Research
Interests
My research lies at the intersection of energy storage mechanics, thermofluid sciences, and computational modeling. I develop reduced-order models and multi-scale simulations to understand and optimize next-generation energy systems.
Focus Areas
Current Research Directions
Malware
Learning malware behavior
Web Security
Web Application Vulnerability
Linux Kernel Security
eBPF based ESSTs and malware
Research Statement
Towards Sustainable Energy Storage
My research focuses on developing predictive models for next-generation energy storage systems. By combining physics-based simulations with machine learning, I aim to accelerate the discovery and optimization of materials for batteries and thermal energy storage. Current projects include reduced-order modeling of lithium-ion battery degradation, multi-scale analysis of solid-state electrolytes, and data-driven approaches for thermofluid prediction.