Xkool | AIGC Workflow on AI-generative images

Instructors: Xiaodi Yang / Peiwen Li / Liangyi Murong / Xudong Liu / Shengzhan Xu / Chi Wai Yuen

Dates: July 24, July 25, July 26, July 27, July 29

Total Hours: 12 hours

Themes: Artificial Intelligence / Space Architecture

Software: Cloud AIGC platform,account will be provided during the course

Number of Students: 40

Workshop full, please refer to the live stream to audit.


The Xkool | AIGC Workflow on AI-generative images offers a unique opportunity for architects, designers, and enthusiasts to delve into the realm of AI generative art and its applications in architectural design. Workshop invites participants to dive into the fascinating world of artificial intelligence and its potential to generate unique and captivating visual architectural drawings. This immersive workshop combines the power of artificial intelligence and the creative vision of participants to push the boundaries of architectural expression. Led by experts in both AI and architecture, this workshop aims to inspire, educate, and empower participants to leverage AI generative techniques to create visually stunning and innovative architectural designs.

Prior knowledge of programming fundamentals, particularly in Python, is beneficial for participants attending the AI Generative Images Workshop. While not mandatory, understanding variables, loops, conditionals, and functions will help with grasping technical aspects. The workshop caters to different skill levels, ensuring hands-on sessions and discussions benefit all attendees.

Workshop Objectives:

●Introduce participants to the concept of AI generative art and its potential in architectural design.

●Explore the fusion of art and architecture, emphasizing the role of AI in pushing creative boundaries.

●Familiarize participants with AI generative tools, algorithms, and frameworks applicable to architectural design.

●Encourage experimentation and exploration of AI-generated architectural forms, patterns, and aesthetics.

●Foster collaboration and knowledge sharing among participants to enhance their understanding and skills in AI generative architectural design.

Learning Outcomes:

●Understand the principles and techniques of AI generative art as applied to architectural design.

●Gain knowledge of various AI algorithms and frameworks used for generating architectural forms and patterns

●Acquire practical skills to use lookX.ai platform for creating unique architectural designs.

●Explore the integration of AI-generated elements into architectural projects, enhancing creativity and innovation.

●Collaborate with peers to develop AI-generated architectural design concepts and solutions.


The AI Generative Images in Architectural Design Workshop offers a dynamic and immersive learning experience where participants explore the fusion of art and architecture through AI generative techniques. The workshop activities are designed to introduce participants to AI generative art in architecture, familiarize them with AI generative algorithms and tools, and foster collaboration and experimentation. Here is a summary of the workshop activities: Introduction to AI Generative Art in Architecture:

●Explore the relationship between art, technology, and architecture.

●Showcase inspiring examples of AI-generated architectural forms. Understanding AI Generative Algorithms for Architecture:

●Overview of AI generative algorithms

●Examine how these algorithms generate diverse architectural designs. AI Generative Tools and Platforms lookX.ai for Architectural Design:

●Hands-on practice sessions. Customizing AI Generative Models for Architectural Design:

●Learn methods to customize and fine-tune AI generative models.

●Experiment with design parameters and input constraints. Collaborative Design Project: AI Generative Architecture:

●Form groups and develop collaborative AI generative design projects.

●Receive mentoring and guidance from instructors. Guest Speaker Session: AI in Architectural Practice:

●Learn from expert architects integrating AI in their practice.

●Discuss real-world applications and future implications. Design Showcase and Closing Ceremony:

●Present collaborative projects to the workshop community.

●Appreciate participants’ efforts and distribute certificates. Throughout the workshop, participants engage in discussions, hands-on exercises, critiques, and collaborative activities to enhance their understanding and skills in AI generative architectural design.

Detail Schedule :

Day 1: July 24 10-12 2hrs, CEST time – Session 1: Introduction to AI Generative Art Session 2: Understanding AI Algorithms Session 3: Hands-on Session: Xkool AI Generative Platforms

Day 2: July 25 10-13 3hrs, CEST time – Session 1: Advanced AI Generative Techniques Session 2: Hands-on Session: Customizing AI Generative Models Session 3: Critique and Feedback

Day 3: July 26 10-13 3hrs, CEST time – Session 1: Ethical Considerations in AI Generative Art Session 2: Exploring Datasets and Training AI Models Session 3: Collaborative Project: AI Generative Art Showcase

Day 4: July 27 10-12 2hrs, CEST time – Q & A

Day 5: July 29 10-12 2hrs, CEST time – Session 1: Finalizing Collaborative Projects Session 2: Project Showcase and Closing Ceremony


Xiaodi Yang

Yang Xiaodi, co-founder of Xkool Tech, COO, Bachelor of Architecture, Chongqing University and Master of Architecture, Berlage institute, Netherlands.

his work focus on both research and practice under realism, and proposing strategic solutions through cutting-edge analysis and thinking.

Peiwen Li

Eng.D in progress at HIT(Harbin Institute of Technology, China), Master’s degree in Architectural Design and Bachelor’s degree in Communication Engineering at SEU(Southeast University, China). Head of ART(Architectural-Research-Team) in Xkool.Main research interests: Generative Design, Operations optimization and AI application within Architecture.

Liangyi Murong

Master’s degree in Big Data Analytics at University of Michigan and Bachelor of Architecture at South China University of Technology. AI research lead in Xkool. With a background in both architecture and engineering, he has been passionately involved in exploring AI applications in architecture industry, working with cutting-edge technology and collaborating with industry leaders to push the boundaries of architectural technology.

Xudong Liu

Xudong Liu is a researcher at Xkool Technology, skilled in various fields such as computational design, generative AI, building performance simulation, SaaS development, and virtual reality. His passion for these areas began during his postgraduate studies in UCL and has since driven his research endeavors. Currently, Xudong’s primary focus lies in the full stack architecture and development of the ARP (Architecture Research Platform) and its associated applications. 

Shengzhan Xu

Shengzhan is an architectural researcher at Xkool Technology.  Master’s degree in Architectural Computation from UCL. He is passionate about researching and developing computational designs and is dedicated to exploring the use of smart products in architecture. Research interets: generative design, geometric optimization, building performance simulation, AIGC and virtual reality.

Chi Wai Yuen

XKool Tech architect. Chi Wai Yuen has years of experience in architectural design in various parts of the world and is active in the fields of public building design, community empowerment, and cultural observation. He takes a long-term and critical perspective on urban phenomena, analyzing the underlying causes and structures behind them. He then communicates his ideas through systematic and data-driven architectural design, urban planning, community empowerment, and written commentary, aiming to promote citizen awareness, participation, and awakening to varying degrees.