S. Chandra Mouli

This researcher's recent work focuses on wireless sensor networks (WSNs), particularly energy-efficient designs such as optimizing how sensor 'clusters' are formed and how a lead node ('cluster head') is chosen to save power, using methods like reinforcement learning, machine learning-based clustering, and nature-inspired optimization algorithms (e.g., firefly, cuttlefish-inspired search methods). Related work touches on federated learning (a way to train machine learning models across many devices without centralizing data) applied to IoT networks, and blockchain network connectivity. Earlier and more varied publications include topics like engineering failure analysis and environmental sustainability policy, suggesting a broadening or shift in focus over time toward networked systems and machine learning applications.

Publication output has grown notably in the last two years (2024-2025), following a more modest and variable pace of 1-4 papers per year in the preceding years of the decade.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026