Machine Learning and Deep Learning for Electroencephalography (EEG)-based Brain Signal Analysis
AI-Powered Insights: Machine Learning and Deep Learning in EEG Analysis
Who will you meet?
About the Masterclass
This session explored the rapidly evolving field of machine learning, with a particular focus on deep learning techniques applied to Electroencephalography (EEG)-based brain signal analysis. Professor Xiaodong Qu shared insights from his extensive teaching and research experience, highlighting how advanced models like transformers were utilized to analyze clinical data. With a strong emphasis on real-world applications, Dr. Qu discussed how his machine learning course - an elective in the CS master's program at GW - had led to twelve of his students publishing seven papers in top-tier conferences over the past three years. Attendees also learned about ongoing interdisciplinary collaborations with leading medical institutions like Harvard Medical School and GW Hospital, and how these partnerships were advancing the use of machine learning in healthcare. The session concluded with a Q&A where students could inquire about research opportunities, the admissions process, and the potential for hands-on projects in the master's program.
What will you learn?
Deep Learning Techniques
EEG Data Analysis
Machine Learning Fundamentals
Real-World Applications
Exclusive Benefits
Expert career advice
Improved Diagnostic Accuracy
Innovative Learning Environment
Interdisciplinary Collaboration
George Washington University | School of Engineering and Applied Science
The George Washington University is a private federally chartered research university in Washington, D.C. Founded in 1821 by the United States Congress, GW is the largest institution of higher education in the District of Columbia. The George Washington University School of Engineering and Applied Science (GW Engineering) promotes an interdisciplinary, impact-oriented approach to teaching, research, and innovation. GW Engineering partners with other GW schools as well as with companies and government agencies throughout D.C. and around the world to connect engineering to other disciplines, responsibly translating innovations to society. These approaches position GW students for leadership and leverage the power of engineering and computing to achieve societal impact. GW Engineering offers a breadth of expertise in engineering and computer science by offering master’s and doctoral degree programs. GW Engineering strives to create a vibrant atmosphere, providing for interaction and joint ventures among faculty, students, and the abundant resources of scientists and facilities available in the Washington, D.C. Metropolitan Area.
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