FANG (FRANK) SUN



• Fang (Frank) Sun graduated with a Bachelor of Science in Architecture degree from the University of Virginia, distinguished by an insatiable enthusiasm for the intersection of architecture, artificial intelligence, and digital fabrication.

• After completing a four-year program and a year of practical experience, he has immersed himself in developing sustainable and resilient design solutions through robotics and digital fabrication. With a minor in computer science, he explores AI, computational methodologies, and adaptive modeling.

• His current work focuses on rapid housing reconstruction for natural disasters, utilizing 3D printing, robotics, and automation to enhance efficiency, optimize material usage, and improve structural resilience.

• Now pursuing dual master’s degrees in Architecture and Science in Design: Robotics and Autonomous Systems (RAS) at the University of Pennsylvania, he continues to blend technical expertise, creative vision, and innovation to advance digital fabrication and resilient design, while currently working as a Research Assistant in the Polyhedral Structures Laboratory (PSL).



                   Click below to learn more about FRANK
           ARCHITECTURE EXPERIENCE
    RESEARCH & TEACHING EXPERIENCE
       COMPUTER SCIENCE EXPERIENCE
                 LEADERSHIP EXPERIENCE
                SERVICE EXPERIENCE



Design Skills
>5 YEARs
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>3 YEARs
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>1 YEAR
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Maya ■ ■ ■ □ □



Program Skills
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Arduino ■ ■ ■ ■ ■



03 Concrete 3D-Printed Flooring Structure — Exploring Architectural Growth with Discrete Design
Research Team Work (PSL)
Spring 2025 - Fall 2025 This research project explores the integration of computational design, robotic fabrication, and structural engineering in large-scale additive manufacturing. The study develops an optimized toolpath logic for 3D-printed concrete floor systems combined with post-tensioning to enhance structural efficiency and material performance.

Parametric workflows were used to generate fabrication-aware geometries, while physical prototyping and strength testing validated the relationship between toolpath design, load distribution, and crack control. The project culminated in the construction and exhibition of scaled structural models and was co-published at the ACM Symposium on Computational Fabrication (SCF 2025).