Kevin Ma

About Me

I am a PhD candidate in Mechanical Engineering at UC Berkeley, where I am a part of the Co-Design Lab advised by Prof. Kosa Goucher-Lambert. I am also affiliated with the Berkeley Institute of Design and am closely associated with the Jacobs Institute of Design, where I have supported design education through teaching and mentorship.

I am a design researcher focused on human-AI collaboration, studying how people and teams use generative AI in creative and technical workflows. My research combines UX research, computational evaluation, and design theory to understand how people use, trust, adapt, and collaborate with AI systems. During my PhD, I have worked with collaborators at City University of Hong Kong, Autodesk Research, Carnegie Mellon, and Virginia Tech on projects spanning GenAI-supported UX storyboarding, LLM evaluation for design, and computational simulation. I also worked as a research intern at NASA Langley Research Center and HP Inc., where I studied GenAI adoption in real-world innovation settings and designed conversational AI agents to support team collaboration.

In the past, I did my BS in Mechanical Engineering at The University of Texas at Austin, and during that time, I conducted research in COVID-19 risk modelling under the supervision of Prof. Michael Lachmann and Prof. Jennifer Johnson-Leung.

In addition to my research work, I enjoy advising undergraduate or masters students who are interested in doing human-AI interaction research. My goal is to support future generations of researchers that are interested in pursuing graduate education. If you are a UC Berkeley student and are interested, please feel free to reach out. Outside of research, I enjoy breakdancing, hiking, and reading in my free time!

Research Interests

• Human-AI Interaction: generative AI in design practice, AI as a social actor, collaborative creativity, human-AI collaboration
• Design Research: early-stage design, design cognition, human-centered design, professional design and innovation workflows
• Computational Design: LLM-supported concept generation, design space exploration, computational analysis of AI-generated design outputs

Teaching

I co-created a design class, Human-AI Design Methods, which is a project-based course where students use human-centered and AI-augmented design methods to develop products, services, and systems while critically examining the technical, ethical, and social implications of AI in design. My prior experience includes serving as a teaching assistant for courses in design methodology and design frameworks.

• MECENG292C / DESINV190 — Human-AI Design Methods Spring 2026
• DESINV200 — Design Frameworks Spring 2024, Fall 2024
• DESINV15 — Design Methodology Spring 2023

News

• [May 2026] I passed my qualifying exam and am now a PhD Candidate!
• [May 2026] Our ongoing work on AI personas in collaborative design was accepted as a poster at ACM Creativity & Cognition.
• [March 2026] Our journal paper on using LLM agents to simulate design theory was published in a Special Issue of the ASME Journal of Mechanical Design.
• [October 2025] Our collaborative paper, led by Zhaohui Liang and Xiaoyu Zhang, on StoryDifusion, a GenAI system for UX storyboarding, was accepted to ACM ICMI 2025.
• [August 2025] Our conference paper on using LLM agents to simulate design theory got chosen as one of the top papers at ASME IDETC 2025.
• [January 2025] Our paper comparing LLM generated ideas versus human crowdsourced ideas got published to ASME Journal of Computing and Information Science in Engineering.

Powered by Jekyll and Minimal Light theme.