Services

How I reduce the trial-and-error of machine learning development:

Facilitate knowledge sharing amongst stakeholders, domain experts, and engineers
Guide machine learning engineers to the most effective models and experiments
Handle the challenges of real world data
Follow industry best practices
Create a clear project roadmap
Design generalizable models
Properly validate models
Smoothly navigate through challenges
Help build an interdisciplinary team

Machine Learning Consulting Options

Custom Consulting

Starting at $30,000

Are you struggling to keep your machine learning projects on the path to success? Are you afraid your machine learning project will turn into an endless stream of failed experiments? What if you had a clear ML strategy for your team? I can keep you abreast of the latest research for your application, help you tackle unique data challenges, provide hiring advice, and more. With a custom engagement, we’ll define the scope to meet the needs of your team.

Schedule a call to learn more

Diagnostic

$7,500

Are you confident that your machine learning models are the best ones for your data? Do your models accommodate challenges like domain shifts, noisy labels, heterogeneous images, or small training sets? My Machine Learning Diagnostic provides recommendations to give your team a clear perspective on what your challenges really are and how you can better apply data- and model-centric techniques to create more robust and generalizable models.

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1 Hour Strategy Session

$750

What if you could talk to an expert quickly? Are you facing a specific machine learning challenge? Do you have a pressing question? Schedule a 1 Hour Strategy Session now. Ask me anything about whatever challenges you’re facing. I’ll give you no-nonsense advice that you can put into action immediately.

Schedule now

These services might not be a good fit if you’re only looking for:

How to setup your data infrastructure or annotate your data
Which MLOps tools to use
Model training and validation done for you
Model deployment

Schedule a free Machine Learning Discovery Call to discuss which service is best for you

Work With Me

Don’t Outsource…
Insource - and Empower Your Team

While machine learning certainly can bring new insights, precision, and efficiency, it takes time to build the technology to do it. And the path to a successful solution is generally not linear.

Many companies outsource machine learning projects. While this can be successful for well-defined applications with a limited scope, high impact projects are different. These projects are often part of a company’s core technology, so they prefer to keep the intellectual property development in house. But they may not have navigated the unique complexities of a machine learning project before. I can help you build the technology and your team in house, ensuring a smoother path to success.

My goal is not just to get you to an ideal solution but to ensure your team also understands how it works so that they can modify it and adapt to new challenges that arise. I will be there to help you navigate these obstacles as needed, but I consider my role most successful if I have transferred this knowledge to your team.

Our team was fortunate to work with Heather on a short-term project, where she was a critical contributor to establishing a framework for future studies.

Keith Wharton Ultivue, VP Medical Director

Working with Heather and Pixel Scientia Labs was a great choice for us because of her extensive experience in cancer detection, imaging, and machine learning. Based on this background and expertise, she was able to support the team as we worked to empower our imaging solutions through AI and machine learning.

Alan Kersey, CytoVeris, President & CEO

Heather’s knowledge of the current state of the art within the digital pathology field is second to none. Discussions of prior art enabled our team to focus on novel research and refine our current AI methodologies for clinical research.

Build an Interdisciplinary Team

I’ve worked with teams spanning many different disciplines and the best results tend to come from a combination of

Pathologists, remote sensing scientists, or other domain experts who understand the data and how it is collected,
Data engineers who gather and organize it,
Machine learning engineers who train and analyze models, and
Software engineers who bring all the pieces together and create a robust system.

Due to the interdisciplinary nature of teams, communication is key.

I can help you in building this team. We start by setting reasonable goals for the project and determine the resources needed. From initial models, I then assess possible next steps including gathering and labeling more data, cleaning data, extending models, and improving computational efficiency. More resources (human or computer) may be needed as the project progresses.