My Research Featured in Dr. Yi Bao's Presentation at RCR Journal Webinar

I am thrilled to announce that my Ph.D. advisor, Dr. Yi Bao, presented our collaborative research on AI-assisted design of low-carbon cost-effective concrete at the monthly webinar hosted by the prestigious journal, Resources, Conservation and Recycling. Below is the embedded YouTube video of Dr. Yi Bao's presentation:

Our publications focus on novel AI-integrated design methodologies to revolutionize the design and development of cementitious composites. A portion of Dr. Bao's presentation was dedicated to two of our recent papers published in Resources, Conservation and Recycling:

• The first paper, titled “Deep Learning from Physicochemical Information of Concrete with an Artificial Language for Property Prediction and Reaction Discovery” (Volume 190, March 2023), is a result of our team's diligent efforts to create an artificial language to represent complex concrete mixtures. Through this research, we were able to configure deep learning models automatically, assess the importance of variables, discover chemical reactions, and predict the mechanical properties of concrete with high accuracy. Our approach paves the way for a deeper understanding of complex concrete mixtures and the development of low-carbon, cost-effective concrete. Read the full paper here.

  
  

  
  

• The second paper, titled “AI-guided auto-discovery of low-carbon cost-effective ultra-high performance concrete (UHPC)” (Volume 189, February 2023), is another milestone in our journey towards sustainable construction practices. Our AI-guided approach automates data augmentation, machine learning model generation, and mixture selection, optimizing the mechanical properties, carbon footprint, and costs of ultra-high performance concrete (UHPC). Our use of evolutionary many-objective optimization led to the discovery of new UHPC mixtures with significantly reduced carbon footprints, embodied energy, and material costs. Read the full paper here.