Hey!
I am
Lily Lee
Skills & Expertise
90%
Product Management
1 Year Experience
Experienced with Agile methodologies including Scrum, Lean Start-Up principles, MVP development, Jobs-to-be-Done framework, market segmentation, and strategic positioning.
99%
Data Analysis
6 Years Experience
Python • R • Altair • gg plot2 • Regression Analysis • Longitudinal Studies • Causal Inference • A/B Testing • CFA/EFA
95%
Mix-Method Research
3 Years Experience
In-depth Interviews • Cognitive Task Analysis • Contextual Inquiry • Usability Testing • Personality Assessment • Competitive Analysis
75%
Human Centered Design
2 Years Experience
Proficient in Figma for creating intuitive user interfaces and interactions. Skilled in wire-framing and prototyping to bring ideas to life and validate design decisions through iterative testing.
Work Experience & Education
Product & UXR Internships
Former UX Researcher Intern at KuaiShou Technology
Product Intern at ZHIPU AI and CMU OLI
Gained hands-on experience conducting user research across diverse product ecosystems, from short-form video platforms to cutting-edge AI applications.
M.S. in Human-Computer Interaction
Carnegie Mellon University
Advanced training in designing and evaluating interactive systems, combining technical proficiency with user-centered design principles.
M.S. in Applied Psychology
Deep foundation in psychological research methods, cognitive processes, and human behavior—essential for understanding user needs and motivations.
Projects Portfolio
Explore some of my impactful research projects that demonstrate a blend of psychological insights and technological innovation, driving meaningful user experiences.
AI onboarding by AI features
A research-driven project of AI tutor (DOT) that increased engagement by scaffolding learning through in-context AI Activation Point instead of passive chat usage.
Product Lead · 8 months
Key Areas: # Human-AI Interaction # Ed-Tech
Trust AI by Design
Rapid 3-month concept-to-launch iteration by translating physician insights directly into features of a physician dashboard
Product Manager Intern · 3 months
Key Areas: # Healthcare
Two User Side UX Research
Dual-sided UX research on a creator marketplace to map real workflows, identify collaboration breakdowns between buyers and sellers
UX Researcher at Kuaishou · 4 months
Key Areas: # E-commerce
Project 1
AI onboarding by AI
Improving Student Engagement with AI Tutor
This project involved a research-driven initiative for an AI tutor (DOT) aimed at increasing user engagement. The core idea was to scaffold learning through proactive, in-context AI Activation Points rather than relying solely on passive chat usage.
Organization: CMU Open Learning Initiative (OLI), funded by Gates Foundation
Role: Product Lead · 8 months
Key Areas: # Human-AI Interaction # Ed-Tech
The Challenge
AI Assistant Adoption rate
remained extremely low.
Only 11% of 4,249 students used DOT*, with most interactions limited to 1–5 times across entire semester-long Chemistry course. Students frequently opted for other resources such as YouTube, or peer assistance.
The goal of the research is to find out:
  • Why learners weren’t discovering or using DOT?
  • How can we optimize on DOT feature to increase the adoption and support learning?
DOT: Digital Online Tutor, AI assistant that is omnipresent in the REAL CHEM, trained on the REAL CHEM courseware, including the actual chemistry content and the specifics of each section (e.g., due dates)
Method
Two Rounds of Mixed-Methods Inquiry
Our goal was to understand why students ignored the AI tutor (DOT) and to design interventions for learning-centered AI engagement.
Research Round 1: Diagnose Behavioral Barriers
Methods:
  • Log Data Analysis (n = 4,249): Identified extremely low usage(11%); 36% copy-paste queries.
  • 9 Student Interviews: 5/9 unaware of DOT, revealing failure at the first step of engagement: awareness.
  • 4 Instructor + 3 Learning Engineer Focus Groups: Defined the ideal role of DOT as a “thoughtful TA” that scaffolds thinking rather than giving answers
Insight
Students are not inherently against AI. Instead, they seek structured, step-by-step assistance and timely visibility of help, moving beyond simple chat interactions.
Ideation
We presented findings and design opportunities to the OLI team. Based on this research, the product direction shifted toward proactive guidance — leading to activation point features for DOT.
Research Method
Two Rounds of Mixed-Methods Inquiry
Research Round 2: Validate Design Intervention
We presented findings and design opportunities to the OLI team. Based on this research, the product direction shifted toward proactive guidance — leading to activation point features for DOT.
Intervention Tested: AI Activation Points + Updated base prompt.
Methods:
  • Log Data (n = 373) after feature release: Measured proactive engagement and help-seeking.
  • 7 User Experience Interviews: Evaluated usefulness, trust, and activation timing.
Outcome
Students shifted from passive answer-checking to guided problem solving, increasing engagement from 11% to 46% (4x).
