Emily Steiner
TomKat Graduate Fellow for Translational Research
Research Lab: Iro Armeni
Year Awarded: 2025
Emily Steiner is a Ph.D. candidate in Electrical Engineering, advised by Prof. Iro Armeni, in the Gradient Spaces Lab. Her interdisciplinary research focuses on developing 3D and 4D computer vision models to digitize and automate construction progress monitoring, thereby enhancing efficiency, safety, and sustainability. Prior to Stanford, she earned a Bachelor of Applied Science in Mechatronics Engineering from the University of Waterloo, where she completed internships focusing on image and sensor systems. Emily is the Co-Faculty Liaison and Co-Mentorship Chair for the Woman in Electrical Engineering group at Stanford, enjoys volunteering at STEM education outreach programs, and loves cycling and hiking around the Bay.
Website: www.easteine.com
Queryable Spatio-Temporal 4D Representation for Construction Progress Monitoring
The construction industry is one of the most resource-intensive sectors, often resulting in excessive material waste and cost overruns. Despite ongoing digitization efforts, site progress is largely tracked through manual, anecdotal estimates that fail to detect issues or inefficiencies early. This work aims to develop state-of-the-art 3D and 4D computer vision models explicitly designed to address the unique challenges of the construction environment, capturing and automatically extracting meaningful information from 3D scans of on-site conditions at different time points. By integrating these models with user-friendly natural language queries, this holistic, data-driven system aims to enable more proactive decision-making and reduce errors, rework, waste, and environmental impacts through timely interventions. The goal of this work is to develop an automated tool that addresses pressing challenges in construction monitoring and to provide a scalable pathway for real-world adoption in industry, thereby fostering greater resilience and sustainability in future infrastructure projects.