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Runjia Tian: Enactive Genesis: Toward Generative Architecture with Human-Centric AI


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Enactive Genesis: Toward generative architecture

with human-centric artificial intelligence




Runjia Tian

Master of Design Studies, Harvard GSD




Runjia Tian holds a Master degree in Design Studies, Technology from Harvard Graduate School of Design (GSD) and a Bachelor in Architecture from Harbin Institue of Technology. Currently, he is an AR Effect Engineer at TikTok, working on TikTok’s AR Effect Platform, Effect House.


Prior to joining TikTok, Runjia worked at Generative Design Group at Autodesk Boston and Harvard Map of Inclusive Place and Symbols. At Harvard GSD, Runjia's research has been supported by Harvard Joint Center for Housing studies student research support grant, MDes Research and Development Award, Harvard Graduate School of Design Summer Research Grant and MIT designX. Runjia has authored/co-authored several peer-reviewed publications on architecture, urban design, and technology in international conferences such as NeurIPS, ACADIA, eCAADe, CAADRIA and CDRF and hosted several workshops on AI and architecture for ACADIA and DigitalFUTURES.


Abstract

Artificial intelligence (AI) algorithms are gaining increasing popularity in the domain of architecture, urban design, and landscape architecture. However, most of the recent generative design workflows using image-based AI, such as generative adversarial neural networks, do not incorporate human-centric evaluation metrics and are prone to potential bias embedded in the dataset researchers used to train AI agents. Moreover, the outcomes of such approaches are pixelated images that are not directly useable in real-world scenarios. Inspired by enactive learning in developmental psychology, the machine learning community has developed increasingly powerful AI agents that learn emergent behavior through unsupervised and reinforcement learning approaches such as self-play or actor-critic that do not rely on human heuristic datasets. Therefore, I propose Enactive Genesis, a novel environment to train generative architecture AI agents through reinforcement learning and human-centric evaluation metrics. The environment is composed of three open-source Software Development Kits (SDK), each comprising a novel and foundational infrastructure towards general and human-centric AI in generative architecture design.



 

Host

Wei Wu


Wei Wu is a designer and computational artist with a Master's degree in Design Studies from Harvard University Graduate School of Design. She operates at the intersection of design and emerging technologies, producing work that encompasses robotic installations, interactive media art, and extended reality design.

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