Ultra-Wideband Channel Modeling for Hurricanes. - Wahab Khawaja; Ismail Güvenç; Arindam Chowdhury (VTC Fall, 2017)

Deep Reader: Information Extraction from Document Images via Relation Extraction and Natural Language. - Vishwanath D; Rohit Rahul; Gunjan Sehgal; Swati; Arindam Chowdhury; Monika Sharma; Lovekesh Vig; Gautam Shroff; Ashwin Srinivasan 001 (ACCV Workshops, 2018)

Reading Industrial Inspection Sheets by Inferring Visual Relations. - Rohit Rahul; Arindam Chowdhury; Animesh; Samarth Mittal; Lovekesh Vig (ACCV Workshops, 2018)

An Efficient End-to-End Neural Model for Handwritten Text Recognition. - Arindam Chowdhury; Lovekesh Vig (BMVC, 2018)

ChartNet: Visual Reasoning over Statistical Charts using MAC-Networks. - Monika Sharma; Shikha Gupta; Arindam Chowdhury; Lovekesh Vig (IJCNN, 2019)

Efficient Power Allocation Using Graph Neural Networks and Deep Algorithm Unfolding. - Arindam Chowdhury; Gunjan Verma; Chirag Rao; Ananthram Swami; Santiago Segarra (ICASSP, 2021)

ML-aided power allocation for Tactical MIMO. - Arindam Chowdhury; Gunjan Verma; Chirag Rao; Ananthram Swami; Santiago Segarra (MILCOM, 2021)

GIST: Distributed Training for Large-Scale Graph Convolutional Networks. - Cameron R. Wolfe; Jingkang Yang; Arindam Chowdhury; Chen Dun; Artun Bayer; Santiago Segarra; Anastasios Kyrillidis (CoRR, 2021)

Unfolding WMMSE Using Graph Neural Networks for Efficient Power Allocation. - Arindam Chowdhury; Gunjan Verma; Chirag Rao; Ananthram Swami; Santiago Segarra (IEEE Trans. Wirel. Commun., 2021)

Label Propagation Across Graphs: Node Classification Using Graph Neural Tangent Kernels. - Artun Bayer; Arindam Chowdhury; Santiago Segarra (ICASSP, 2022)

Stability Analysis of Unfolded WMMSE for Power Allocation. - Arindam Chowdhury; Fernando Gama; Santiago Segarra (ICASSP, 2022)

Learning Non-myopic Power Allocation in Constrained Scenarios. - Arindam Chowdhury; Santiago Paternain; Gunjan Verma; Ananthram Swami; Santiago Segarra (ACSSC, 2023)

Automatic Detection of COVID-19 from Chest X-ray Images Using Deep Learning Model. - Alloy Das; Rohit Agarwal; Rituparna Singh; Arindam Chowdhury; Debashis Nandi (CoRR, 2024)

Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks. - Arindam Chowdhury; Gunjan Verma; Ananthram Swami; Santiago Segarra (IEEE Trans. Wirel. Commun., 2024)

GIST: distributed training for large-scale graph convolutional networks. - Cameron R. Wolfe; Jingkang Yang; Fangshuo Liao; Arindam Chowdhury; Chen Dun; Artun Bayer; Santiago Segarra; Anastasios Kyrillidis (J. Appl. Comput. Topol., 2024)

Deep Quasi-Recurrent Self-Attention With Dual Encoder-Decoder in Biomedical CT Image Segmentation. - Rohit Agarwal; Arindam Chowdhury; Rajib Kumar Chatterjee; Haradhan Chel; Chiranjib Murmu; Narayan Murmu; Debashis Nandi (IEEE J. Biomed. Health Informatics, 2024)

Rim learning framework based on TS-GAN: A new paradigm of automated glaucoma screening from fundus images. - Arindam Chowdhury; Ankit Lodh; Rohit Agarwal; Rahul Garai; Ahana Nandi; Narayan Murmu; Sumit Banerjee; Debashis Nandi (Comput. Biol. Medicine, 2025)

Exploring the Capabilities of the Frontier Large Language Models for Nuclear Energy Research. - Ahmed Almeldein; Mohammed Alnaggar; Rick Archibald; Tom Beck; Arpan Biswas; Rike Bostelmann; Wes Brewer; Chris Bryan; Christopher Calle; Cihangir Celik; Rajni Chahal; Jong Youl Choi; et al. (CoRR, 2025)