STACEY BRANDSMA
AI Strategist • Patient Safety Champion • Public Health Enthusiast
I'm a Digital Product Senior Manager at Amgen, where I translate complex patient safety challenges into scalable, AI-enabled solutions that help protect patients and enhance pharmacovigilance operations worldwide.
Georgia Tech
AI Innovation
& Public Health
Patient Safety Innovation
Developing intelligent solutions that revolutionize pharmacovigilance processes—from document intelligence that streamlines patient safety reporting to assessment engines that improve how we evaluate and respond to patient safety signals. My work focuses on building AI systems that enhance our ability to protect patients through more efficient and effective patient safety operations.
Precision Medicine
Building ML models for patient stratification that enable personalized approaches to both therapeutic optimization and adverse drug reaction prediction. By identifying which patients are most at risk for specific patient safety events, we can advance precision patient safety as a critical component of public health—preventing harm before it occurs rather than just responding to it.
- AI Document Authoring Platform - Automating periodic patient safety reports using generative AI, revolutionizing regulatory document creation
- Patient Safety Assessment Engine - Improving the signal assessment process with ML and data-driven methods
- Risk Prediction Models - Building predictive models for proactive patient safety management and early risk identification
- Leadership - Co-leading AI taskforces for Patient Safety and Obesity & Weight Management across global teams
- AI Training & Education - Delivered multiple training sessions for patient safety practitioners on AI applications in pharmacovigilance
- Precision Medicine - Developing patient stratification models for IBD and obesity, enabling personalized treatment approaches
- Clinical Intelligence - Building competitive intelligence and forecasting models to support strategic business decisions
- Digital Health - Evaluating and implementing digital health solutions for clinical trials, improving patient outcomes and operational efficiency
- AI Taskforce Leadership - Co-leading AI taskforces for Patient Safety and Obesity & Weight Management, driving innovation across therapeutic areas
- Symposium Leadership - Vice Chair of Data Science Symposium for 1,500+ employees, creating learning opportunities and knowledge sharing
- Pharmacovigilance Innovation - Advanced signal assessment and patient safety data review using machine learning and statistical methods
- Created COVID-19 ICU capacity and census prediction models
- Deployed models for hospital visit cost forecasting
- Built pipeline for calculating regional COVID-19 Rt values
- Received outstanding work award during pandemic response
- Developed models for detecting suspicious orders in controlled substances
- Built interactive visualization tools for statistical concepts
- Implemented IoT analytics for location prediction and tracking
- Enhanced pharmaceutical patient safety and regulatory compliance
- Designed and implemented M&E frameworks for multi-sector development projects
- Conducted field evaluations and data collection in remote rural communities
- Built capacity for local NGOs in data collection and analysis methodologies
- Managed cross-cultural teams and facilitated community engagement initiatives
- Developed sustainable monitoring systems for healthcare and education outcomes
- Applied statistical analysis to assess project impact and inform policy decisions
Specialization in AI Ethics & Society, Deep Learning, and Human-Computer Interaction. Independent study on patient risk factors for diabetes, obesity, and sleep apnea.
Focus on machine learning, Bayesian statistics, high dimensional data analytics, business analytics, and data visualization.
Development economics, randomized evaluations, and social data analysis.
Published thesis in International Journal of Food Microbiology. Laurence Decore Student Leadership Award, VP Student Government.
Craft & Code: Where Fiber Arts Meet Computer Science
Pattern recognition, systematic thinking, and iterative problem-solving form the foundation of both fiber arts and computer science.
A Lifelong Love of Making
Ever since I was a kid, I've been drawn to making things with my hands—knitting intricate scarves, sketching detailed drawings, building elaborate sandcastles, and creating whatever my imagination could conjure. There's something magical about the process of transforming raw materials into something beautiful and functional.
I've discovered that my best ideas come when my hands are busy and my mind is free to wander. Whether I'm working through complex stitches in a sweater pattern or debugging a particularly stubborn piece of code, there's a meditative quality to the repetitive, methodical work that opens up creative pathways in my brain.
There are profound parallels between crafting and computing—both involve taking an idea that exists only in your mind and making it real. Whether you're creating a knitted garment or writing code, you're translating abstract concepts into tangible results through systematic, deliberate steps.
Historical Parallels: Craft & Computation
Jacquard Loom (1804)
The first programmable machine used punch cards to create complex textile patterns—directly inspiring early computer programming concepts.
Ada Lovelace
Often called the first computer programmer, Lovelace compared her analytical engine work to the Jacquard loom's pattern-making capabilities.
Binary Thinking
Knitting and weaving operate on binary principles (knit/purl, over/under) that mirror the fundamental logic of computing.
Interactive Pattern Generator
When I wanted to take my fiber artwork to the next level, I realized I could combine my passion for crafting with my technical skills. That's when I built an interactive pattern generator that uses clustering algorithms to transform any image into knitting or cross-stitch patterns. It's the perfect marriage of my two worlds—using computer science to enhance and expand my creative practice.
Upload an image and watch clustering algorithms transform it into a knitting or cross-stitch pattern!
Click to upload an image or drag and drop
Supports JPG, PNG, GIF
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