Summary
Madison Clark-turner is a Scientist IV and deep learning research scientist with a decade of experience developing perception and inference systems for edge platforms across ground, air, medical, and human-centric domains. As a principal investigator, she has led multidisciplinary teams from proposal writing and product roadmaps to deploying real hardware solutions used in austere environments and high-throughput settings. Her work spans multimodal human intent understanding, multispectral situational awareness, and injury detection—combining video, audio, depth, thermal, and language models to drive robust, sample-efficient learning for robotics. She completed a PhD in Computer Science focused on video-based, sample-efficient deep learning and learning-from-demonstration for real-world robotic tasks, and has translated that research into operational systems for NASA, DARPA, and the Army. Madison pairs academic rigor—evidenced by publications and conference talks at venues like ICRA and iROS—with practical engineering experience from Amazon Robotics and DEKA, making her adept at moving prototypes into production. Based in Newmarket, NH, she is noted for blending temporal representation research with pragmatic multimodal fusion to improve trust and autonomy in collaborative human-robot interaction.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Arts (B.A.) Computer Science and Biology, Bachelor of Arts (B.A.) Computer Science and Biology at Franklin & Marshall College
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of New Hampshire
Japanese