assisted machine-learning C Martin Linares, E Koronaki, Y Psarellis, G Karapetsas, I Kevrekidis Bulletin of the American Physical Society, 2022 | | 2022 |
| Accelerating Multiscale Global Optimization through Reduced Bayesian Optimization NJ Wichrowski, G Psarellis, A Georgiou, J Bello-Rivas, F Dietrich, ... 2022 AIChE Annual Meeting, 2022 | | 2022 |
| A Machine Learning Approach to Bridge the Gap between the Kuramoto-Sivashinsky and the Navier-Stokes Equations for Thin Film Flow CM Linares, E Koronaki, G Psarellis, G Karapetsas, IG Kevrekidis 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Computations and Optimization for Catalysts Under Dynamic Operation G Psarellis, P Dauenhauer, M Kavousanakis, IG Kevrekidis 2021 AIChE Annual Meeting, 2021 | | 2021 |
| Pathologies of Neural Networks As Models of Discrete-Time Dynamical Systems T Cui, G Psarellis, T Bertalan, S Reich, IG Kevrekidis 2021 AIChE Annual Meeting, 2021 | | 2021 |
| Learning Partial Differential Equations from Multiscale or Experimental Data: A Showcase on Bacterial Chemotaxis G Psarellis, S Lee, S Datta, IG Kevrekidis 2021 AIChE Annual Meeting, 2021 | | 2021 |
| Learning Coarse-Grained Partial Differential Equations from Fine-Scale Data Via Machine Learning S Lee, G Psarellis, H Arbabi, C Siettos, F Dietrich, G Samaey, ... 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| Assessing the Response of Dynamic Catalytic Surfaces G Psarellis, MA Ardagh, P Dauenhauer, IG Kevrekidis 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| Connections between Residual Networks and Explicit Numerical Integrators, with Applications to Identification of Noninvertible Dynamical Systems T Cui, T Bertalan, G Psarellis, IG Kevrekidis 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
