About

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The Building Informatics and Visualization Lab (biLAB) at NYU Tandon School of Engineering specializes in utilizing an integrated suite of cutting-edge technologies to tackle challenges observed during the design, construction, and operation of urban built environment. The research team endeavors to detect, quantify, and visualize patterns over time, leveraging data obtained from reality capture technologies (e.g., cameras, laser scanners) and embedded sensing. By exploiting the intersection of BIM, AI, robotics, and manufacturing processes, the lab aims to enhance the scalability and efficiency of construction methods, particularly in modular construction contexts. BiLAB pioneers novel solutions for optimization of energy use in urban buildings towards achievement of sustainability goals.

The research team works on information modeling and visualization to quantify the impact of architecture on human experience in the built environment, understand and improve the behaviors of existing/new facilities and civil infrastructure systems for next generation construction, maintenance, and operations. The research team takes advantage of advancements in technology in information modeling and visualization to integrate and provide information that engineers, owners, and facility operators need, at the right level of detail and visual form.

They work on developing information repositories and visualization platforms to better integrate the data captured from sensors and the context under which they operate to get a holistic view of the monitored system/infrastructure for better maintenance and operation.

BiLAB Research Interests:

  • AR/VR
  • BIM and digital twins
  • Computer Vision/AI/ML
  • Data Analytics and visualization
  • Building /Urban Informatics

Research Projects

  • Data-driven Generative design for buildings
  • AI-Assisted Modular Construction
  • Computer Vision enabled Urban Façade Safety and Maintenance
  • BIM and Ontologies in AEC/FM
  • Roadway Worker Safety with Wearables and Virtual Environments
  • Data-driven Building/Urban Energy Efficiency for Sustainable Cities
  • Synchronized Calibration of Multi-Simulators for Transportation Applications
  • AR/VR applications and data visualization in AEC/FM
  • Neuroscience for Architecture and Urban Design

Testbeds utilized: legacy and smart buildings, airports, highways.

Tools utilized: Building information models, data driven methodologies, advanced visualization

The biLab is spearheaded by Prof. Semiha Ergan, Associate Professor of the Department of Civil and Urban Engineering.

Prof. Ergan’s NYU profile

Prof. Ergan on Google Scholar

Prof. Ergan on ResearchGate