Ann Chen, a Product Manager and a Master’s student at Harvard specializing in AI products, UI/UX design, and mixed-method user research.
Before Harvard, she published computer science research, interned at Apple, and worked a visual artist for seven years!
End-to-end UI/UX Design
Before working at Homemade*, a three-person startup at Harvard Business School FieldX, I worked as a product manager and UI/UX designer. I had experience conducting iterative user research, designing websites, and prototyping mobile apps.
*Homemade is a Boston company matching private chefs to working professionals who don’t have time to cook.
Hardware AI UX Research
I developed RDog, an award-winning AI hardware product that increases navigation success rates for visually impaired users by 40% through iterative participatory design sessions.
Product & Research @ NUS-HCI Lab, where I uncovered key pain points in existing assistive tools and conducted sessions to design a proactive, trust-centered robotic guide dog.
Software AI UX Research
First-Author Conversational AI Research published at a top-tier human–computer interaction conference.
I led survey research (n=150) and concept testing on tactics conversational AI can use to ask for human help. I tested three design framings and identified one that increased human helping behavior toward AI by 6.9% and another that increased trust by 27.5%
Research @ NUS AI For Social Good Lab, where I initiated this research project after noticing Reddit posts where users expressed frustration about ChatGPT asking for human help.
Software Engineering
Hands-on engineering experience in both small teams at Yale and global tech companies like Apple.
At Apple, I delivered a data product for metric reporting on Apple Watch, supporting data and manufacturing teams and improving reporting time by 40%.
At Yale, I led a team of three engineers to design and ship a minimum viable product: a walking app for Yale students that increased user participation by 35%.
Other Design, Data, Product Developed by Ann in Industry and Academia
User Experience Intern @
Abillion - #2 most innovative consumer review platform in 2022
I designed user journeys for product pages, conducting keyword, listicle research for content strategy to raise traffic of the website
Go-To-Market Strategist @
MIT Early-Revenue Food Tech Startup ($1M–$5M)
I informed market entry decision-making by alignment across executive stakeholders and through thorough user and market research
Passion Project:
Redesigning the Nuli Fitness
App UI/UX
I informed market entry decision-making by alignment across executive stakeholders and through thorough user and market research
Product Researcher @
Harvard Teaching and Learning Lab
I redesigned Harvard’s How People Learn course for working professionals in collaboration with MIT Sloan’s Learning Designer, leveraging iterative user research and expert interviews to improve learner engagement and retention.
Data Scientist Intern @
Artefact
I uncovered gaps in beauty consumer preferences and market positioning through exploratory data analysis, and implemented ML models to segment customers, forecast demand, and recommend high-potential product prioritization.
Product Engineering Intern @
HP
I diagnosed challenges in HP printer quality compared to competitors by identifying performance gaps and customer pain points, and executed comprehensive testing frameworks, established KPIs, and performed analysis to address those gaps.
AI Harm Researcher @
Social Well-being, Empathy, and Emerging Technologies Lab
I analyzed 10,000+ user–AI conversations to identify response patterns, partnering with engineering to implement mitigation strategies.
Conversational AI Researcher @
AI for Social Good Lab
I designed chatbot generating exercise advice to overweight users, driving 7% higher perceived advice quality and 12% trust, and conducted interviews with HR professionals, partnering with engineers and HRs to develop an AI-powered recruiter support tool.
Robotics Researcher @
Yale Social Robotics Lab
I examined the robot’s strategy for apologizing to humans after making mistakes by programming the NAO robot and designing the experiment.