Experience & Education

• Participate in scientific collaboration and advance cutting-edge research publication
• Focus on industrialization and transformation of AI engineering capabilities
• Completed two academic papers as first author or co-author, covering DAS fiber-optic sensing and urban vibration source tracking

• Led comprehensive R&D direction and commercialization strategy for company’s urban intelligence portfolio
• Oversaw cross-disciplinary R&D teams (~20 members) spanning geophysics, AI, and urban engineering
• Directed end-to-end development of flagship products: seismic-based traffic monitoring system and seismic-based airport monitoring system
• Managed optimization challenges in multimodal large-scale models for signal separation and recognition
• Coordinated 16+ verification projects across 6 infrastructure categories (bridges, tunnels, highways, dams, slopes, airports)
• Coordinated 7 emergency response deployments for high-profile infrastructure incidents

• Led R&D and commercialization roadmap for next-generation urban safety monitoring systems
• Drove deployment of non-voice intelligent auditory technology in smart transportation and urban safety scenarios
• Led research, development, and deployment of city-scale infrastructure monitoring systems from concept to implementation

• Established foundational geophysical science framework for urban infrastructure monitoring
• Pioneered algorithmic approaches combining seismic inversion theory with real-time signal processing
• Led initial research phases for AI-driven traffic and airport monitoring systems

In my Ph.D. research, I explored the integration of optimal transport theory into geophysical full waveform inversion (FWI), with a particular focus on the Sinkhorn divergence as a robust and scalable objective function. This work represents one of the earliest efforts to apply regularized OT-based distances to the optimization of subsurface models in seismic imaging.

GPX Full Scholarship | Outstanding Thesis

Full National Scholarship | Top 1%

GPA: 3.77/4.00 | Ranking: 1/125 | Outstanding Graduate