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BACK
BACK
Xinwei Zhuang

Xinwei Zhuang

Ph.D. Student - Architecture
Email
xinwei_zhuang@berkeley.edu
Website(s)
xinwei-zhuang.github.io
Website(s)
https://xinwei-zhuang.github.io./
Email
xinwei_zhuang@berkeley.edu

SPECIALIZATIONS

With an interdisciplinary background, Xinwei focuses her research on performance-driven design. She integrates machine learning into the design process, aiming to enhance environmental sustainability and energy resilience in urban landscapes.

EDUCATION
B.S. in Civil Engineering, Edinburgh Napier University
M.S. in Architectural Computation, University College London

BIOGRAPHY

Xinwei Zhuang is a PhD student at the Department of Architecture, UC Berkeley, with a designated emphasis on new media. She is a member of the XR lab and Center for the Built Environment (CBE). Xinwei is seeking to weave together the realms of architecture and urban design with energy resilience. Her doctoral research focuses on energy resilience and sustainability, data-informed design, and machine learning-aid generative design and optimization. Xinwei worked as both a researcher and an architect, and served as a research assistant at Lawrence Berkeley National Lab, working on simulation, data analysis, and visualization for estimating the energy and carbon impacts of various energy conservation measures.

COURSES TAUGHT

Graduate Student Instructor:

  • ARCH 140 – Energy and Environment
  • ARCH 150 – Introduction to Structures
  • ARCH 240 – Advanced Study of Energy and Environment

AWARDS & RECOGNITION

Golden Gate Chapter Scholarship, 2021
Eric T. Andresen Memorial Scholarship, 2023

Publications

(* denotes equal contribution)
Zhuang X.*, Huang Z.*, Zeng W. and Caldas L. (2023) MARL: Multi-scale Archetype Representation Learning for Urban Building Energy Modeling, workshop on Computer Vision Aided Architectural Design (CVAAD), at International Conference on Computer Vision (ICCV), Paris, France.
Zhuang X.*, Huang Z.*, Zeng W. and Caldas L. (2023) Encoding Urban Ecologies: Automated Building Archetype Generation through Self-Supervised Learning for Energy Modeling, in 2023 Conference on Association for Computer Aided Design in Architecture (ACADIA), Denver, United States of America.
Zhuang X., Luo N., Hong, T. and Koenig M. (2023) "What can we learn from Honda Smart Home with high-resolution monitored performance data: A zero-net energy home in California," 18th International IPBSA Conference and Exhibition, Building Simulation 2023, Shanghai, China.
Li F.* and Zhuang X.*(2023). "Infomorphism: Integrating An Auto decoder-based generative model maximizing solar accessibility for local energy networks," 18th International IPBSA Conference and Exhibition, Building Simulation 2023, Shanghai, China.
Zhuang X., Ju Y., Yang, A. and Caldas L. (2023) "Synthesis and Generation for 3D Architecture Volume with Generative Modeling," in International Journal of Architecture Computing, Vol. 21, Issue 2: AI, Architecture, Accessibility, & Data Justice.
Zhuang X.(2022) "Rendering sketches: Interactive rendering generation from sketches using conditional generative adversarial neural network, in 40th Education and research in Computer Aided Architectural Design in Europe. Ghent, Belgium vol. 1, p. 517-524.
Zhuang X. and Caldas L. (2022) "Prediction of Ventilation Performance in Urban Area with CFD Simulation and Conditional Generative Adversarial Networks," in proceedings of the 5th International Conference on Building Energy and Environment. COBEE 2022. Environmental Science and Engineering. Springer, Singapore., p. 129–138.
Zhuang X. and Hanna S. (2020) "Space Frame Optimisation with Spectral Clustering," in International Journal of Machine Learning and Computing vol. 10, no. 4, pp. 507-512.

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