Solution
AI Activation Points
With AI Activation Points, DOT no longer relies on students to seek help but proactively engages them in their learning journey.
To increase awareness, deepen learning, and reduce copy-paste misuse, we introduced three proactive AI Activation types that guide students at key learning moments.
Page Activations
DOT pops up automatically when students open a page, posing metacognitive questions about learning strategies and introducing social psychology interventions (e.g., growth mindset)
Paragraph Activations
Prompts create dialog about what students have just read, asking clarifying questions, addressing potential misconceptions, or reinforcing understanding of key concepts.
Activity Activations
Provides immediate feedback on the correctness of written responses to constructed response questions, such as those found in REAL CHEM simulations.
Other solution: Base Prompt Updated: Reluctant to directly answer homework questions/ Must be concise + structured + correct LaTeX
Impact & Learning
Quantifiable Outcomes
The implementation of AI Activation Points significantly transformed student engagement and secured institutional commitment for continued innovation.
4x
Engagement Jump
Student usage of DOT surged from 11% to 46% after the introduction of activation points.
36%
Proactive Learning
A significant portion of students (36%) now proactively seek help, moving beyond passive interactions.
15K+
Wider Adoption
The AI feature was adopted by 25+ instructors and deployed to over 15,000 learners. Also implemented in multiple independent-learner courses.
Fund
Secured Funding
The project helped OLI secure continued Gates Foundation support for AI learning innovation; Strengthened OLI’s position for future grant opportunities related to AI and learning innovation
Key Learning
When Designing AI Features
1. Seamless workflow integration drives engagement AI must appear at natural moments in the learner journey.
2. Users value agency and control: There is a careful balance between automation and user autonomy. Users prefer AI that offers support without taking over the task or making decisions for them.
Try this out!
Scan the QR code to log in.
Go to Unit 1 "How to Use AI in REALCHEM" experience DOT's AI-powered onboarding in REAL CHEM for yourself!
Project 2
Your Health,
Your Plan
Transforming fragmented health data into a continuous, personalized story of well-being
Led end-to-end research to design an AI-supported physician dashboard that transforms scattered health data into actionable, longitudinal insights supporting preventive care decisions
Organization: CMU Corporate Startup Lab
Role: Product Manager Intern
Key Areas: # AI # Healthcare
My Role & How I Worked
Product Manager
  • Owned end-to-end research strategy: scoping, recruitment, interview protocol, synthesis.
  • Translated insights into PRD requirements and feature prioritization that engineers could implement.
  • Partnered closely with PMs, engineers, and CEO to align research insights with business goals.
The Challenge
The Reality of U.S. Healthcare Today
Physician Burnout
"Physicians are drowning in tasks they were never trained for, and patients are left guessing about what they’re supposed to do."
— Gabe, CEO of Forefront Concierge Medicine
Primary Care Crisis
"U.S. primary care ranks last among high-income countries."
— The Commonwealth Fund
Client Requirements
Build monitoring platform (YHYP) aggregating labs, EHR data, wearables, lifestyle metrics, a new operating system for proactive care
Research Question
How might we design a second set of eyes for physicians?
Plans & Phases
Three-Phase Design
We framed the project in three phases, with research embedded as the driver of design:
01
Phase 1 – Discovery & Initial Design
  • Marketplace Analysis: Lit review and market scan
  • Semi-structured interviews physicians interviews (N=7)
  • Workflow walkthroughs covering pre-visit, visit, and post-visit activities
  • EHR screen-sharing sessions (Observational research with think-aloud protocol)
  • First conceptual dashboard (V0 → V1)
02
Phase 2 – Feedback & Design Iteration
  • Usability testing with physicians (N=3)
  • Refined health components, layout, and AI behavior
  • V2 dashboard + refined PRD
03
Phase 3 – Finalization & Build
  • V3 final design
  • Integration with backend (Athena + custom DB)
  • Demo-ready product for Forefront clinics
Research Translation to Design
Impact
We built a new operating system for proactive care that help physicians reclaim prep time, accelerate documentation, and surface hidden risks for earlier intervention.
Product Impact
120+
Physicians Using Platform
Enabled launch-ready platform now actively used by concierge physicians
45%
estimated Reduction in Prep Time
Delivered significant reduction in pre-visit preparation time
Research Impact
Direct Causal Chain
  • Enabled rapid 3-month concept-to-launch iteration by translating physician insights directly into PRD requirements and features.
Try out yourself!

