Weirui Peng PDF

University of Michigan, Ann Arbor, MI
Ph.D., Computer Science and Engineering
Advisor: Xu Wang and Eytan Adar

Columbia University, New York, NY
M.S., Electrical Engineering
Advisor: Lydia Chilton

The Chinese University of Hong Kong, Sha Tin, HK
B.Eng., Electronic Engineering
Graduated with First Class Honors
Advisor: Thierry Blu

EduPolicySim: LLM-Agent Simulation for Navigating the Pedagogical Policy Space
Weirui Peng , Hyoungwook Jin , Ethan Beaird , Xu Wang
CHI 2026 Workshop. (PoliSim@CHI 2026: LLM Agent Simulation for Policy)

GLITTER: An AI-assisted Platform for Material-Grounded Asynchronous Discussion in Flipped Learning
Weirui Peng* , Yinuo Yang* , Zheng Zhang , Toby Jia-jun Li
UIST 2025.

LADICA: A Large Shared Display Interface for Generative AI Cognitive Assistance in Co-Located Team Collaboration
Zheng Zhang , Weirui Peng , Xinyue Chen , Luke Cao , Toby Jia-jun Li
CHI 2025.

What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use
Qianou Ma , Weirui Peng , Chenyang Yang , Hua Shen , Kenneth Koedinger , Tongshuang Wu
TOCHI 2025.

Exploring the Diversity of Music Experiences for Deaf and Hard of Hearing People
Kyrie Zhixuan Zhou , Weirui Peng , Yuhan Liu , Rachel F. Adler
CSCW 2025.

Enhancing User Engagement in AI Auditing Through Gamification and Storytelling
Weirui Peng , Mengyi wei , Kyrie Zhixuan Zhou
CSCW 2023 User AI Auditing Workshop.

Lifelong Learning Lab, University of Michigan
Graduate Research Assistant
Advisors: Xu Wang and Eytan Adar

• LLM-simulated students for exploring and reforming educational policy.
• Mitigating learner overreliance on LLMs in educational settings.

WInE Lab, Carnegie Mellon University
Research Assistant
Mentor: Sherry Tongshuang Wu

• Designed and implemented a web-based interactive system that transforms user requirements into effective prompts for large language models (LLMs).
• Conducted in-depth data analysis of user study results to evaluate system usability and effectiveness, deriving key findings for further development.
• Paper accepted to TOCHI 2025.

HCII, Carnegie Mellon University
Research Assistant
Mentor: Niki Kittur & Nik Martelaro

• Investigated how designers utilize bio-inspiration to improve design outcomes, focusing on the methods and processes employed in translating natural phenomena into innovative solutions.
• Developed workshop agendas and organized sessions to explore how designers identify and extract key elements from bio-inspiration, facilitating deeper insights into their creative processes.

SaNDwich Lab, University of Notre Dame
Research Assistant
Mentor: Toby Jia-jun Li

• Conducted interviews with users to understand their unique needs in team collaboration tools.
• Designed interactive systems for supporting co-located team collaborations and asynchronous discussion in flip learning.
• Papers accepted to CHI 2025 & UIST2025.

Information Experience and Accessibility Lab, University of Illinois Urbana-Champaign
Research Assistant
Mentor: Rachel F. Adler

• Conducted a qualitative content analysis and text mining on Reddit discussions about music experiences of Deaf and Hard-of-hearing (DHH) people.
• Conducted interviews with DHH people to understand their needs in music appreciation.
• Paper accepted to CSCW 2025.

Computational Design Lab, Columbia University
Research Assistant
Mentor: Lydia Chilton

• Created an AI-powered interactive system to assist design students in crafting digital art portfolioswith p5.js.
• Utilized generative AI to co-create visual, audio, and interactive elements based on artists' visions.

Adobe Research
Research Scientist Intern (incoming)
Mentor: Mira Dontcheva

• Incoming role; planned focus on agentic video and audio editing.

Oortech, New York, NY
Machine Learning Engineer intern

• Conducted a detailed comparative analysis of large language models (LLM) including GPT3.5, Vicuna, Bloom, Llama2, Phoenix, and ChatGLM, using the Fastchat platform.
• Implemented the LoRA finetuning for LLMs to build and refine a specialized LLM product tailored for Lenovo, incorporating the company's product knowledge through custom datasets constructed from the information provided by Lenovo.
• Addressed and resolved technical challenges in model training and integration, significantly enhancing the service's ability to provide accurate and effective responses to customer queries.

University of Michigan CSE Departmental Fellowship

• Full tuition and stipend coverage for first-year PhD study.

Talent Development Scholarship, Hong Kong

Second Runner Up & Xiaomi Vela- Smart City IoT Award, HackUST

Bronze Medal at National Level, 7th International Internet+ College Students' Innovation & Entrepreneurship Competition