About Me
I'm passionate about solving problems to make people's lives easier, whether it's pain, frustration, or just everyday annoyances. My background in public health taught me to look at things holistically and dig into the "why" behind human behavior, not just the surface-level problem. I've spent my career thinking like a researcher and a listener, someone who spots patterns, asks better questions, and turns empathy into action. Friends say I'm the person they rant to because I make them feel heard and help them find solutions that actually make sense for them. Honestly, that's the same energy I bring to product. After years working in oncology research and the federal health space, I've learned how to innovate within constraints, blend tech with humanity, and keep users at the heart of everything.
Experience
A progressive journey across research and clinical operations into product
Product Manager
SSV AI, LLC - Self-Employed
Early-stage company developing an AI-powered application for chronic disease management
Key Achievements
- Defined concept for mobile app CalmCGM to reduce medical burnout from glucose management; performed competitive analysis, conducted user interviews and identified pain points to translate into app features.
- Identified opportunities to translate AI capabilities into practical, user-focused solutions, to generate personalized mental health focused insights regarding attitudes on continuous glucose monitoring.
- Identified user requirement for stress-free app engagement; developed a gamification concept that provided positive reinforcement without penalizing lapses in app use.
- Leveraged AI tools (Lovable, Magic Patterns, Bolt) for rapid prototyping, UI mockups and landing page for generating user interest and feedback.
Associate Product Manager / Clinical Operations
National Cancer Institute
Federal cancer research agency focused on advancing cancer prevention, treatment, and disparities research
Key Achievements
- Increased overall clinical trial recruitment across 4 active trials by 45% by leading end-to-end design, launch and adoption of an online patient enrollment system on low-code/no-code platforms, liaising between cross-functional teams of clinicians, developers, and operational leaders on a $3.3M health IT contract.
- Led user research by applying epidemiological concepts with 20+ users and 10 clinicians to identify pain points, gathered and translated user needs into product requirements, managed feature/bug prioritization and backlog.
- Identified paper-based surveys as a key operational bottleneck in clinical workflows from usability studies and led the launch of an electronic survey program that increased user response rate by 70% and 2x user engagement.
- Co-developed and maintained 20+ strategic partnerships with research institutions to expand access to rare disease data, and managed the scalability of data infrastructure.
- Collaborated on customer success efforts to resolve onboarding issues, providing proactive support, building and maintaining patient-provider relationships, ensured continuous delivery of value from using the enrollment platform.
- Led preparation for high-visibility branch evaluation, gathered and organized materials from 10+ clinicians, and ensured on-time delivery in ambiguous and resource-constrained settings.
- Reduced manual and duplicate data entry by 50% by standardizing workflows to prevent recurring data backlog.
- Managed clinical EDC/survey platforms and automated processes such as survey distribution, documentation, and preparation for analysis, reducing manual data entry from weeks to hours.
Social Media Marketing Manager (Aggressive Driving campaign)
George Washington University Center for Injury Prevention and Control
TikTok public health campaign focused on aggressive driving behaviors
Key Achievements
- Managed content ideation and script writing for a TikTok public health campaign, led a team of 4 medical student content creators, thus reducing video development time by 50% but doubling video output.
- Advised on best practices and current trends that would boost viewership by 60%, 200% increase in followers, and improved overall audience engagement.
- Analyzed pre- and post-intervention data to evaluate changes in attitudes towards aggressive driving behaviors among adult males in Washington, D.C.
Program Evaluation Associate
District of Columbia Center for AIDS Research (CFAR)
Part of a larger network of CFARs funded by the National Institutes of Health to provide scientific leadership and institutional infrastructure for HIV/AIDS research
Key Achievements
- Revamped existing survey infrastructure to support systematic program evaluation by discovering 20 new actionable KPIs, which were included in publications about the effort.
- Aligned survey strategy with program goals to assess the nationwide rollout of 15 pathway initiatives to improve minority representation in HIV/AIDS research careers.
Current Projects
Active initiatives I'm working on right now
VibeChef
You set the vibe, we'll set the menu. Select the vibe of your meal prep plan and instantly get recipes according to what's in your pantry
VibeChef
Technologies & Tools
Replit, Magic Patterns
User Personas
"Taylor the Busy Professional" - 25-40 years old, hybrid worker (blend of in-office/WFH days) needs recipe suggestions to fulfill their daily target protein intake on a high-protein plant-based bodybuilding diet. "Jordan the Busy Parent" - 30-45 years old, has 3 children with different dietary restrictions, needs to track pantry inventory and plan grocery trips, minimizing food waste. "Riley the Stressed College Student" - 18-22 years old, craves comfort food while juggling a jam-packed schedule, and is often too tired to plan meals. Needs an easy way to be suggested recipes that fits the craving.
