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Data Science Initiative - Events

Upcoming Events

Brain Space Initiative Talk Series: Leveraging biological knowledge: From Brain Mapping to predictive models

September 25, 2020: The Brain Space Initiative Talk Series: Leveraging biological knowledge: From Brain Mapping to predictive models, as part of the activities of the Brain Space Initiative, co-sponsored by the Data Science Initiative, IEEE Signal Processing Society. Presented by Dr. Simon Eickhoff. The long predominant paradigm in neuroimaging has been to compare (mean) local volume or activity between groups, or to correlate these to behavioral phenotypes. Such approach, however, is intrinsically limited in terms of possible insight into inter-individual differences and application in clinical practice. Recently, the increasing availability of large cohort data and tools for multivariate statistical learning, allowing the prediction of individual cognitive or clinical phenotypes in new subjects, have started a revolution in imaging neuroscience.

 

2021 IEEE Data Science and Learning Workshop (DSLW 2021)

June 5-6, 2021: The 2021 IEEE Data Science & Learning Workshop (DSLW 2021), to be co-located with ICASSP 2021, will be held at the University of Toronto on June 05-06, 2021. The workshop is organized by the IEEE Signal Processing Society. It aims to bring together researchers in academia and industry to share the most recent and exciting advances in data science and learning theory and applications. The workshop provides a venue for innovative data science & learning studies in various academic disciplines, including signal processing, statistics, machine learning, data mining and computer vision.

 


Past Events

Collaboration at ICASSP

Collaborative Sessions at ICASSP 2020.

In order to highlight the fact that "Data Science" really comprises a lot of signal processing and cuts across numerous areas within signal processing, the DSI organized two "collaborative sessions in data science" at ICASSP 2020 consisting of papers that consider common problems in data science:

These sessions featured 12 papers with topics ranging from financial engineering to music recommendations to dictionary learning, showcasing the broad range of topics in data science.

 

First TReNDS Neuroimaging Competition

The First TReNDS Neuroimaging Competition: Multiscanner normative age and assessments prediction with brain function, structure, and connectivity

Human brain research is among the most complex areas of study for scientists. With much of the research using MRI scans, data scientists are well positioned to support future insights. In particular, neuroimaging specialists look for measurable markers of behavior, health, or disorder to help identify relevant brain regions and their contribution to typical or symptomatic effects. In this competition, participants predict multiple assessments plus age from multimodal brain MRI features.

  • 3H: Highly complex, heterogeneous, and high-dimensional data
    • 3H: Highly complex, heterogeneous, and high-dimensional data
    • 3R: Robustness, reproducibility, replicability

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