Research Statement

My research focuses on developing intelligent, data-driven methods for smarter and safer infrastructure. I integrate unmanned aerial vehicles (UAVs), computer vision, and artificial intelligence to automate bridge inspection and structural health monitoring (SHM). By combining deep learning, sensing technologies, and data fusion, I aim to transform visual data into actionable insights that support efficient and objective infrastructure management.

In parallel, I work on the design and optimization of architected and multifunctional materials using additive manufacturing, topology optimization, and metaheuristic algorithms. My broader goal is to advance adaptive, high-performance materials and systems that can sense, analyze, and evolve with their environment.

Research Areas

Smart Infrastructure & Structural Health Monitoring

  • UAV-Based Automated Inspection and Damage Detection
  • AI-Driven Structural Health Monitoring
  • Embedded and Self-Powered Sensor Networks
  • Data Fusion and Digital Twins for Infrastructure

Additive Manufacturing & Multifunctional Materials

  • Architected and Cellular Metamaterials
  • Multifunctional and Adaptive Materials
  • AI-Driven Material Design and Characterization

Computational Optimization & Design

  • Topology and Shape Optimization
  • Metaheuristic and Physics-Informed Methods
  • Graph-Theoretical Models for Optimization
  • Multi-Objective and Uncertainty-Aware Design

Current Projects

UAV-Enabled Bridge Deck Inspection

Development of an autonomous bridge inspection framework using UAVs, infrared and RGB imaging, and AI-based defect detection. Funded by the New Mexico Department of Transportation (NMDOT), this project enhances inspection accuracy, safety, and efficiency.

AI-Driven Structural Health Monitoring

Design of deep learning models for crack detection and bridge component segmentation. The project applies computer vision and data fusion to automate condition assessment and support data-driven infrastructure maintenance.

Computational Optimization of Architected Materials

Exploration of lightweight and multifunctional metamaterials through topology optimization, metaheuristic algorithms, and graph-theoretical design. The work aims to enable adaptive and high-stiffness material systems for advanced structural applications.

Research Impact

My research integrates UAVs, AI, and optimization to advance the digitalization of infrastructure inspection and design. These efforts improve the speed, safety, and accuracy of bridge assessment while paving the way for intelligent, data-driven maintenance strategies. In parallel, my work on architected materials contributes to the development of adaptive and efficient structural systems for next-generation engineering solutions.