Computer Vision for People & Planetary Health

Reducing the trial-and-error of model development

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Frustrated by the never ending cycle of model development?

  • Lacking technical credibility in AI?
  • Unsure whether you’re focusing on the best model types for your application?
  • Worried about how to mitigate the ethical concerns of AI?
  • Struggling to keep up with the rapidly advancing field?

Get to market faster with less wasted time on unsuccessful approaches

  • Understand and communicate technical details to investors and end users
  • Create a realsitic modeling roadmap and risk assessment
  • Develop unbiased models that provide the most valuable insights
  • Keep up with AI trends and innovations

Here are three ways I can help...

Strategy Session

A one hour call to get practical advice to move your project forward

Foundation Model Assessment

Get a clear perspective on whether your team can benefit from a domain-specific foundation model

Modeling Roadmap

A strategic roadmap outlining the components you’ll need to make your project a success

Hi, I’m Heather Couture, and I accelerate computer vision projects with evidence-driven model development

While working with a variety of organizations on computer vision projects, I’ve witnessed the long and iterative development cycles. Every dataset is different, so it does take some experimentation to get a robust model.

But some of this experimentation could be reduced by following three key principles:

  • Identifying sources of variation or other data challenges – domain experts are essential for this
  • Understanding prior work – a literature review can find candidate solutions and unresolved challenges
  • Validating early and often to reveal failure modes – essential for making improvements

Model development progresses much faster and smoother when you understand the challenges in your dataset and can try solutions that have worked for others on similar data. And proper validation can focus your efforts to improve your models and help you recognize major obstacles earlier.

I guide organizations in following these principles. Given the unique characteristics of a dataset, I help them identify the best path to robust and generalizable models, enabling them to take their products to market sooner.

Organizations I've Worked With

Enspectra Health
Zaya AI
Digital Smiths

Why work with me?

Proven Track Record

Accelerated CV/ML projects for more than 15 clients – mostly seed or early stage startups.

Domain Knowledge

Heavily focused on microscopy and satellite imagery, providing deep insights and the ability to collaborate across disciplines.

State-of-the-Art Expertise

20 years of experience in CV/ML
PhD in Computer Science
15+ peer-reviewed publications