| 2026 | EACL | Language Model-Driven Data Pruning Enables Efficient Active Learning. | Abdul Hameed Azeemi, Ihsan Ayyub Qazi, Agha Ali Raza |
| 2025 | COLING | To Label or Not to Label: Hybrid Active Learning for Neural Machine Translation. | Abdul Hameed Azeemi, Ihsan Ayyub Qazi, Agha Ali Raza |
| 2024 | ACL | Deepfake Defense: Constructing and Evaluating a Specialized Urdu Deepfake Audio Dataset. | Sheza Munir, Wassay Sajjad, Mukeet Raza, Emaan Abbas, Abdul Hameed Azeemi, Ihsan Ayyub Qazi, Agha Ali Raza |
| 2024 | EMNLP | Generalists vs. Specialists: Evaluating Large Language Models for Urdu. | Samee Arif, Abdul Hameed Azeemi, Agha Ali Raza, Awais Athar |
| 2023 | EMNLP | Data Pruning for Efficient Model Pruning in Neural Machine Translation. | Abdul Hameed Azeemi, Ihsan Ayyub Qazi, Agha Ali Raza |
| 2023 | Interspeech | Self-Supervised Dataset Pruning for Efficient Training in Audio Anti-spoofing. | Abdul Hameed Azeemi, Ihsan Ayyub Qazi, Agha Ali Raza |
| 2022 | Interspeech | Dataset Pruning for Resource-constrained Spoofed Audio Detection. | Abdul Hameed Azeemi, Ihsan Ayyub Qazi, Agha Ali Raza |