
Haichang Li
LinkedIn / Twitter / Github / Google Scholar / Résumé
HelloWorld ✍
I am Haichang(Charles) Li(李海畅), recently graduated from Purdue University with a B.Sc degree (3.96/4.0 GPA, with Distinction) in Information and Communication. At Purdue University, I was affiliated with DE4M Lab and AIM, and I was lucky enough to be mentored by Prof. Liang He and IEEE Fellow/ACM Distinguished Scientist Prof. Yung hsiang Lu. In addition, I am a founding member of SOUNDING.AI, which is a startup receiving 10M+ CNY to explore how to build AI-based systems and I built a group of AI technical teams here. Currently, I am collaborating with MEMO.AI and exploring using contextual information through AI-integrated glasses to enhance human-AI interaction.:)
Here is a statement of my interest in "symbiosis between humans and machines.":
My research is inspired by the 1997 debate on "Direct Manipulation" and "Interface Agents," the concept of Mixed-Initiative Interaction, and the philosophy of "Taiji." , focus on making humans and machines each contribute their strengths at the most appropriate times. I want to balance the duality of machines and humans like TaiJi: machines work naturally and intelligently like humans, and humans provide control to make sure the machines conform to their intentions and expectations.
Specifically, I am dedicated to designing and evaluating next-generation intelligent systems that dynamically allocate initiative between humans and machines based on contextual information and human intent to support productivity and accessibility.
My goal is to design systems where machines act as human "friends". If you share similar interests and would like to collaborate with me, feel free to drop me an email :)!
News 🌊
[2025.1] Completed my first independent research paper with MEMO.AI and submitted it to CHI 25' LBW. We are now starting to develop a patent focusing on using MEMO to assist blind people.🌟
[2024.12] Successfully graduated from Purdue University with Distinction! Thank you to all who supported me on this journey.🎓
[2024.11] I independently completed the main writing of Code2Fab. We plan to submit this manuscript to the upcoming UIST.💪
[2024.4] The user study of "Mus2Vid" was accepted by IEEE CAI 2024! The results of our user survey will be exhibited in Singapore.🇸🇬🦁
[2024.1] The final version of "Shine Resume" is released in Chinese! Hope this will help some of the "hidden" crowd and shine with them! Thanks for the efforts of all the partners this summer. This is the first time for me to complete a commercial project from 0 to 1, from design to implementation and promotion.🎨
Past 🎯
An AI Assistive 3D Modeling Tool for Accessibility
The co-first authored manuscript will be submitted UIST 25', supervised by a team of faculty in HCI and accessibility researchThe authors info and detailed contents anonymized to avoid potential review process conflicts
An Literature Review of Accessibility Artifacts
Currently targeting CHI 26', supervised by faculty specializing in accessibility researchThe authors info and detailed contents anonymized to avoid potential review process conflicts

Memore: AI-Assisted Memory Assistance and Visualization
Leading research in MEMO, memory assistance system with MEMO AI glasses and mobile/web UI integration
Memore is a hierarchical context-enhanced memory management system to assist elderly users in capturing, organizing, and retrieving memories with the help of LLM-powered multi-agent systems.
WEB / Research Paper (Submitted to the CHI25' LBW)
Mus2Vid: Music Visualization based on Synesthesia
Leading Project, supervised By Prof. Yung Hsiang Lu and Prof. Yeon-Ji YunMus2Vid employs LLMs to simulate human cognition in music visualization, hierarchically generating storyboard-driven videos that align machine outputs with artistic intent through contextual awareness and cinematic narrative frameworks.
Prior Survey (2024 IEEE CAI) / WEB / CODE / Technical Paper (In Prep)
ShineResume: Resume Writing System for Confused Graduates
Founding Member of a "0 to 1" entrepreneurial experience obtaining 10M+ CNY funding supportShineResume is an AI-driven initiative-balancing system that dynamically shifts control between user autonomy and system guidance, leveraging contextual data to recommend career paths and optimize resumes for Post-COVID 19 graduates, ensuring ethical human-AI collaboration in navigating job market uncertainties.
WEB(CHINESE)
Social Robot for the Depressed and Lonely
Project Prototype for Assistive Tech with Taehyeon Kim, instructed By Prof. Byung-Cheol MinThis Assistive Technology Grad course project explores how to LLM to identify contextual cues and utilize agent-driven decision-making for API integration, aiming to provide support and assistance for individuals struggling with depression and loneliness.
PROPOSAL / WEB / CODE / PDFContact With Me 🍔
I always enjoy discussing and exchanging ideas with others, welcome to communicate with me.📤