AI + Design + Human Factors
Designing Human-Centered AI Systems for the Physical World
I am a graduate student at Tsinghua University, specializing in Urban Human Factors Engineering and AI‑driven design systems. My work explores how artificial intelligence, data science, and human experience converge to build intelligent environments and creative tools that understand people — not just data.
As the Co‑founder & COO of AlloTech, an AI platform for generative manufacturing design, I lead cross‑functional teams combining algorithmic modeling, data engineering, and product design. My broader research investigates how human factors principles can shape the next generation of AI‑driven urban and digital systems.
My journey moves between research, entrepreneurship, and design — from conducting large‑scale data analysis at ByteDance and Meituan to leading projects that merge machine learning with spatial cognition. Outside the studio, I find balance in mountain hiking and outdoor exploration, where I draw inspiration for resilient design thinking.
Beijing, China
Master of Architecture – Urban Human Factors Engineering
Sep. 2023 – Jun. 2025
• GPA: 3.9/4.0 | Rank: 35/119
Tianjin, China
Bachelor of Architecture and Urban Planning
Sep. 2018 – Jun. 2023
• GPA: 3.9/4.0 | Rank: 1/186
Leading AI-driven innovation across industry and academia
Leading a generative AI platform that automates manufacturable design generation, integrating geometry encoding, multimodal diffusion models, and constraint optimization.
Developed ML pipelines for location-based behavior prediction and experimentation optimization across >100M samples.
Fine-tuned large language models with advanced data cleaning and bias reduction techniques, improving dataset quality by 12%.
Semantic segmentation on 30,000+ street-view images for environmental indicator extraction.
AI-adaptive environmental regulation based on behavioral and emotional measurement models.
AI × Design × Human Factors
An intelligent spatial system capable of sensing user emotion and adapting environmental parameters in real time. This thesis explores the intersection of affective computing, spatial design, and human-centered AI, proposing a new paradigm for responsive architectural environments.
An experimental prototype for interactive urban public spaces that combines human behavioral data with generative form optimization. The project demonstrates how AI can inform responsive urban design that adapts to community needs and usage patterns.
A computational framework for personalized environmental control that merges IoT sensing with machine learning for comfort prediction. The system learns individual preferences and optimizes lighting, temperature, and air quality in real-time.
At AlloTech, I lead strategy, data infrastructure, and product development, translating cutting‑edge AI models into scalable tools for real‑world design.
Achievements
Previously Student Union President and Football Team Captain, leading multidisciplinary teams toward shared goals. Outside of work, I am a mountain hiker and long‑distance runner — exploring resilience, balance, and clarity.
Tracing the transition from architectural design to algorithmic systems that shape environments and experiences. An exploration of how spatial thinking informs intelligent system design.
Behind the process of connecting geometry encoders, diffusion models, and user needs. A deep dive into the technical and human challenges of building AI for physical design.
Let’s connect and collaborate on AI‑driven design, human factors, and intelligent systems.
“Always open for collaborations that bridge data, design, and humanity.”
