| Kapitza resistance between few-layer graphene and water: liquid layering effects D Alexeev, J Chen, JH Walther, KP Giapis, P Angelikopoulos, ... Nano letters 15 (9), 5744-5749, 2015 | 223 | 2015 |
| Learning to school in the presence of hydrodynamic interactions M Gazzola, AA Tchieu, D Alexeev, A de Brauer, P Koumoutsakos Journal of Fluid Mechanics 789, 726-749, 2016 | 171 | 2016 |
| Synchronisation through learning for two self-propelled swimmers G Novati, S Verma, D Alexeev, D Rossinelli, WM Van Rees, ... Bioinspiration & biomimetics 12 (3), 036001, 2017 | 168 | 2017 |
| The in-silico lab-on-a-chip: petascale and high-throughput simulations of microfluidics at cell resolution D Rossinelli, YH Tang, K Lykov, D Alexeev, M Bernaschi, P Hadjidoukas, ... Proceedings of the International Conference for High Performance Computing …, 2015 | 38 | 2015 |
| Bayesian uncertainty quantification and propagation for discrete element simulations of granular materials PE Hadjidoukas, P Angelikopoulos, D Rossinelli, D Alexeev, ... Computer Methods in Applied Mechanics and Engineering 282, 218-238, 2014 | 38 | 2014 |
| The ICON-A model for direct QBO simulations on GPUs (version icon-cscs: baf28a514) MA Giorgetta, W Sawyer, X Lapillonne, P Adamidis, D Alexeev, V Clément, ... Geoscientific Model Development 15 (18), 6985-7016, 2022 | 23* | 2022 |
| Mirheo: high-performance mesoscale simulations for microfluidics D Alexeev, L Amoudruz, S Litvinov, P Koumoutsakos Computer Physics Communications 254, 107298, 2020 | 16 | 2020 |
| Hierarchical Bayesian uncertainty quantification for a model of the red blood cell A Economides, G Arampatzis, D Alexeev, S Litvinov, L Amoudruz, ... Physical Review Applied 15 (3), 034062, 2021 | 12 | 2021 |
| Synchronised swimming of two fish G Novati, S Verma, D Alexeev, D Rossinelli, WM van Rees, ... arXiv preprint arXiv:1610.04248, 2016 | 10 | 2016 |
| Global climate simulations at 2.8 km on GPU with the ICON model X Lapillonne, W Sawyer, P Marti, V Clement, R Dietlicher, L Kornblueh, ... EGU2020, 2020 | 3 | 2020 |
| The in-silico lab-on-a-chip D Rossinelli, YH Tang, K Lykov, D Alexeev, M Bernaschi, P Hadjidoukas, ... Proceedings of the International Conference for High Performance Computing …, 2015 | 1 | 2015 |
| Inertial Focusing of Spherical Particles: The Effects of Rotational Motion D Alexeev, S Litvinov, A Economides, L Amoudruz, M Toner, ... arXiv preprint arXiv:2408.09552, 2024 | | 2024 |
| ICON NWP on GPUs M Jacob, D Alexeev, R Dietlicher, V Cherkas, E Germann, F Gessler, ... EMS2022, 2022 | | 2022 |
| Two-Element Keyboard-Block Model Of Megathrust Earthquakes Generation For Central Kurils Y Gabsatarov, I Vladimirova, D Alexeev, L Lobkovsky EGU General Assembly Conference Abstracts, EGU21-305, 2021 | | 2021 |
| Challenges of Running Global Climate Simulations at 2.8 km on GPU with the ICON Model X Lapillonne, W Sawyer, R Dietlicher, L Kornblueh, S Rast, R Schnur, ... AGU Fall Meeting Abstracts 2020, A022-12, 2020 | | 2020 |
| The role of the fault-block structure of the continental margin in the generation of the strongest subduction earthquakes I Vladimirova, Y Gabsatarov, D Alexeev, L Lobkovsky EGU2020, 2020 | | 2020 |
| High Performance Computing For Microfluidics On Graphics Processing Units D Alexeev ETH Zurich, 2019 | | 2019 |
| Towards the Virtual Rheometer: High Performance Computing for the Red Blood Cell Microstructure A Economides, L Amoudruz, S Litvinov, D Alexeev, S Nizzero, ... Proceedings of the Platform for Advanced Scientific Computing Conference, 1-13, 2017 | | 2017 |
| Abstract B04: From modeling to in vivo tracking: a new platform for the design of delivery vectors that exploit tumor microfluidics S Nizzero, S Litvinov, D Alexeev, A Economides, ED Rosa, J Wolfram, ... Cancer Research 77 (2_Supplement), B04-B04, 2017 | | 2017 |
| Blood pressure follower G Novati, S Verma, D Alexeev | | |
Petros KoumoutsakosHarvard UniversityZweryfikowany adres z seas.harvard.edu