Amitash Nanda, Md Kamal Hossain Chowdhury, Hannah Ross, and Kevin Gott, “Exploring Dynamic Load Balancing Algorithms for Block-Structured Mesh-and-Particle Simulations in AMReX,” In Practice and Experience in Advanced Research Computing 2025: The Power of Collaboration (PEARC ‘25), ACM, New York, NY, USA, Article 5, 9 pages, July 2025.
Amitash Nanda, Sree Bhargavi Balija, and Debashis Sahoo, “FedNAMs: Performing Interpretability Analysis in Federated Learning Context,” Preprint arXiv:2506.17466, arXiv, June 2025.
Sree Bhargavi Balija, Amitash Nanda, and Debashis Sahoo, “Decoding Federated Learning: The FedNAM+ Conformal Revolution,” Preprint arXiv:2506.17872, arXiv, June 2025.
Mahdi Behroozikhah, Soni Khandelwal, Amitash Nanda, Atishna Samantaray, Arya Prabhudesai, Dharanidhar Dang, Debashis Sahoo, “Expression gradient of cancer suppressor gene using Vision-AI,” Manuscript in Preparation.
Amitash Nanda, Dharanidhar Dang, Sophia Carpinelli, Courtney Tindle, Saptarshi Sinha, Pradipta Ghosh, Debashis Sahoo, “OrgaTuring: Accelerating Organoid Discovery with Vision-AI,” Manuscript in Preparation.
Amitash Nanda, Sree Bhargavi Balija, Debashis Sahoo, “CHAI-KTQ: CHAI-KTQ: A Novel Framework for Scalable LLMs and Efficient Inference,” Manuscript in Preparation.
Amitash Nanda, H M Zabir Haque, Debashis Sahoo, “Leveraging High-Performance Computing for Spatial Transcriptomic Identification of CDX2 Genes in Intestinal Crypts Using Deep Neural Network,” Manuscript in Preparation.
