dr Nora El-Gohary

University of Illinois at Urbana-Champaign
W078 featured speaker

"Together, data and AI open endless opportunities for the built environment."

Nora El-Gohary is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign.

 

Dr. El-Gohary’s research focuses on data analytics and AI for the development and operation of sustainable buildings and infrastructure systems, including information modeling, information extraction, data fusion, machine learning, and big data analytics. Her research has been funded by the National Science Foundation (NSF), Illinois Department of Transportation, Qatar Foundation, and Natural Sciences and Engineering Research Council (NSERC) of Canada among other funding agencies. The outcomes of her research have been published in over 140 journal and conference publications. She has received several research awards including the NSERC’s Discovery Award in 2009, the NSF’s CAREER Award in 2013, the Center of Advanced Study Award in 2015, the National Center for Supercomputing Applications (NCSA) Award in 2018, and the Institute for Sustainability, Energy, and Environment (iSEE) Award in 2019.

 

Dr. El-Gohary currently serves as the Co-Chair of the Transportation Research Board’s Information Systems in Construction Management Subcommittee, the Past Chair of the Executive Committee of the American Society of Civil Engineers (ASCE)’s Computing Division, and the Past Chair of the Executive Committee of the ASCE’s Construction Research Council. She also currently serves as Associate Editor for the ASCE Journal of Computing in Civil Engineering.

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Artificial Intelligence for the Built Environment: Opportunities, Challenges, and the Path Forward

Artificial intelligence (AI) is bringing tremendous opportunities for scientific discovery and efficient operation that leverage data, context, and intelligence for more sustainable and efficient design, construction, operation, and maintenance of buildings and infrastructure systems. Advances in data analytics and AI technologies – including natural language processing and generation, computer vision, and machine learning – offer a new wave of opportunities for turning data into actionable insights, advancing automation, and enabling autonomous operations.  However, the implementation of AI does not come without challenges such as learning from multiple sources of heterogenous data and reaching explainability and generalizability in AI.

 

This keynote will discuss recent research efforts and directions that aim to leverage these opportunities, address these challenges, and advance the science and application of AI in the built environment, including:

  1. Extracting meaningful information from unstructured data sources that have traditionally been difficult to digest and harness;

  2. Aligning and linking data with different representations, in heterogeneous formats, and from multiple sources to move from isolated data to fully-integrated multi-source predictive analytics;

  3. Enabling adaptive and advanced machine learning strategies to address data scarcity and quality challenges; and

  4. Leveraging advanced sensing technologies and robotics to enable data-driven autonomous operations.

 

The keynote will also discuss the path forward towards the next-generation AI, including human-centric AI, convergence approaches, and living AI labs.