[BIC-announce] Séminaire UNF _ Dr Anisha Keshavan - Jeudi 31 mai 1pm

[Claude Godbout]

Bonjour,

 

Voici l’annonce du prochain séminaire de l’UNF.

Merci de faire circuler.

 

Claude

Mme Claude Godbout M.Sc.

Coordonnatrice de recherche et de l’UNF

35e_logo_courriel (4)

Centre de recherche de l’Institut universitaire de gériatrie de Montréal

CIUSSS du Centre-Sud-de-l’Île-de-Montréal

4565 chemin Queen-Mary

Montréal (Québec) H3W 1W5

Tél. : 514-340-3540 poste 3633

claude.godbout at criugm.qc.ca

www.criugm.qc.ca

 

SÉMINAIRE DE L’UNF / SEMINAR UNF SERIES

 

 


Présentateur/ Speaker:

Dr Anisha Keshavan


Titre/  Title:

Leveraging Web Technology to address challenges with Big Data in
Neuroscience.


Endroit/ Where:

CRIUGM – Local E1910 (http://www.criugm.qc.ca/en/contact.html)


Date/ When:

Jeudi 31 mai, 13h-14h/ Thursday May 31st 1pm-2pm


 

*La conférence sera présentée en anglais/The seminar will be present in
English

 

 

 

Dr Anisha Keshavan works with Jason Yeatman in Speech and Hearing Sciences
and Ariel Rokem at the eScience Institute. Her research focuses on big data
methods in neuroimaging. Advances in MRI technology and image segmentation
algorithms have enabled researchers to begin to understand the mechanisms of
healthy brain development, psychiatric and neurological disorders. However,
accurately measuring the brain at a scale large enough to accommodate
genetic association and precision medicine studies is challenging; expert
neuroanatomist tracings can take a long time, while automated algorithms are
not accurate enough. Dr Keshavan aims to develop methods to combine the
accuracy of an experts with the speed of computers by incorporating
crowdsourced image segmentation with deep learning algorithms. She received
a doctoral degree in Bioengineering from the UC Berkeley - UCSF Joint
Graduate Program, and a Bachelor's degree in Aerospace Engineering and
Applied Mathematics from the University of California, Los Angeles.

 

Abstract:

Advances in technology have enabled neuroscientists to collect massive
amounts of data to answer important scientific questions. But the drawback
is that we are experiencing a “data deluge”, which has brought about new
challenges that we must overcome in order to truly reap the benefits that
Big Data promises. In this talk, I propose that web technology can help us
overcome big data challenges, and present examples of how this is done in
the field of neuroimaging. First, how web-based data visualization can
address the challenges of high data dimensionality. Second, how web-based
collaborative meta analyses can address the challenge of integrating the
never-ending stream of new results in the research literature. Finally, how
web-based citizen science platforms can address the problem that decisions
made by neuroimaging experts cannot be reliably scaled to large datasets.
Web technology has completely transformed our everyday lives, but we are
only just beginning to unleash its full potential to accelerate scientific
discovery.

 

I hope to see you there / J’espère vous voir nombreux.

 

Pierre Bellec 

Assistant professor/Professeur adjoint sous octroi, Département
d'informatique et de recherche opérationnelle ( <http://diro.umontreal.ca/>
DIRO)

Director/Directeur, Unité de Neuroimagerie Fonctionnelle (
<http://unf-montreal.ca> UNF)

Researcher/Chercheur Centre de recherche de l'institut Universitaire de
gériatrie de Montréal ( <http://www.criugm.qc.ca/> CRIUGM)

Université de Montréal, Montréal, Canada

Phone +1 514 713 5596  

 <http://simexp-lab.org/brainwiki/doku.php?id=pierrebellec> Coordinates/c
<http://simexp-lab.org/brainwiki/doku.php?id=pierrebellec> oordonnées.

 <http://simexp-lab.org> Laboratory/Laboratoire SIMEXP.

 

 

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