Neuro Eng & Neuro RobotLocation: WEB L110 (WEB L110)
Neuro Eng & Neuro RobotLocation: WEB L110 (WEB L110)
- Association of Clinical and Translation Science . 03/2021 - present. Position : Member.
- Society of Neuroscience. 04/2017 - present. Position : Member.
- Brain-Computer Interface Society. 04/2017 - present. Position : Member.
- IEEE Engineering Medicine and Biology Society. 02/2017 - present. Position : Member.
- Alpha Eta Mu Beta Biomedical Engineering Honor Society. 08/2014 - present. Position : Member.
- Biomedical Engineering Society. 08/2012 - present. Position : Member.
The best way to learn is to teach, and the best teacher is a passionate teacher. As an instructor, my goal is to facilitate student-led learning through a collaborative classroom environment focusing on student-specific applied learning and effective scientific communication.
Student-Led Learning. My objective is to inspire and empower students to be the directors of their own education. To this end, I favor the “flipped-classroom” or “inverted-classroom” approach, where students watch video lectures prior to class in order to maximize the amount of in-class time dedicated to active student-led problem-solving. The flipped classroom has a long and successful history within the University of Utah’s ECE department, dating back to 2007 when Dr. Cynthia Furse pioneered this approach in electromagnetics.
Collaborative Classroom Environment. To establish a collaborative classroom environment, I have students perform group assignments and then present their unique solutions to the rest of the class. This promotes inclusion and peer teaching while simultaneously highlighting diverse learning approaches.
Student-Specific Applied Learning. I strive to make project-based applied learning the ultimate goal of every course. The University of Utah is unique in that a large number of undergraduate students are actively engaged in research and the Office of Undergraduate Research provides numerous resources to undergraduate researchers. This amplifies the benefits of project-based learning by allowing students to apply their knowledge to their ongoing research or to establish a new line of research.
Effective Scientific Communication. Effective communication is crucial for engineers, regardless of their career trajectory. Providing in-class time for students to practice scientific communication, both written and oral, reinforces all other aspects of my teaching philosophy. As students present answers to various homework or exam problems to the class, they become the leaders of their own education, create an inclusive and collaborative environment, and establish a diverse repertoire of learning approaches. Likewise, allowing students to communicate topics of their choice (e.g., their course projects) leverages the unique interests of each student to establish effective and passionate student-teachers.
BME 6440 / ECE 6540
Neural Engineering & NeuroRobotics
This 3-credit course covers tools and applications in the field of Neural Engineering with an emphasis on real-time robotic applications. Neural Engineering is an interdisciplinary field that overlaps with many other areas including neuroanatomy, electrophysiology, circuit theory, electrochemistry, bioelectric field theory, biomedical instrumentation, biomaterials, computational neuroscience, computer science, robotics, human-computer interaction, and neuromuscular rehabilitation. This course is designed around the central idea that Neural Engineering is the study of transferring electromagnetic information into or out of the nervous system. With this framework, the course is divided into three broad segments: neurorecording, neurostimulation and closed-loop neuromodulation. The neurorecording segment includes: invasive and non-invasive recording techniques, signal processing, neural feature extraction, biological and artificial neural networks, and real-time control of robotic devices using neurorecordings. The neurostimulation segment includes: invasive and non-invasive stimulation techniques, signal generation, physiological responses, safety analysis, and real-time stimulation for haptic feedback and for reanimating paralyzed limbs. The closed-loop neuromodulation segment will feature hands-on student-led group projects where students can combine techniques from the first two segments to create various neurorobotic applications. Example applications include bionic arms controlled by thought that restore a natural sense of touch, or neural-links that can decode a person’s thoughts to reanimate a paralyzed limb.
Fundamentals of Robotics & Cyberphysical System
This 3-credit course covers the fundamentals of the sensing, actuation, signal-processing, and control concepts underlying most robots and other intelligent physical systems. Transduction principles governing common sensors and actuators. Basic circuits and principles for the interfacing of sensors and actuators with embedded microcontrollers. Introduction to digital signal processing including intelligent thresholding, low- and high-pass filters, and Kalman filters. Introductory feedback control principles including PID and data-driven machine-learning methods including linear discriminate analysis, multi-layer perceptrons and convolutional neural networks. Hands-on hardware and software component in every lecture period. Final exam consists of a multifaceted team-based robotics competition.
M. M. Iversen, M. R. Brinton, T. S. Davis, J. A. George, “Return of the Jedi Scientist: Feel the Force!,” Faculty for Undergraduate Neuroscience, Summer Virtual Meeting, July 30 – August 1, 2020. DOI: 10.13140/RG.2.2.21687.14241 (Poster)
J. A. George, C. R. Butson, “Training the Next Generation of Jedi Scientists,” Society for Neuroscience, Chicago, IL, October, 19-23, 2019. DOI: 10.13140/RG.2.2.16405.06888/1 (Poster)
J. A. George, C. R. Butson, “Training ‘Jedi Scientists’ to Control Bionic Arms with their Minds,” Utah Biomedical Engineering Conference, Salt Lake City, UT, September 13. DOI: 10.13140/RG.2.2.14253.84964 (Poster)
Proposal Writing & Presentations, “Fellowship/Grant Applications with Q&A,” 2018
Neural Engineering, “Neural Interfacing via Utah Electrode Array and Variants,” 2018
Systems Neuroscience, “Motor Pathways and Spinal Cord Reflexes,” 2018
Graduate Funding Fair, “Kickstart Your Applications," 2018
Neural Engineering, “Introduction to Neural Recording,” 2017
Undergraduate Workshop Series, “Graduate School Applications and Interview Process," 2016