Shicong Cao is an architect, engineer, and AI enthusiast working at the intersection of artificial intelligence and the built environment. A licensed architect specializing in healthcare design, she has worked with leading firms such as HDR and Heinlewischer, gaining hands-on experience with complex projects that shape the future of healthcare environments. Since 2021, she has focused on leveraging AI and machine learning to transform architectural workflows and urban design processes.

As Founder & CEO of DataDrivenAEC, Shicong is leading the charge to integrate data and AI into architecture, engineering, and construction (AEC). Her work includes pioneering machine learning models to predict the health impacts of the built environment, as demonstrated in her published research “A POI-Based Machine Learning Method in Predicting Health.” She has developed and deployed a range of AI and machine learning solutions tailored to AEC, such as:

●  A machine learning model to automatically populate BIM parameters, trained on 15,000+ existing doors.
●  Custom data visualization tools for real-time project management.
●  AI-powered knowledge systems, including context-aware chatbots designed to assist architects with complex design and documentation tasks.
●  Automated design evaluation tools that enable performance-based decision-making.

A published researcher in leading computational design conferences, Shicong is committed to promoting data literacy among architects. She is the founder and author of the DataDrivenAEC newsletter, a platform dedicated to exploring the transformative potential of data-driven methods in the AEC industry.

Shicong’s work is driven by a belief that AI and automation can free architects from routine production tasks, enabling them to focus on creating spaces that better serve people. She envisions a future where AEC is a truly user-centered industry, driven by data, empathy, and design excellence.