A New Chat Solution for Shared Services using Natural Language Processing Models. - M. Saravanan; Satheesh K. Perepu; Sudipta Bose (ICON, 2018)

Exploring Collective Behavior of Internet of Robotic Things for Indoor Plant Health Monitoring. - M. Saravanan; Satheesh K. Perepu; Amit Sharma (IOTAIS, 2018)

Focusing Social Media Based Analytics for Plant Diseases in Smart Agriculture. - M. Saravanan; Satheesh K. Perepu (MISNC, 2018)

Realizing Social-Media-Based Analytics for Smart Agriculture. - M. Saravanan; Satheesh K. Perepu (Rev. Socionetwork Strateg., 2019)

Online Estimation of Missing Data Using Sparse Optimization Techniques With Applications to Classical Control. - Satheesh K. Perepu; Arun K. Tangirala (IEEE Trans. Control. Syst. Technol., 2019)

CDDM: A method to detect and handle Concept Drift in Dynamic Mobility Model for seamless 5G Services. - Satheesh K. Perepu; Kaushik Dey (GLOBECOM (Workshops), 2020)

Reinforcement Learning based dynamic weighing of Ensemble Models for Time Series Forecasting. - Satheesh K. Perepu; Bala Shyamala Balaji; Hemanth Kumar Tanneru; Sudhakar Kathari; Vivek Shankar Pinnamaraju (CoRR, 2020)

Resource-Constrained Federated Learning with Heterogeneous Labels and Models. - Gautham Krishna Gudur; Bala Shyamala Balaji; Satheesh K. Perepu (CoRR, 2020)

Federated Learning with Heterogeneous Labels and Models for Mobile Activity Monitoring. - Gautham Krishna Gudur; Satheesh K. Perepu (CoRR, 2020)

Intelligent Question Answering using Knowledge Representation for Managed Services. - M. Saravanan; Satheesh K. Perepu (COMAD/CODS, 2021)

Zero-Shot Federated Learning with New Classes for Audio Classification. - Gautham Krishna Gudur; Satheesh Kumar Perepu (Interspeech, 2021)

DSDF: An approach to handle stochastic agents in collaborative multi-agent reinforcement learning. - Satheesh K. Perepu; Kaushik Dey (CoRR, 2021)

Optimize Next State Prediction in Safe RL for 5G Ecosystem. - Satheesh K. Perepu; M. Saravanan (COMSNETS, 2022)

Intent-based multi-agent reinforcement learning for service assurance in cellular networks. - Satheesh K. Perepu; Jean P. Martins; Ricardo Souza S; Kaushik Dey (GLOBECOM, 2022)

A novel unsupervised method for root cause analysis of anomalies using sparse optimization techniques. - Satheesh K. Perepu; Vivek Shankar Pinnamaraju (ICSC, 2022)

Multi-agent reinforcement learning for intent-based service assurance in cellular networks. - Satheesh K. Perepu; Jean P. Martins; Ricardo Souza S; Kaushik Dey (CoRR, 2022)

Domain Adaptation of Reinforcement Learning Agents based on Network Service Proximity. - Kaushik Dey; Satheesh K. Perepu; Pallab Dasgupta; Abir Das (NetSoft, 2023)

Goals are Enough: Inducing AdHoc Cooperation Among Unseen Multi-Agent Systems in IMFs. - Kaushik Dey; Satheesh K. Perepu; Abir Das (CCNC, 2024)

DSDF: Coordinated look-ahead strategy in multi-agent reinforcement learning with noisy agents. - Satheesh Kumar Perepu; Kaushik Dey; Abir Das (COMAD/CODS, 2024)

Towards Adaptive Networks - Generalized utility functions in Multi-Agent Frameworks. - Kaushik Dey; Satheesh K. Perepu; Abir Das; Pallab Dasgupta (NetSoft, 2024)

Towards Adaptive IMFs - Generalization of utility functions in Multi-Agent Frameworks. - Kaushik Dey; Satheesh K. Perepu; Abir Das; Pallab Dasgupta (CoRR, 2024)

Advanced Machine Learning Framework for Efficient Plant Disease Prediction. - Aswath Muthuselvam; S. Sowdeshwar; M. Saravanan; Satheesh K. Perepu (CoRR, 2024)

FedLabeling: A Federated Framework for Handling Noisy Labeled Data for Efficient Alarm Detection. - Satheesh K. Perepu; M. Saravanan (COMSNETS, 2025)