Heather D. Couture, Ph.D.
Heather D. Couture has more than 10 years of experience with data-driven image analysis in both academic and industry settings. She has worked on a variety of interdisciplinary R&D projects including digital pathology and planetary science.
Heather completed a B.Math in Computer Science at the University of Waterloo and, through one of five internships, discovered computer vision. This led her to the Robotics Institute at Carnegie Mellon University for a Masters where she worked on methods to detect and geologically classify rocks from images, an autonomous science technology for planetary rovers and for processing returned images.
Local area startup Digitalsmiths (since acquired by TiVo) drew her to the Research Triangle of North Carolina. While at Digitalsmiths she worked on numerous projects to index movies and TV shows - methods that operate behind the scenes to help consumers find the content they're looking for.
Heather then returned to academia and completed a Ph.D. in Computer Science at the University of North Carolina at Chapel Hill. During her dissertation work she developed a low cost and repeatable method for predicting breast tumor biomarkers from H&E histology - some of these biomarkers were previously not known to be predictable from images alone. She also explored models for integrating image and genomic data. More broadly, her research in image recognition and machine learning studied methods for forming discriminative representations for large, heterogeneous images and multimodal data. These techniques are applicable to other disease and image types for applications ranging from improving treatment decisions to better understanding the disease itself. They are also extendable to aid discriminability for many forms of heterogeneous data.
Heather started Pixel Scientia Labs in 2012 to service local companies in need of specialized machine learning and image recognition skills. She has continued to follow the emerging research in this area, with deep learning opening up new possibilities in automated analysis of images. Heather enjoys the challenge of developing custom solutions to unique problems and loves to learn more about the science of each application along the way.