Devon Martin, Ph.D Email & Phone Number

Coming from a strong STEM background, I have a great appreciation for the scientific method and uncovering the best approximation of the truth. As a pragmatist, I enjoy applying my knowledge to the real-world applications we encounter in the lab every day. I am passionate about challenging myself and have focused on studying multi-sensor data fusion as a balance between improved accuracy and filtering out an ever-more-present noise signal.I’ve worked in biotech for several years in Research Triangle Park, NC. In a field dominated by biologists and chemists, I found a niche in database design and data analysis. I shifted focus to the coming internet-of-things (IoT) revolution and issues with large deployments of sensor systems, which I explored with the iBionicS lab at North Carolina State University under Dr. Alper Bozkurt. Here, I focused on applications of multi-sensor data fusion to agriculture and animal welfare applications.My present work focuses on applying deep learning, kernel methods, and computer vision to projects on canines to predict behavior from tail motion analysis and collar-based sensor systems. I am wrapping up several projects and transferring my methods for the iBionicS lab as a postdoc. I recently accepted a position as a Systems Engineer with Northrop Grumman’s Future Technical Leaders program, which will commence this August. Topics of interest include RADAR and electronic warfare.I graduated with my PhD in Electrical Engineering in the Spring of 2024, with a dissertation on applying multi-sensor data fusion to agriculture and animal welfare. My projects include 1. a Python package for rapid prototyping of data fusion pipelines complete with a CI/CD framework using Github Actions; this will improve the speed of testing different fusion methodologies 2. predictions of canine action states from IMU, audio, and environmental sensors data with 40% accuracy in a 10-state system; these help Guiding Eyes for the Blind evaluate their seeing eye dogs 3. improving a computer vision system using a Region-based CNN to collect canine tail location motion and further process the tail wag signal for veterinary ethology studiesMy project experience has ranged from IoT, app design, GUI, advanced function modeling, feature extraction, data quality analysis, biological signal analysis, and computer vision. Naturally, I have developed many soft skills over the years too, including a collaborative attitude, teamwork, and leadership. My recent winnings in hackathons is a testament to my ability to play to people’s diverse strengths.