Program


The SMI 2020 conference invites submissions of proposals for invited oral sessions and collaborative case study sessions. 

Invited oral sessions: 3 speakers per session. Please include a session title, names and affiliations of the speakers, and titles of the talks.

The collaborative case-studies: it is a long-standing SMI conference tradition to foster interaction and translational communication between statisticians and field collaborators by discussing particular applied problems in imaging science that have been addressed with innovative statistical strategies or that call for new statistical methods.  Please include a session title, titles of the talks, and the names and affiliations of 2-3 speakers. The session can feature a multidisciplinary team of statisticians and field collaborators or 2-3 imaging scientists.

Please submit the proposals to smi2020emory [at] gmail [dot] com. The submission deadline is November 11, 2019. 


Keynote Speaker

Tom Nichols (Professor of Neuroimaging Statistics, Nuffield Department of Population Health, University of Oxford)


Short Course

Introduction to Deep Learning (8:30am-12:30pm on 05/18/2020)

Deep Learning is ubiquitous today across data-driven applications as diverse as machine vision, natural language processing, and super-human game-playing. This half-day workshop will introduce the fundamentals of the main types of deep learning models.  You will also learn the motivation and use cases of deep learning through hands-on exercises using R and Python in the cloud environment. This workshop is designed for the audience with a statistics background. No software download or installation is needed, everything is done through an internet browser (Chrome or Firefox) in Databricks free cloud environment.

Topics:

  •       Feedforward Neural Networks
  •       Convolutional Neural Networks
  •       Recurrent Neural Networks
  •       Deep Learning Hands-on (Python and R)

Instructor: Hui Lin, Head of Data Science at Netlify, 2325 3rd street, Suite 215, San Francisco, CA, 94017, hui [at] netlify [dot] com

Bio: Hui Lin is the head of data science at Netlify where she is leading and building the data science department. Before Netlify, she was a Data Scientist at DuPont. She provided data science leadership for a broad range of predictive analytics and market research analysis from 2013 to 2018. She is the co-founder of Central Iowa R User Group, blogger of https://scientistcafe.com/, and 2018 Program Chair of ASA Statistics in Marketing Section. She enjoys making analytics accessible to a broad audience and teaches tutorials and workshops for practitioners on data science (https://course2019.scientistcafe.com/). She holds an MS and Ph.D. in statistics from Iowa State University.