P. Choppara and B. Lokesh, “A machine learning approach to genomic task scheduling in fog computing,” in 2025 IEEE 4th International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET), IEEE, 2025, pp. 1–6

P.CHOPPARA and B.LOKESH,“Quantum machine learning for prediction of compound-protein interactions in drug discovery,” in 2024 12th International Conference on Intelligent Systems and Embedded Design (ISED), 2024, pp. 1–6. doi: 10.1109/ISED63599.2024.10956316.

P.Choppara and S. S. Mangalampalli, “Reliability and trust aware task scheduler for cloud-fog computing using advantage actor critic (a2c) algorithm,” IEEE Access, vol. 12, pp. 102126–102145, 2024. doi: 10.1109/ACCESS.2024.3432642

P.Choppara and S.S.Mangalampalli, “A hybrid task scheduling technique in fog computing using fuzzy logic and deep reinforcement learning,” IEEE Access, vol. 12, pp. 176363–176388, 2024. doi: 10.1109/ACCESS.2024.3505546.

P.Choppara and S.Mangalampalli, “An effective analysis on various task scheduling algorithms in fog computing,” EAI Endorsed Transactions on Internet of Things, vol. 10, 2024.

P.Choppara and S.Mangalampalli, “An efficient deep reinforcement learning based task scheduler in cloud-fog environment,” Cluster Computing, vol. 28, no. 1, pp. 1–26, 2025.

P.Choppara and S.S.Mangalampalli, “Resource adaptive automated task scheduling using deep deterministic policy gradient in fog computing,” IEEE Access, vol. 13, pp. 25969–25994, 2025. doi: 10.1109/ACCESS.2025.3539606.

P.Choppara and S.S.Mangalampalli, “Adaptive task scheduling in fog computing using federated dqn and k-means clustering,” IEEE Access, vol. 13, pp. 75466–75492, 2025. doi: 10.1109/ACCESS.2025.3563487

P.Choppara and B.Lokesh, “Q-bafnet: A hybrid quantum classical approach for drug-target binding affinity prediction,” IEEE Transactions on Computational Biology and Bioinformatics, 2025

P.Choppara and B.Lokesh, “Leveraging quantum lstm for high-accuracy prediction of viral mutations,” IEEE Access, vol. 13, pp. 25282–25300, 2025. doi: 10.1109/ACCESS.2025.3539337.

P.Choppara and B.Lokesh, “Efficient task scheduling and load balancing in fog computing for crucial healthcare through deep reinforcement learning,” IEEE Access, vol. 13, pp. 26542–26563, 2025. doi: 10.1109/ACCESS.2025.3539336.

P. Choppara and L. Bommareddy, “Ai-driven protein pocket detection through integrating deep q-networks for structural analysis,” Journal of Computer-Aided Molecular Design, vol. 39, no. 1, p. 90, 2025.