| MeltpoolNet: Melt pool characteristic prediction in Metal Additive Manufacturing using machine learning P Akbari, F Ogoke, NY Kao, K Meidani, CY Yeh, W Lee, AB Farimani Additive Manufacturing 55, 102817, 2022 | 115 | 2022 |
| Thermal control of laser powder bed fusion using deep reinforcement learning F Ogoke, AB Farimani Additive Manufacturing 46, 102033, 2021 | 91 | 2021 |
| Graph convolutional networks applied to unstructured flow field data F Ogoke, K Meidani, A Hashemi, AB Farimani Machine Learning: Science and Technology 2 (4), 045020, 2021 | 69* | 2021 |
| Surrogate modeling of melt pool temperature field using deep learning AP Hemmasian, F Ogoke, P Akbari, J Malen, J Beuth, AB Farimani Additive Manufacturing Letters 5, 100123, 2023 | 32* | 2023 |
| High-resolution melt pool thermal imaging for metals additive manufacturing using the two-color method with a color camera AJ Myers, G Quirarte, F Ogoke, BM Lane, SZ Uddin, AB Farimani, ... Additive Manufacturing 73, 103663, 2023 | 31 | 2023 |
| Deep-learned generators of porosity distributions produced during metal Additive Manufacturing OF Ogoke, K Johnson, M Glinsky, C Laursen, S Kramer, AB Farimani Additive Manufacturing 60, 103250, 2022 | 19 | 2022 |
| Inexpensive high fidelity melt pool models in additive manufacturing using generative deep diffusion F Ogoke, Q Liu, O Ajenifujah, A Myers, G Quirarte, J Malen, J Beuth, ... Materials & Design 245, 113181, 2024 | 13 | 2024 |
| Convolutional neural networks for melt depth prediction and visualization in laser powder bed fusion F Ogoke, W Lee, NY Kao, A Myers, J Beuth, J Malen, A Barati Farimani The International Journal of Advanced Manufacturing Technology 129 (7), 3047 …, 2023 | 10 | 2023 |
| AMGPT: A large language model for contextual querying in additive manufacturing A Chandrasekhar, J Chan, F Ogoke, O Ajenifujah, AB Farimani Additive Manufacturing Letters 11, 100232, 2024 | 7 | 2024 |
| ThermoPore: Predicting part porosity based on thermal images using deep learning P Pak, F Ogoke, A Polonsky, A Garland, DS Bolintineanu, DR Moser, ... Additive Manufacturing 95, 104503, 2024 | 4 | 2024 |
| Latent neural PDE solver: A reduced-order modeling framework for partial differential equations Z Li, S Patil, F Ogoke, D Shu, W Zhen, M Schneier, JR Buchanan Jr, ... Journal of Computational Physics 524, 113705, 2025 | 3 | 2025 |
| Deep learning for melt pool depth contour prediction from surface thermal images via vision transformers F Ogoke, P Pak, A Myers, G Quirarte, J Beuth, J Malen, AB Farimani Additive Manufacturing Letters 11, 100243, 2024 | 3 | 2024 |
| Deep Learning based Optical Image Super-Resolution via Generative Diffusion Models for Layerwise in-situ LPBF Monitoring F Ogoke, SK Suresh, J Adamczyk, D Bolintineanu, A Garland, M Heiden, ... arXiv preprint arXiv:2409.13171, 2024 | | 2024 |
| Deep Learning based Super-resolution models for Accelerating Multiphysics Simulations of Laser Powder Bed Fusion F Ogoke, Q Liu, O Ajenifujah, A Barati Farimani APS March Meeting Abstracts 2023, M53. 006, 2023 | | 2023 |
| The Mallat Scattering Transform for Reduced Order Modelling of Partial Differential Equations F Ogoke, M Glinsky, A Barati Farimani APS April Meeting Abstracts 2021, K17. 009, 2021 | | 2021 |
| Inference on spatially unstructured flow fields using Graph Neural Networks F Ogoke, K Meidani, A Hashemi, A Barati Farimani APS Division of Fluid Dynamics Meeting Abstracts, S01. 023, 2020 | | 2020 |
| Direct numerical simulation of rain drop impact on a thin layer of oil over a deep water pool F Ogoke, W Mostert, MJ Thoraval, L Deike APS Division of Fluid Dynamics Meeting Abstracts, C21. 008, 2019 | | 2019 |
