Research activities focus on wave-equation-constrained computational electrodynamics and device-level modeling within integrated nanophotonics. The central methodology bridges classical Maxwell field theory and fabricable integrated optical components through rigorous full-wave electromagnetic simulation, coupled-mode analysis, and physics-informed computational frameworks. The primary objective is establishing open, reproducible simulation workflows that map structural geometric parameters directly to optical, electrical, and quantum behavior.
Investigation spans three primary physical domains: integrated active nanophotonics, nonlinear quantum photonics, and physics-informed neural surrogates. Work in active nanophotonics examines field-guided optical modes interacting with anisotropic material tensors in bound-state-in-the-continuum metasurfaces and resonant cavity geometries. In quantum photonics, research targets the synthesis of entangled photon-pair sources via spontaneous parametric down-conversion in anisotropic waveguides, optimizing modal phase-matching and joint spectral characteristics for quantum state generation.
To overcome computational bottlenecks inherent in iterative full-wave simulations, physics-informed neural networks and operator architectures are combined with exact differential equation formulations, yielding fast surrogate solvers for gradient-based inverse design. Academic training includes the MAOT program at FAU Erlangen-Nürnberg and a B.Sc. from Alexandria University, alongside research at the Max Planck School of Photonics and IMRE, A*STAR.
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