Hugh Xuechen, Liu

“Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.” — Richard Feynman

“Boys, be ambitious! (少年よ、大志を抱け!)” - William S. Clark

I study how emerging technical infrastructures reshape creative and cultural practice — by building with them. Geolocation AR, blockchain, and now generative AI have each served as substrates for this same question.

Currently, this means making game research knowledge machine-actionable, with a focus on game design knowledge: translating theories from game studies — ontologies, design patterns — into knowledge bases, generation pipelines, and evaluation frameworks that AI/ML systems can grasp, use, and extend.

Three research lines carry this programme:

• Computationalizing Game Design Knowledge (formalize): Building AI-friendly knowledge bases of game design principles and patterns (ontologies, knowledge graphs, GNN-based knowledge discovery).

• AI-Driven Game Development (operationalize): Creating AI systems that transform high-level design intent (e.g., “make a platformer like Super Mario Bros.”) into interpretable, playable code in Unity — with evaluation frameworks that measure whether generated scenes are actually correct.

• User-Centered AI for Games (validate): Studying how players, designers, and students work with AI systems, across creativity, education, and health — ensuring accessibility and transparency.

#AI #GameDesign #ComputationalCreativity #LLM #GenerativeAI #HCI #KnowledgeGraph #Neo4j #Unity #Blockchain #AR #ScienceViz #Gamification

“How could you describe this heart in words without filling a whole book?” — Leonardo da Vinci