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About

Dimple Sharma is a researcher specializing in embedded systems, FPGA-based computing, and runtime adaptive architectures, with a particular focus on ensuring the reliability and sustainability of autonomous systems in demanding application domains. Her work addresses critical challenges faced by System-on-Programmable Chip (SoPC) platforms deployed in robotics, aerospace, defense, and autonomous vehicle environments, where dynamic workloads, power constraints, and hardware faults pose significant operational risks. Sharma's most notable contributions center on developing intelligent decision-making frameworks that enable FPGA-based systems to autonomously adapt their structural configurations at runtime. By responding in real time to fluctuations in power budgets, die temperatures, and hardware faults, her methods allow embedded systems to maintain required performance levels without human intervention — a critical capability for mobile autonomous platforms. Her 2018 paper on run-time mitigation of power and fault variations stands as her most recognized work, accumulating 6 citations, while subsequent publications in 2021 extended these ideas to broader sustainability challenges in multimodal workload environments. Though still building her citation footprint, Sharma's research addresses genuinely pressing challenges at the intersection of hardware resilience and autonomous system design, making her work increasingly relevant as embedded intelligence continues to expand into safety-critical industries.