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Dec
2
Fri
HEMI Seminar: Jay Gould
Dec 2 @ 3:00 pm – 4:00 pm

Jay Gould, professor of photography at Maryland Institute College of Art and HEMI’s 2016 Artist in Residence, will present a variety of new projects that depict and react to the research being done at HEMI in preparation for an exhibition at the MSE Library in April, 2017.

Using a wide range of media and processes, this work reimagines HEMI’s research using playful analogies, unique narratives and unexpected lab documentation, inviting audiences to admire the depth and fascination that extreme materials represent.

About

Photo of Jay GouldGould received his BFA from the University of Wisconsin and his MFA in photography from the Savannah College of Art and Design. His work, which integrates scientific topics into installation, and constructed photographic projects, is widely exhibited and has won numerous national awards, such as the Berenice Abbott Prize and the Magenta Foundation’s Flash Forward Festival.

2016 HEMI and MICA Extreme Arts Program Open House
Dec 2 @ 4:00 pm – 6:00 pm
2016 HEMI and MICA Extreme Arts Program Open House @ Malone G33/35

The Extreme Arts Open House provides an opportunity for representatives from HEMI and Maryland Institute College of Art (MICA) faculty and students to learn about each other’s research interests and explore potential synergies for either the Artist in Residence program or the Summer Project/Internship.

The event is free. Researchers from HEMI will be onsite and available to discuss their interests in possible collaboration within, but not limited to, the following areas:

  • Data visualization
  • Interpretation, translation, and/or effective communication of large amounts of data
  • Response to research regarding HEMI ‘extreme’ events, collaborations, interdependent systems through:
    • Storyboarding and narrative
    • Animation
    • Photography
    • Graphic Design and graphics
    • Interactive arts or products
    • Games
    • Information visualization
    • Illustration
    • Drawing
    • Painting
    • Sculptural forms or materials

To view a list of potential HEMI researchers, click here.

If you have any questions regarding the event, please contact Ms. Bess Bieluczyk, bess@jhu.edu or (410) 516-7794.

Information for attendees:

If you are traveling by car, visitor parking is available in the South Garage. If you are using a GPS system for directions, the best address to use in 3101 Wyman Park Drive.

Malone Hall (#45 on the map) is located between Mason Hall and Hackerman Hall on the Johns Hopkins University campus.

Mar
7
Tue
ICM Distinguished Seminar presents “An Adaptable Framework to Extract Abnormal Brain Networks”
Mar 7 @ 11:00 am – 12:00 pm
ICM Distinguished Seminar presents "An Adaptable Framework to Extract Abnormal Brain Networks" @ Clark Hall 110, Johns Hopkins University Homewood campus

Archana Venkataraman, assistant professor of electrical and computer engineering at Johns Hopkins University, will present “An Adaptable Framework to Extract Abnormal Brain Networks” as part of the Institute for Computational Medicine‘s Distinguished Seminar Series. The seminar begins at 11 a.m. in 110 Clark Hall on March 7.

Click here to view the webcast.


Abstract

There is increasing evidence that complex neurological disorders reflect distributed impairments across multiple brain systems. These findings underscore the importance of network-based approaches for functional data. However, network analyses in clinical neuroimaging is largely limited to aggregate measures, which do not pinpoint a concrete etiological mechanism. In contrast, I will present a novel Bayesian framework that captures the underlying topology of the altered functional pathways.

In the first part of this talk, I will introduce our core framework to extract abnormal network foci from functional MRI data. This model relies on a latent structure, which captures hidden interactions within the brain; the latent variables are complemented by an intuitive likelihood model for the observed neuroimaging measures. The resulting variational EM algorithm produces clinically meaningful results by simultaneously localizing the centers of abnormal activity and the network of altered connectivity. Next, I will address three technical challenges: flexible network topology, multimodal integration and patient-specific analysis. I will demonstrate that our core framework can elegantly be adapted to each of these scenarios and yields novel insights into autism, schizophrenia and epilepsy, respectively. Finally, I will highlight some exciting future directions for our methodology that revolve around clinical understanding and interventions.

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