Neurotechnology at Case Western
Welcome to our student-led neurotechnology club at Case Western Reserve University. Join us in exploring the exciting field of neurotech through competitions, workshops, mentorship, and networking opportunities.
BCI Competitions
We plan to attend and possibly host BCI hackathons around the country.
Technical Workshops
Participate in our technical workshops to enhance your neurotech expertise.
Interactive Projects
Form project groups and tackle your own paradigm using our advanced EEG system!
Elevate your workflow by seamlessly integrating our machine learning platform with your existing tools. We understand the importance of collaboration and compatibility, which is why our platform supports a wide array of integrations.
Owen Anderson
Third-year neuroscience, computer science + AI student at CWRU. Researcher at Cleveland Clinic.
Lucas Vorkoper
Third year cognitive science and neuroscience student. Researcher at CWRU school of medicine.
Jarvis Chen
Treasurer
Third year Biomedical Engineering + Electrical Engineering student at Case Western Reserve University. Researcher at Cleveland Clinic.
Mark Shteyn
Technical Mentor
Second year Data Science, Mathematics, and Artificial Intelligence student at Case Western Reserve University. Researcher at SDLE Lab.
Tiger Newman
Secretary
Third year Neuroscience & Pre Medical Student at Case Western Reserve University. Researcher & Nursing Assistant at Cleveland Clinic.
Students from All Backgrounds Welcome — Your Perspective Matters
FOR NEUROSCIENCE STUDENTS
Leverage your knowledge of the brain to interpret neural data.
Neuroscience students play a vital role in understanding how brain activity translates into technology. Contribute to decoding complex EEG signals and connecting neuroscience principles to advanced AI models.
Analyze and interpret neural data to uncover key patterns
Identify and map neural responses to external stimuli
Provide insight into neurological processes for AI-driven research
FOR COMPUTER/DATA SCIENCE STUDENTS
Transform neural data into insights using cutting-edge deep learning.
Computer and data science students are essential for developing machine learning models that can handle the intricacies of brainwave data, optimizing them for real-world applications in neurotechnology.
Develop deep learning models to process complex EEG signals
Create pipelines for efficient data preprocessing and visualization
Implement algorithms to predict neural responses and interactions
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