forefront-yhyp-nine.vercel.app

Your Health, Your Plan

Your Health, Your Plan - Physician Dashboard for Concierge Medicine

“From a cardiovascular standpoint, these AI recommendations are appropriate. Doctors often miss things like ACE inhibitors or the DASH diet — having AI surface those and letting me click once to add them to the action plan would be a real one-stop shop.
- Dr. Amir
“I love having vitals, labs, and wearable data all in one place. I'd pull this up with patients and walk through it visually during visits — incredibly helpful for clinical decision-making.
- Dr. Sheena
Project 3
Improving Marketplace Match Efficiency Through Dual-Side UX Research
  • Platform: Kuaishou Technology (DAU: 400 Million) Magnetic Creative (commercial creative marketplace) that connects
  • Advertisers & agencies who need creative production
  • Creative studios & freelancers who provide those services
  • Stage: In 2022, the platform was shifting away from a subsidy-driven growth model toward relying on product experience to drive real transactions.
  • Core challenge: Low transaction efficiency, supply–demand mismatch, and emerging risks to retention and satisfaction
Project Overview
my ROLE & responsibility
UX Research Intern
  • Study design
  • Survey construction and quantitative analysis
  • Cross-side insight synthesis
  • Translating research into product strategy recommendations
Scope
  • Dual-side user research
  • Buyers: 70 survey responses
  • Sellers: 88 survey responses
Methods
  • Quantitative surveys
  • Cross-role comparative analysis
  • Scenario → workflow → pain-point attribution analysis
Research Goals
Dual-Perspective Research Framework
Rather than asking “Who is satisfied and who isn’t?”, I reframed the core problem as:
Where is the platform failing to effectively connect supply and demand?
Key Research Questions
1
Efficient Creative Transactions
Does the platform truly support efficient creative transactions?
  • Do features align with real operational workflows?
2
Buyer & Seller Divergence
Where do buyer and seller expectations diverge?
  • Order intent vs. execution quality
3
Conversion & Retention Impact
Which breakdowns directly impact conversion and retention?
Methodology & Participants
I used a dual-sided survey design, so both buyers and sellers were asked similar questions:
  • Usage goals
  • Tasks
  • Satisfaction across features
  • Communication patterns
  • New feature interest

Buyers — Advertisers & Agencies
70 participants
Roles: purchasing managers, ad reviewers, campaign operators
37% had used the platform for more than 1 year
Sellers — Creative Service Providers
88 participants
Mostly business owners or studio leads
Most had 1–5 years of professional production experience
Overall satisfaction
Both sides rated the platform at a moderate satisfaction level:
3.71
Buyers
out of 5
3.52
Sellers
out of 5
This suggested the platform was "okay" — but not strong enough to be the working tool for collaboration

Shared pain points
1
Heavy off-platform communication
  • Order details, changes, and clarifications moved to WeChat instead of staying in the system.
2
Fragmented workflow
  • Orders, assets, progress tracking, and revisions were managed across multiple screens and even tools.
3
Weak data usability
  • Performance dashboards were difficult to connect back to creative assets or cost breakdowns.
4
Broken trust-building
  • Users relied on private reputation instead of platform information.
  • Service quality, reliability, and case history were hard to assess.
Workflow: Understanding the ecosystem
Buyer journey
  • Create campaign need
  • Browse and evaluate services
  • Submit order requirements
  • Clarify details privately (usually via WeChat)
  • Review submissions
  • Approve delivery
  • Check performance and settle payments
Seller journey
  • Publish and update services
  • Browse orders and bid
  • Clarify requirements
  • Produce creative assets
  • Upload and revise materials
  • Check performance and receive payment

What the map revealed
Experience Gaps
All issues clustered into four core experience gaps
Discoverability Gap
  • Sellers struggle to gain trust and visibility within the platform
  • Buyers face challenges in efficiently identifying high-quality providers
Ordering Friction
  • Complex and unstructured requirement descriptions lead to miscommunication
  • Absence of standardized templates complicates order placement
  • Heavy reliance on external messaging apps for crucial order details
Tracking Blindness
  • Lack of clear visibility for both parties on project progress
  • Difficulties in tracking revisions and status changes
Data Disconnect
  • Creative assets, performance metrics, and settlement information are fragmented
  • Absence of a closed-loop feedback system for informed future decisions
Impact & Business Value
This research helped align product, design, and e-commerce teams around improving marketplace efficiency.
Product Enablement
  • Concept Testing: Validated the service-provider bidding feature, which became a core platform offering
  • Identified critical unmet user needs and friction points, directly shaping product roadmap priorities
Business Value
  • Provided evidence for a strategic shift from subsidy-driven growth to transaction-efficiency optimization
  • Clarified retention risk points across the buyer–seller journey
  • Uncovered opportunities to enhance commercial efficiency and user satisfaction
Research Impact
  • Developed the first dual-sided, system-level model of marketplace experience pain points
  • Established ongoing user satisfaction tracking as a baseline to monitor marketplace health
Thank You!
I'd love to chat!
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📱 Phone
+1 (412) 973-8285
👣 Book a Meeting with me!