Courses
| Name | Department and Instructor | Description |
| Bioelectrical Systems | ECEKarim Oweiss |
Covers the theoretical and quantitative perspective of bioelectrical signals reflecting the activity of the brain, the muscles, and the heart. Examines bases of modeling, measuring, processing and analyzing bioelectrical signals and systems, as well as common clinical applications. Laboratory. |
| Neural Signals, Systems and Technology | ECEKarim Oweiss |
Biophysical principles of neural signaling, characterization of neural circuits and systems, technology design principles for interfacing with biological neural systems, overview of clinical applications and industrial opportunities for neurotechnology. |
| Neural Engineering | BMEAysegul Gunduz |
Applying engineering to neuroscience; includes such diverse areas as neural tissue engineering, models of neural function, and neural interface technology. Focuses mainly in the context of neural interfaces and prosthetics, from basic neural physiology and models of neural mechanisms to advanced neural interfaces currently in development or produced commercially. |
| Introduction to Neural Interfaces and Systems (planned for Spring 2024) | ECEAdam Khalifa | The interdisciplinary course focuses on invasive neural implants and covers various types of recording and stimulating neural interface technologies used in animal research and humans. The course examines the neurophysiological principles and computational modeling of neurons, as well as the tissue-electrode interface, to better understand how electrical signals and information are transmitted between the devices and neurons. The course will also cover block diagrams of circuits commonly utilized in neural implants. |
| Neurotechnologies in Education | Ed. Tech.Pavlo Antonenko |
This seminar focuses on the neuroscience frameworks and technologies that are gained popularity in education research as a way to supplement and offset the weakness of self-report data. |
| Future Micro/Nano System and their Applications | ECEJack Judy | Introduction to the wide range of exciting new applications for microscale and nanoscale devices and systems, including transducers, as well as their use in metamaterials, biological science, medical diagnostics, environmental, IoT, biometric cyber security, neural interfaces, multi-functional micro/nanosystems, and other application areas. |
| Neural Networks and Deep Learning | ECEJose Principe | Optimal filters in vector spaces. Linear machines and discriminant functions. Gradient descent in additive neural model. Performance measure of multilayer perceptions and Hopfield. Dynamic neural networks and issues of short-term memory; unsupervised learning; feature extraction, data reduction; machine learning. |
Training
| UF CTSI Translational Workforce Development | The CTSI Translational Workforce Development Program provides educational opportunities that facilitate the training of clinical and basic science investigators, clinical trialists, laboratory technicians, study coordinators and other related personnel required to establish and support multi- and interdisciplinary clinical and translational researchers and research teams |