Research

Advanced topology optimization

I develop advanced topology optimization frameworks that push beyond classical linear, single-material designs. I integrate nonlinear mechanics, plasticity, and fracture into physics-based optimization to create structures that remain strong and resilient under extreme deformation and failure. By combining rigorous finite-element modeling with gradient-based optimization and GPU-accelerated computing, I transform topology optimization into a practical design engine for multimaterial, multiscale, and manufacturable systems. My goal is to make high-performance structural design both predictive and accessible.

Metamaterial design and artificial intelligence

I design architected metamaterials whose properties emerge from geometry rather than composition, enabling lightweight, ultra-tough, and programmable mechanical behavior. I couple data-driven learning, physics-informed neural networks, and generative models with simulation-based optimization to rapidly explore vast design spaces. This AI-empowered workflow accelerates discovery while preserving physical interpretability. By integrating machine intelligence with human intuition, I build design tools that help researchers and engineers create materials that were previously unimaginable.

Structural hazard mitigation

I apply my computational design frameworks to improve the safety and resilience of civil and mechanical infrastructure under hazards such as impact and extreme loading. I engineer energy-absorbing and fracture-resistant structures that dissipate damage in a controlled manner, protecting critical components and occupants. By bridging mechanics, optimization, and advanced manufacturing, I translate fundamental research into deployable solutions for safer buildings, vehicles, and protective systems. Ultimately, I aim to design structures that fail gracefully rather than catastrophically.