| Pretrained language models are symbolic mathematics solvers too! K Noorbakhsh, M Sulaiman, M Sharifi, K Roy, P Jamshidi arXiv preprint arXiv:2110.03501, 2021 | 34 | 2021 |
| Counterfactual Temporal Point Processes K Noorbakhsh, MG Rodriguez Advances in Neural Information Processing Systems (NeurIPS), 2022 | 29 | 2022 |
| LPF-Defense: 3D Adversarial Defense based on Frequency Analysis H Naderi, K Noorbakhsh, A Etemadi, S Kasaei PLOS ONE 18 (2), 1-19, 2023 | 16 | 2023 |
| m3: Accurate Flow-Level Performance Estimation using Machine Learning C Li, A Nasr-Esfahany, K Zhao, K Noorbakhsh, P Goyal, M Alizadeh, ... Proceedings of the ACM SIGCOMM 2024 Conference, 813–827, 2024 | 12 | 2024 |
| Glia: A Human-Inspired AI for Automated Systems Design and Optimization P Hamadanian, P Karimi, A Nasr-Esfahany, K Noorbakhsh, J Chandler, ... arXiv preprint arXiv:2510.27176, 2025 | 4 | 2025 |
| Savaal: Scalable Concept-Driven Question Generation to Enhance Human Learning K Noorbakhsh, J Chandler, P Karimi, M Alizadeh, H Balakrishnan arXiv preprint arXiv:2502.12477, 2025 | 4 | 2025 |
| Vision models can be efficiently specialized via few-shot task-aware compression D Kuznedelev, S Tabesh, K Noorbakhsh, E Frantar, S Beery, E Kurtic, ... arXiv preprint arXiv:2303.14409, 2023 | 4 | 2023 |
| Pre-trained language transformers are universal image classifiers R Goel, M Sulaiman, K Noorbakhsh, M Sharifi, R Sharma, P Jamshidi, ... arXiv preprint arXiv:2201.10182, 2022 | 3 | 2022 |
| Scaling Automatic Question Generation to Large Documents: A Concept-Driven Approach K Noorbakhsh Massachusetts Institute of Technology, 2025 | | 2025 |
| TACO Vision Models Can Be Efficiently Specialized via Few-Shot Task-Aware Compression D Kuznedelev, S Tabesh, K Noorbakhsh, E Frantar, S Beery, E Kurtic, ... Transactions on Machine Learning Research, 0 | | |
Pooyan JamshidiAssociate Professor, University of South Carolina, ex-GoogleVerified email at cse.sc.edu
