Yu-Chin Chan

data-driven metamaterials design, deep learning, statistical design optimization

I am a Ph.D. student at Northwestern University in the IDEAL group. My interests are an interdisciplinary mix of engineering design, computer vision and graphics, mechanics and materials science, especially applied to metamaterials and additive manufacturing.

(This site is under construction. Please see my LinkedIn for more complete information.)


North Carolina State University
B.S. Mechanical Engineering (Honors)
2011 - 2015
Minor Mathematics
Summa Cum Laude
Northwestern University
Ph.D. Mechanical Engineering
2016 - (2021)
Advisor: Prof. Wei Chen


Paper of Distinction for [Chan, Y. et al., 2020]
Design Automation Conference at ASME IDETC/CIE,
August 2020
Graduate Research Fellowship
National Science Foundation,
April 2018
Predictive Science & Engineering Design Fellowship
Northwestern University,
August 2017
Paper of Distinction [Tao, S. et al., 2017]
Design Automation Conference at ASME IDETC/CIE,
August 2017
Walter P. Murphy Fellowship
Northwestern University,
September 2016


  • Generative Design Intern (Siemens Corporate Technology)
    June - September 2018
    Accelerated topology optimization for large-scale industrial problems (US Patent Pending); implemented as Python software.


  • METASET: An Automated Data Selection Method for Scalable Data-Driven Design of Metamaterials
    Design Automation Conference at ASME IDETC/CIE ,August 18, 2020.
  • A Spectral Shape Descriptor Based Approach for Data-Driven Metamaterials Design Optimization
    15th U.S. National Congress on Computational Mechanics , Austin, TX, July 29, 2019.



Data-Driven Metamaterials Design

Data-driven design and topology optimization of multi-scale metamaterials using deep learning and reduced geometric representations.