| 2025 | COMSNETS | Resource-Aware Monkeypox Diagnosis: Leveraging High-Capacity and Lightweight Models with Knowledge Distillation. | Avi Deb Raha, Mrityunjoy Gain, Sudip Kumar Saha, Md Shohanur Rahman, Apurba Adhikary, Rameswar Debnath, Anupam Kumar Bairagi, Sujit Biswas |
| 2025 | GLOBECOM | Towards Lifelong Vision-Based Beamforming: A Continual Learning-Driven Framework for 6G. | Avi Deb Raha, Mrityunjoy Gain, Girum Fitihamlak Ejigu, Zhu Han, Choong Seon Hong |
| 2024 | NOMS | Transfer Learning Empowered Power Allocation in Holographic MIMO-enabled Wireless Network. | Apurba Adhikary, Avi Deb Raha, Yu Qiao, Seok Won Kang, Choong Seon Hong |
| 2024 | NOMS | Open RAN Embracing Continual Learning: Towards NextG Adaptive Traffic Analysis. | Mrityunjoy Gain, Avi Deb Raha, Apurba Adhikary, Kitae Kim, Choong Seon Hong |
| 2024 | NOMS | Towards Ultra-Reliable 6G: Semantics Empowered Robust Beamforming for Millimeter-Wave Networks. | Avi Deb Raha, Apurba Adhikary, Mrityunjoy Gain, Yu Min Park, Choong Seon Hong |
| 2023 | APNOMS | Transformer-based Communication Resource Allocation for Holographic Beamforming: A Distributed Artificial Intelligence Framework. | Apurba Adhikary, Avi Deb Raha, Yu Qiao, Md. Shirajum Munir, Ki Tae Kim, Choong Seon Hong |
| 2023 | APNOMS | Knowledge Distillation in Federated Learning: Where and How to Distill? | Yu Qiao, Chaoning Zhang, Huy Q. Le, Avi Deb Raha, Apurba Adhikary, Choong Seon Hong |
| 2023 | APNOMS | Segment Anything Model Aided Beam Prediction for the Millimeter Wave Communication. | Avi Deb Raha, Apurba Adhikary, Md. Shirajum Munir, Yu Qiao, Choong Seon Hong |
| 2023 | APNOMS | EFCKD: Edge-Assisted Federated Contrastive Knowledge Distillation Approach for Energy Management: Energy Theft Perspective. | Luyao Zou, Huy Q. Le, Avi Deb Raha, Dong Uk Kim, Choong Seon Hong |
| 2023 | NOMS | Artificial Intelligence Framework for Target Oriented Integrated Sensing and Communication in Holographic MIMO. | Apurba Adhikary, Md. Shirajum Munir, Avi Deb Raha, Yu Qiao, Choong Seon Hong |
| 2023 | NOMS | CDFed: Contribution-based Dynamic Federated Learning for Managing System and Statistical Heterogeneity. | Yu Qiao, Md. Shirajum Munir, Apurba Adhikary, Avi Deb Raha, Choong Seon Hong |