Who will you meet ?

Speaker

Dr. Xiaodong Qu Assistant Professor of Practice

Assistant Professor of Practice

The George Washington University, School of Engineering and Applied Science Professor Xiaodong Qu’s expertise lies at the intersection of Machine Learning and Brain-Computer Interfaces. His research focuses on developing neuro-inspired algorithms for time-series data, such as Recurrent Neural Networks (RNNs) and Transformer models. On the brain signal side, Dr. Qu specializes in non-invasive techniques, particularly Electroencephalography (EEG), for both clinical and non-clinical applications. His work has been applied to critical areas such as mental health and cognitive neuroscience, with ongoing collaborations with Harvard Medical School and GW Hospital. Dr. Qu holds a Ph.D. in Computer Science from Brandeis University and has mentored numerous students to achieve publications at top computer science conferences. For more details about Dr. Qu’s academic profile and research, please visit his faculty profile page: https://faculty.cs.gwu.edu/xiaodongqu/
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Speaker

Katherine Hugins

Associate Director, Admissions & International Partnerships

The George Washington University School of Engineering and Applied Science (GW Engineering) Katherine Hugins is the Associate Director of Admissions & International Partnerships at The George Washington University’s School of Engineering & Applied Science. With over seven years of experience in graduate admissions, she specializes in international recruitment and partnership building. Katherine previously served as Assistant Director of International Graduate Admissions, playing a key role in enrollment strategies for global students. She is dedicated to facilitating smooth admission processes for diverse applicants.
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Who will you meet ?
speaker
Dr. Xiaodong Qu Assistant Professor of Practice

Assistant Professor of Practice

The George Washington University, School of Engineering and Applied Science Professor Xiaodong Qu’s expertise lies at the intersection of Machine Learning and Brain-Computer Interfaces. His research focuses on developing neuro-inspired algorithms for time-series data, such as Recurrent Neural Networks (RNNs) and Transformer models. On the brain signal side, Dr. Qu specializes in non-invasive techniques, particularly Electroencephalography (EEG), for both clinical and non-clinical applications. His work has been applied to critical areas such as mental health and cognitive neuroscience, with ongoing collaborations with Harvard Medical School and GW Hospital. Dr. Qu holds a Ph.D. in Computer Science from Brandeis University and has mentored numerous students to achieve publications at top computer science conferences. For more details about Dr. Qu’s academic profile and research, please visit his faculty profile page: https://faculty.cs.gwu.edu/xiaodongqu/
chevron_right
speaker
Katherine Hugins

Associate Director, Admissions & International Partnerships

The George Washington University School of Engineering and Applied Science (GW Engineering) Katherine Hugins is the Associate Director of Admissions & International Partnerships at The George Washington University’s School of Engineering & Applied Science. With over seven years of experience in graduate admissions, she specializes in international recruitment and partnership building. Katherine previously served as Assistant Director of International Graduate Admissions, playing a key role in enrollment strategies for global students. She is dedicated to facilitating smooth admission processes for diverse applicants.
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About the Masterclass

This session will explore 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 will share insights from his extensive teaching and research experience, highlighting how advanced models like transformers are being utilized to analyze clinical data. With a strong emphasis on real-world applications, Dr. Qu will discuss how his machine learning course—an elective in the CS master’s program at GW—has led to twelve of his students publishing seven papers in top-tier conferences over the past three years. Attendees will also learn about ongoing interdisciplinary collaborations with leading medical institutions like Harvard Medical School and GW Hospital, and how these partnerships are advancing the use of machine learning in healthcare. The session will conclude with a Q&A where students can inquire about research opportunities, the admissions process, and the potential for hands-on projects in the master's program.

What will you learn ?

Machine Learning Fundamentals

Deep Learning Techniques

Real-World Applications

EEG Data Analysis

Machine Learning Fundamentals

Deep Learning Techniques

Real-World Applications

EEG Data Analysis

Exclusive Benefits

Expert career advice

Improved Diagnostic Accuracy

Interdisciplinary Collaboration

Innovative Learning Environment

Expert career advice

Improved Diagnostic Accuracy

Interdisciplinary Collaboration

Innovative Learning Environment

Register Now

George Washington University | School of Engineering & Applied Science

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Located at the heart of the Washington, D.C. Metropolitan Area, the George Washington University School of Engineering and Applied Science (GW Engineering) is a beacon for transformative education, research, and innovation. Driven by a deep commitment to interdisciplinary collaboration, GW Engineering empowers students to become tomorrow's problem-solvers, equipping them to address the world's most pressing challenges. Ranked among the top engineering schools, GW Engineering boasts an impressive network, with nearly 300 leading companies such as Amazon, Cisco, Google, and The World Bank actively recruiting its graduates. With its unique location in Washington, D.C., the school leverages its proximity to government agencies, businesses, and international organizations, empowering students and faculty to make impactful contributions globally. SEAS prioritizes ethical leadership, academic excellence, and the pursuit of innovation in the service of humanity.

Programs Offered

M.S. Biomedical Engineering

M.S. Civil & Environmental Engineering

M.S. Computer Engineering

M.S. Computer Science

M.S. Cybersecurity in Computer Science

M.S. Data Analytics

M.S. Electrical Engineering

M.S. Engineering Management

M.S. Mechanical & Aerospace Engineering

M.S. Systems Engineering

Ph.D. Biomedical Engineering

Ph.D. Civil & Environmental Engineering

Ph.D. Computer Engineering

Ph.D. Computer Science

Ph.D. Electrical Engineering

Ph.D. Engineering Management

Ph.D. Mechanical & Aerospace Engineering

Ph.D. Systems Engineering

Register Now

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Connect with us

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Frequently Asked Questions

Get all your questions answered about SEED !

The masterclass is absolutely free of charge to attend for prospective Master's & MBA aspirants! However since we have limited capacity, we encourage you to sign up as early as possible
You will get to learn about the programmes offered, application advice, career and scholarship opportunities directly from university representatives and admissions officers.
We will provide a recording (YouTube Link) of the webinar to registered attendees.
You can submit your questions through the webinar platform's Q&A feature. We will address as many questions as possible during the Q&A session.
The application fee waiver can be used for applying to the school. Instructions on how to redeem the application fee waiver will be provided to webinar attendees.
You will need a stable internet connection and a device (computer, tablet, or smartphone) with a compatible web browser.

Contact us

For any queries, please feel free to reach out to us!

email
Email

info@seedglobaleducation.com

call
Phone

+918591624998