Problem Statement
Busy people need an easier way to plan what they're going to eat, verbalize their cravings into prepared grocery lists/recipes. Pantry tracker apps do not account for dietary needs/nutritional goals and recipes are not personalized to the actual quantities of the items in the pantry, revealing a need for more intelligent ways of meal prepping.
Success Metrics
Beta Testing: 100+ users providing feedback (target: Q1 2026) Week 1 Retention >40%
CalmCGM
Creating a companion mobile app designed to reduce medical burnout from continuous glucose monitoring systems
CalmCGM
Technologies & Tools
Lovable, Magic Patterns, Bolt
User Personas
Alex the newly diagnosed diabetic - 20-25 years old (Type 1/takes insulin) wants a simple "in-range/attention/urgent" view, so that they know when to act without decoding charts. Hayden the student - 19-24 years old (Type 2/non-insulin) wants a quick way to reflect and process feelings about their glucose management without spending more than a minute on it. Sophia the early career professional - 28 years old (Type 2/insulin) wants Daytime alerts to be subtle and actionable, so that I can acknowledge or snooze quickly and not be disturbed during meetings.
Problem Statement
Existing mobile apps that pair with continuous glucose monitors flood the user with data, charts and insights but nothing actionable. The burden of interpretation and action is on the user, which compounded over time with managing chronic diseases such as diabetes, leads to medical burnout and alarm fatigue.
Future Direction
Phase 1 - Product Validation and User Research, Phase 2 - Feature Planning and Prototyping, Phase 3 - User Feedback and Iteration
Success Metrics
# of Active Users (DAU, WAU, MAU), Week 1 Retention >40%, Beta testing: 100+ users providing feedback (target Q1 2026)
Longitudinal Survey Process Redesign
Redesigned the longitudinal survey process for the National Cancer Institute (NCI), streamlining data collection workflows and improving participant retention rates in their active clinical trials.
Longitudinal Survey Process Redesign
Technologies & Tools
Qualtrics PowerBI ServiceNow
Problem Statement
The existing follow-up survey process was paper-based and suffered from declining participant retention, dropping 25% in 2 years, complex multi-step workflows that confused both researchers and participants, and manual data entry errors occurring in 15% of records. Participants reported frustration with lengthy paper surveys, unclear instructions, and lack of progress feedback. Research staff spent 15+ hours weekly on administrative tasks that could be automated.
Success Metrics
70% increase in user response rate, Time spent on data entry - 4 weeks -> 2 hours
Case Studies
Deep dives into product thinking and problem-solving approaches
FAExam App - AI-powered lesion identification
At-home cancer screening promotes early detection and optimizes healthcare resources. How can we leverage AI capabilities to identify pre-cancerous oral lesions earlier and more accurately before an in-person visit?
FAExam App - AI-powered lesion identification
Challenge
The app allows patients with Fanconi Anemia, a genetic predisposition to developing pediatric cancers such as squamous cell carcinoma of the head and neck and oral cavities to self screen for oral lesions that could turn cancerous. Currently the features only support self-directed screening of oral lesions but the burden of scheduling visits with the providers still rests with either the patient or clinical staff. This presents a need for more sophisticated methods of analyzing lesion growth over time, and identifying cases that warrant a visit with the provider.
Current Landscape
Market trends suggest a positive uptick in adoption of at-home screening tools, and favorable attitudes from both patients and medical centers. Patients appreciate the convenience and feel more empowered with their health decision making, while medical centers benefit from cost-savings and optimization of resources, and prioritizing early detection.
Goal Definition
1) To identify pre-cancerous oral lesions proactively with >80% accuracy and escalate cases for review by a provider. 2) Automate scheduling telehealth visits for concerning cases
Customer Segment
Individuals diagnosed with Fanconi Anemia, or those with a heightened risk to developing squamous cell carcinoma (SCC) of the head and neck and oral cavity. Recommended for >16 years old.
Suggested Improvements
AI/ML image pattern recognition - analyzes pictures uploaded by the user to identify oral lesions, estimate size and color and classifies as "Low, Medium or High Concern" where medium to high concern warrants further evaluation by a provider. High concern cases will trigger an agentic workflow to schedule a telehealth appointment with the designated provider.
Metrics
App metrics: Downloads/active users (MAU, WAU, DAU) → indicates uptake among target patients. Accuracy of automated growth tracking → validated vs. clinician assessment. Escalation efficiency → time saved between concerning lesion detected → in-person appointment scheduled False negative rate → incorrectly classifying a high concern case as low concern. Business metrics: $ saved in clinician hours
UI Mockups
AI Projects
Leveraging artificial intelligence to solve complex problems and create innovative solutions
Coming Soon!
Ask my AI avatar any questions about my experience, goals or working together! Target completion: End of Q4 2025
Contact
Let's connect and discuss opportunities
Contact Information
Quick Response
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