The Statistical Methods in Imaging (SMI) conference is the annual meeting of the American Statistical Association (ASA) Statistics in Imaging Section. The conference aims to bring together statisticians and imaging researchers working on methodology, theory, and applications in imaging science. The SMI 2021 conference will be held virtually from May 17-19, 2021.
Conference Sessions
The SMI 2021 conference includes:
Founders Talk
Keynote Speakers
Invited oral sessions
The collaborative case-study sessions
Shorts course
Poster Session and Opening Mixer
Visit our conference website scholarblogs.emory.edu/smi2021 for more information about registration and the complete program of speakers. Registration for the SMI 2021 Conference has been extended to Noon (12:00pm EST) on 05/07/2021.
Agenda
Founders Talk
Timothy Johnson
Professor, Department of Biostatistics, University of Michigan
Keynote Speakers
Tom Nichols "Statistical Challenges and Opportunities in Population Neuroimaging"
Wellcome Trust Senior Research Fellow at the Big Data Institute, and
Professor of Neuroimaging Statistics, Nuffield Department of Population Health,
University of Oxford
Vince Calhoun
Director, Tri-institutional Center for Translational Research in Neuroimaging and Data Science
Short Course
Introduction to Deep Learning
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, is currently a Quant Researcher at Google. Before Google, Hui held different roles in data science. She was the head of data science at Netlify, where she built and led the data science team, and a Data Scientist at DuPont, where she did a broad range of predictive analytics and market research analysis. She is the blogger of https://scientistcafe.com/ and the 2018 Program Chair of ASA Statistics in Marketing Section. She enjoys making analytics accessible to a broad audience and teaches tutorials and workshops for data science practitioners. She holds MS and Ph.D. in statistics from Iowa State University.
The Complete Program includes:
Statistical Software for Imaging Analysis sessions
Speakers in Invited Oral Sessions
Speakers in Collaborative Case-Studies
Poster Session and Opening Mixer
Event Type
- Affiliate Award Fund Eligible
- NISS Sponsored
Host
Sponsor
Website
Location
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