Hoboken, NJ 07030
United States
Stevens Institute of Technology
AI-assisted design of materials; architectured polymer-concrete composite (APCC); high strength and high toughness material; Latin hypercube sampling; Lion Pride Optimization; sequential surrogate modeling
physicochemical variation, solid waste valorization, ultra-high-performance concrete (UHPC), human-computer interaction, interpretable machine learning, knowledge based system
explainable machine learning, interpretable AI, knowledge graph, multi-objective optimization, physicochemical information, ultra-high performance geopolymer (UHPG)
crack monitoring, dense microcrack, generative artificial intelligence (AI), generative adversarial network (HGAN), strain-hardening cementitious composites, vision transformer
crack assessment, distributed fiber optic sensors, interface mechanics, metaheuristic inverse analysis, optical frequency domain reflectometry (OFDR), Structural Health Monitoring
data-driven design, knowledge-data fusion, knowledge discovery, large language model, physicochemical mechanism
alternative binder, data-driven design, knowledge-guided data-driven model, Machine learning, Sustainable construction, Waste Valorization
Computer vision, Crack segmentation, crack pattern transfer, lightweight deep learning model, Stable Diffusion Inpainting, Transfer Learning
Agentic artificial intelligence (AI), material discovery, chloride diffusion, knowledge graph, large language model, physics-based model
