معرفی
Rucha Bhalchandra Joshi is a Researcher affiliated with the Computation-based Science & Technology Research Center (CaSToRC) at The Cyprus Institute. Her research focuses on advancing machine learning techniques with an emphasis on graph neural networks, privacy-preserving methodologies, and their applications in energy systems and computational science. Joshi’s work bridges theoretical advancements in AI with practical challenges in data privacy, resource optimization, and scalable energy analysis.
Her publications span topics such as adversarial attacks on graph structures, efficient graph representation learning, and privacy mechanisms for sensitive data. She has contributed to innovations like ReconXF for privacy leakage analysis and eBIM-GNN for energy-efficient building analysis. Her research often intersects computational methods with real-world infrastructure challenges.
Joshi’s interdisciplinary approach combines principles from graph theory, cybersecurity, and energy systems engineering. While specific grants or awards are not explicitly noted in the provided materials, her work reflects a commitment to addressing emerging challenges in computational science and privacy-aware AI.
