| 2025 | ICMLA | Out-of-the-Box Uncertainty: Reducing Confident Errors with Dirichlet Classifiers. | Courtney Franzen, Farhad Pourkamali-Anaraki |
| 2025 | ICMLA | Kolmogorov-Arnold Networks in Low-Data Regimes: A Comparative Study with Multilayer Perceptrons. | Farhad Pourkamali-Anaraki |
| 2023 | CoDIT | Evaluating Regression Models with Partial Data: A Sampling Approach. | Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili |
| 2023 | ICMLA | Advancing Precision Medicine: An Evaluative Study of Feature Selection Methods. | Carol M. Kiekhaefer, Farhad Pourkamali-Anaraki |
| 2022 | ICIP | D-CBRS: Accounting for Intra-Class Diversity in Continual Learning. | Yasin Findik, Farhad Pourkamali-Anaraki |
| 2021 | ICMLA | An Empirical Evaluation of the t-SNE Algorithm for Data Visualization in Structural Engineering. | Parisa Hajibabaee, Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili |
| 2020 | ICMLA | Kernel Ridge Regression Using Importance Sampling with Application to Seismic Response Prediction. | Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Lydia Morawiec |
| 2018 | AAAI | Randomized Clustered Nystrom for Large-Scale Kernel Machines. | Farhad Pourkamali-Anaraki, Stephen Becker, Michael B. Wakin |
| 2014 | ICASSP | Efficient recovery of principal components from compressive measurements with application to Gaussian mixture model estimation. | Farhad Pourkamali-Anaraki, Shannon M. Hughes |
| 2014 | ICML | Memory and Computation Efficient PCA via Very Sparse Random Projections. | Farhad Pourkamali-Anaraki, Shannon M. Hughes |
| 2013 | ICASSP | Compressive K-SVD. | Farhad Pourkamali-Anaraki, Shannon M. Hughes |
| 2013 | ICIP | Kernel compressive sensing. | Farhad Pourkamali-Anaraki, Shannon M. Hughes |