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The official Jupyter Conference
August 22-23, 2017: Training
August 23-25, 2017: Tutorials & Conference
New York, NY
Demba Ba

Demba Ba
Assistant Professor of Electrical Engineering and Bioengineering, Harvard University

Demba Ba is an assistant professor of electrical engineering and bioengineering at Harvard University, where he directs the CRISP group. He and his group develop mathematical and computational tools to elucidate the role of dynamic networks of neurons in phenomena such as anesthesia, sleep, the learning of fear, and aging and to enable more efficient signal representations that exploit the structure present in natural media such as audio, images, and video. Demba is passionate about teaching, and eagerly incorporates Jupyter notebooks and the Python ecosystem in his courses because of the unique opportunity they provide for interactive, web-based teaching of content that has not traditionally leveraged scientific computing resources. Attempting to bridge the gap that has existed between theory and pen-and-paper courses and application- and coding-focused classes, he spearheaded the development and deployment of the JupyterHub Notebook on Amazon AWS cloud for two classes in Harvard’s School of Engineering and Applied Sciences. In 2016, Demba received a research fellowship in neuroscience from the Alfred P. Sloan Foundation. He holds a BSc in electrical engineering from the University of Maryland, College Park, and both an MSci and a PhD in electrical engineering and computer science with a minor in mathematics from the Massachusetts Institute of Technology.

Sessions

10:05am–10:25am Thursday, August 24, 2017
Location: Grand Ballroom
Demba Ba (Harvard University)
Average rating: *****
(5.00, 3 ratings)
Demba Ba discusses two new signal processing/statistical modeling courses he designed and implemented at Harvard, exploring his perspective as an educator and that of the students as well as the steps that led him to adopt the current cloudJHub architecture. Along the way, Demba outlines the potential of architectures such as cloudJHub to help to democratize data science education. Read more.