Dalton Moore, Ph.D.

• Applied machine learning models in PyTorch to improve decoders predicting hand movements from brain activity. • Constructed a full-stack data pipeline that decreased processing time for raw data streams of ~1TB/day by >100%. • Served as lead data scientist for the research team and refined the lab’s data processing and analysis infrastructure. • Mentored five junior graduate students in all facets of computational, experimental, and data science techniques. • Led the development of long-term research agendas and coordinated software development projects.

Graduate Researcher / September, 2017 — September, 2023

• Surgically implanted electrodes and recorded neural activity from the brain of marmoset monkeys. • Built a statistical model to predict brain activity from hand movements and network interactions between neurons. Generated ground-breaking findings in the field of motor control through examination of network interactions. • Collaborated with a team of world-leading neuroscientists and engineers to design and advance human brain-computer interfaces allowing paralyzed participants to control robotic arms and hands with brain activity. • Contributed to open-source computer vision tools. • Designed and built the multi-camera data acquisition system that will be used by all future researchers in the lab. • Presented research at high-impact conferences including SFN, AREADNE, and Simian Collective.

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