Jill Nelson
Papers
4
Total Citations
45
H-Index
3
About
Jill Nelson is a pioneering researcher at the intersection of cognitive neuroscience and artificial intelligence, with her primary focus on mental workload classification using functional near-infrared spectroscopy (fNIRS). Her most impactful contribution, the 2019 paper "Mental Workload Classification From Spatial Representation of FNIRS Recordings Using Convolutional Neural Networks," has garnered 32 citations and established a foundational approach for designing adaptive human-computer interfaces. This work is critical for enhancing safety and operator performance in high-stakes fields such as aerospace and robotic surgery. Nelson further advanced this domain with her 2021 study applying recurrent convolutional neural networks for mental workload assessment. More recently, she has expanded into STEM education, developing a hands-on program for biologically inspired maritime robotics that introduces high school students to underwater robotics using lighter-than-air vehicles. Her 2024 publications document both the program's development and valuable lessons learned, reflecting her commitment to making complex engineering accessible to young learners. Nelson's work bridges cutting-edge neurotechnology with practical educational outreach, demonstrating a rare ability to translate sophisticated research into tangible societal benefits.
Research Focus
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Top Papers
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