| 2025 | HPDC | On Optimizing Checkpoint Restoration for HPC Applications: Leveraging Merkle Trees and Asynchronous I/O. | Zackary Malkmus, Nigel Tan, Ian Lumsden, Kevin Assogba, M. Mustafa Rafique, Bogdan Nicolae, Michela Taufer |
| 2025 | NAACL | Bayelemabaga: Creating Resources for Bambara NLP. | Allahsera Auguste Tapo, Kevin Assogba, Christopher M. Homan, M. Mustafa Rafique, Marcos Zampieri |
| 2024 | Middleware | Towards Affordable Reproducibility Using Scalable Capture and Comparison of Intermediate Multi-Run Results. | Nigel Tan, Kevin Assogba, Walter J. Ashworth, Befikir Bogale, Franck Cappello, M. Mustafa Rafique, Michela Taufer, Bogdan Nicolae |
| 2023 | CLUSTER | PredictDDL: Reusable Workload Performance Prediction for Distributed Deep Learning. | Kevin Assogba, Eduardo Lima, M. Mustafa Rafique, Minseok Kwon |
| 2023 | HiPC | Optimizing the Training of Co-Located Deep Learning Models Using Cache-Aware Staggering. | Kevin Assogba, Bogdan Nicolae, M. Mustafa Rafique |
| 2023 | SC | Asynchronous Multi-Level Checkpointing: An Enabler of Reproducibility using Checkpoint History Analytics. | Kevin Assogba, Bogdan Nicolae, Hubertus Van Dam, M. Mustafa Rafique |
| 2022 | CCGRID | On Realizing Efficient Deep Learning Using Serverless Computing. | Kevin Assogba, Moiz Arif, M. Mustafa Rafique, Dimitrios S. Nikolopoulos |
| 2022 | ICPP | Exploiting CXL-based Memory for Distributed Deep Learning. | Moiz Arif, Kevin Assogba, M. Mustafa Rafique, Sudharshan Vazhkudai |
| 2022 | SC | Canary: Fault-Tolerant FaaS for Stateful Time-Sensitive Applications. | Moiz Arif, Kevin Assogba, M. Mustafa Rafique |