Research-focused modeling Engineer with 10+ years of experience applying advanced machine learning and numerical methods to analog, mixed-signal, and power electronics systems. Expertise in developing graph neural network (GNN) architectures and physics-informed models to accelerate circuit simulation, modeling, and design automation workflows. Skilled in Python and C++ software development, algorithm design and applied mathematics. Experienced in integrating knowledge graphs and heterogeneous GNNs—into EDA-related applications, including circuit topology generation, parameter optimization, and multi-physics modeling for IC design. Authored multiple journal and conference publications on AI-based electric circuit representation and secured competitive research funding for AI-driven circuit generation and datacenter power converter modeling through EDITA and IBM-AIU programs