A review of adaptive approaches to MapReduce scheduling in heterogeneous environments. - Nenavath Srinivas Naik; Atul Negi; V. N. Sastry (ICACCI, 2014)

A learning-based mapreduce scheduler in heterogeneous environments. - Nenavath Srinivas Naik; Atul Negi (ICACCI, 2017)

Implementation of telugu speech synthesis system. - Gangala Ramya; Nenavath Srinivas Naik (ICACCI, 2017)

Improving straggler task performance in a heterogeneous MapReduce framework using reinforcement learning. - Nenavath Srinivas Naik; Atul Negi; V. N. Sastry (Int. J. Big Data Intell., 2018)

Prediction of Coronary Heart Disease using Supervised Machine Learning Algorithms. - Divya Krishnani; Anjali Kumari; Akash Dewangan; Aditya Singh; Nenavath Srinivas Naik (TENCON, 2019)

A data locality based scheduler to enhance MapReduce performance in heterogeneous environments. - Nenavath Srinivas Naik; Atul Negi; B. R. Tapas Bapu; R. Anitha (Future Gener. Comput. Syst., 2019)

Early Detection of Forest Fire using Deep Learning. - Medi Rahul; Karnekanti Shiva Saketh; Attili Sanjeet; Nenavath Srinivas Naik (TENCON, 2020)

Energy-aware scheduling using slack reclamation for cluster systems. - Ashish Kumar Maurya; Kashish Modi; Vinay Kumar; Nenavath Srinivas Naik; Anil Kumar Tripathi (Clust. Comput., 2020)

Stroke Prediction Using Machine Learning in a Distributed Environment. - Maihul Rajora; Mansi Rathod; Nenavath Srinivas Naik (ICDCIT, 2021)

Mobilizing Digital Volunteers to Support Underserved Communities in India During COVID-19 Lockdowns. - Devansh Mehta; Vishnu Prasad; Tarun Chitta; Nenavath Srinivas Naik; Amit Prakash; Aditya Vashistha (COMPASS, 2022)

Ensemble multimodal deep learning for early diagnosis and accurate classification of COVID-19. - Santosh Kumar 006; Sachin Kumar Gupta; Vinit Kumar; Manoj Kumar 009; Mithilesh Kumar Chaube; Nenavath Srinivas Naik (Comput. Electr. Eng., 2022)

Privacy preservation and security challenges: a new frontier multimodal machine learning research. - Santosh Kumar 006; Mithilesh Kumar Chaube; Nenavath Srinivas Naik; Sachin Kumar Gupta; Sumit Kumar Tetarave (Int. J. Sens. Networks, 2022)

A Novel Hybrid Model for Predictive Analysis of Myocardial Infarction using Advanced Machine Learning Techniques. - Abhishek Shrivastava; Santosh Kumar 006; Nenavath Srinivas Naik; Tejasv Bhatt (OCIT, 2023)

Enhancing Hadoop Performance with Q-Learning for Optimal Parameter Tuning. - Garika Akshay; Nenavath Srinivas Naik; Jai Vardhan (TENCON, 2023)

Coffee Leaf Disease and Severity Prediction Using Deep Learning. - Harshit Kumar Chaubey; Siri Arelli; Aryan Raj; Nenavath Srinivas Naik (TENCON, 2023)

Reinforcing Security and Usability of Crypto-Wallet with Post-Quantum Cryptography and Zero-Knowledge Proof. - Yathin Kethepalli; Rony Joseph; Sai Raja Vajrala; Jashwanth Vemula; Nenavath Srinivas Naik (CoRR, 2023)

Prediction of dengue fever using supervised machine learning based on hyperparameter tuning and an analysis of the factors influencing dengue spread. - Harshita Mandalika; Manya Rampuria; Nenavath Srinivas Naik (Int. J. Artif. Intell. Soft Comput., 2023)

Detecting and predicting countermeasures against clickjacking. - Aryaman; Nenavath Srinivas Naik; Satyanarayana Vollala; Ruhul Amin 001 (Secur. Priv., 2023)

A decentralised KYC based approach for microfinance using blockchain technology. - Bodicherla Digvijay Sri Sai; Nikhil Ramisetty; Shivangini Prasad; Nenavath Srinivas Naik (Cyber Secur. Appl., 2023)

Automated Disease Detection in Millet Crops Using Deep Learning. - Nenavath Srinivas Naik (MIWAI (2), 2024)

Weed detection and classification in sesame crops using region-based convolution neural networks. - Nenavath Srinivas Naik; Harshit Kumar Chaubey (Neural Comput. Appl., 2024)

Quantum leap in cardiac prognosis: EMIP-cardioPPG's pioneering approach to early myocardial infarction prediction. - Abhishek Shrivastava; Santosh Kumar 006; Nenavath Srinivas Naik (Signal Image Video Process., 2024)

Adaptive Node-Oriented Data Placement for Heterogeneous Hadoop Clusters. - Vishnu Prasad Verma; Santosh Kumar 006; Nenavath Srinivas Naik (IEEE Access, 2025)