Yvonne Mwende

Founder & CEO, GluCorp | AI Engineer | Bioinformatician

Building AI systems that save mothers' lives.

Stanford-trained in precision medicine and bioinformatics. Combining AI engineering with computational biology to detect pregnancy complications early—giving mothers and doctors the time they need to act.

Stanford-Certified in Bioinformatics & Precision Medicine

Advanced training from Stanford University in computational biology and data-driven healthcare

STANFORD UNIVERSITY

Fundamentals of Data Science in Precision Medicine and Cloud Computing

Key Learning Outcomes:

  • Genomic data analysis and interpretation
  • Computational methods for biological research
  • Bioinformatics algorithms and tools
  • Foundation for AI-driven healthcare solutions
STANFORD UNIVERSITY

Fundamentals of Data-Driven Precision Medicine for Diabetes

Key Learning Outcomes:

  • Clinical data integration and analytics
  • Precision medicine frameworks for chronic disease
  • Data science applied to diabetes management
  • Patient-centered healthcare technology design

These certifications provide the bioinformatics foundation that powers GluCorp's AI-driven maternal health platform

GluCorp: Saving Mothers Through Early Detection

AI-powered maternal health platform for early detection of pregnancy complications

The Problem

Every year, thousands of mothers die from preventable pregnancy complications like preeclampsia and gestational diabetes.

These conditions often go undetected until it's too late. Traditional monitoring methods miss early warning signs, leaving mothers and healthcare providers without the time they need to intervene.

The Solution

GluCorp uses AI and bioinformatics to detect risks earlier—analyzing clinical data, vital signs, and biomarkers to predict complications before they become critical.

Our platform gives doctors and mothers the early warning system they need, transforming maternal healthcare from reactive to predictive.

My Role as Founder & CEO

I lead GluCorp's mission to make maternal healthcare predictive, not reactive. Combining my Stanford training in precision medicine with AI engineering expertise, I'm building the technical foundation and clinical partnerships to bring this vision to life.

Current Focus:

  • AI risk prediction models for preeclampsia & GDM
  • Clinical decision support tools for prenatal care
  • Partnerships with hospitals and maternal health providers
  • Platform development & clinical validation

Impact Goals:

  • Detect complications 4-8 weeks earlier than current methods
  • Reduce preventable maternal mortality
  • Make precision maternal care accessible to all communities
  • Empower mothers with data-driven insights