Daniel Merrick

Daniel Merrick began their work experience as a Global Data Insights & Analytics (GDI&A) Intern at Ford Motor Company in 2019. Daniel then worked as an Undergraduate Research Assistant at Purdue University starting in 2018, where they led a team of undergraduate researchers focused on evaluating and improving the consistency of CNN-Object Detectors. In addition, they worked on low-power computer vision systems during their time at Purdue.

After completing their undergraduate studies, Daniel returned to Ford Motor Company in 2020 as a Machine Learning Engineer. In this role, they applied a combination of concepts such as semantic segmentation, object detection, and 3D computer vision to develop high-definition maps for autonomous vehicles. Daniel also optimized the pipelines for HD maps and benchmarked image classifiers in Tensorflow and OpenVino.

Most recently, in 2022, Daniel joined Canopy as a Software Engineer - Perception / ML. In this role, they are responsible for building and deploying machine learning solutions for vehicle security. Daniel has already prototyped and evaluated different hardware solutions for this purpose.

Daniel Merrick attended Purdue University from 2016 to 2019, where they earned a Bachelor of Engineering (B.E.) degree in Electrical and Computer Engineering. In September 2020, they obtained a certification in "Deep Neural Networks with PyTorch" from Coursera. Additionally, they hold a certification as an "Open Water Diver" from PADI, although the exact date of obtaining this certification is unknown.