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Welcome to the U-M Big Data Summer Institute 2021 Wiki!

Lectures

Week 1

• Study Design and Inference, Observational Data and Bias, Parameter Estimation and Likelihood - Dr. Rod Little

    -Part 1, Part 1 Slides
    -Part 2
    -Part 3
    -Part 4
    -Part 5

• Linear Algebra - Lap Sum Chan

    -Recording

• Linear Regression - Fatema Shafie Khorassani

    -Recording

• Probability - Rupam Bhattacharyya

    -Recording

• Data Wrangling in R with dplyr - Dr. Matthew Flickinger

    -Lecture Slides

• Data Visualization in R with ggplot2 - Dr. Matthew Flickinger

    -Lecture Slides

Week 2

• Machine Learning - Dr. Jenna Wiens
• Data Mining - Jiong Zhu
• Logistic Regression - Aubrey Annis

    -Recording

• Generalized Linear Models - Aubrey Annis

    -Recording

• R Markdown - Dr. Phil Boonstra

    -Synchronous Lecture Recording

• Python - Dr. Fred Feng

    -Synchronous Lecture Part I and II Recording
    -Synchronous Lecture Part III and IV Recording

Week 3

• Assessment of Predictive Models - Dr. Phil Boonstra

    -Recording

• Causal Inference - Dr. Walter Dempsey
• Model Selection - Nicky Wakim

    -Recording
    -Model Selection Slides
    -Annotated Model Selection Slides

Week 4

• Introduction to Bayes - Dr. Xiaoquan William Wen
• Missing Data - Dr. Peisong Han
• Clustering - Fahad Kamran

Week 5

• Social Networks - Dr. Eytan Adar
• Electronic Health Records - Dr. Xu Shi
• Genetics/Genomics - Dr. Jean Morrison
• Health Disparities in Strokes - Dr. Lynda Lisabeth
• Precision Health - Dr. Sachin Kheterpal

Week 6

• Data Integration and Precision Medicine - Dr. Veera Baladandayuthapani
• Radiation Oncology - Dr. Arvind Rao
• Better, Not Just Bigger Data Analytics - Dr. Brahmajee Nallamothu
• Clinical Trials - Dr. Kelley Kidwell

Week 7

• Preparing for Graduate School - Dr. Kelley Kidwell
• CVs and Resumes - Krystle Forbes
• Scientific Writing - Dr. Brett Griffiths
• Pick Me! - Dr. Brett Griffiths

Journey Lectures

• Week 1: Dr. Michael Boehnke
• Week 2: Dr. Mousumi Banerjee

Past BDSI Student Poster Presentations

2019 Student Poster Presentations

• Data Mining Presentation
• Machine Learning Presentation
• Genomics Presentation

2018 Student Poster Presentations

• Imaging Group Presentation
• Machine Learning Group Presentation
• Genetics Group Presentation
• Data Mining Presentation

2017 Student Poster Presentations

• Data Mining/ Machine Learning
• Electronic Health Records (EHR)
• Genomics
• Imaging

2017 Symposium Lecturers

• A Time-to-Event Analysis of Heart Failure via Electronic Health Records
• Melanoma Detection by Classifying Skin Lesion Images
• Classifying Skin Lesions Images Using Adaptive Boosting
• Machine Learning Classification of Skin Lesion Images
• Genomics: Genome Storage and Assembly
• Predicting the Transcriptome from the Genome
• Classification of Cell Types from Peripheral Mononuclear Blood Cells
• EHR-Based Study of Long-Term Infectious Diseases
• Visualizing Lab and Phenotype Associations Using PheWAS and Electronic Health Records
• Data Mining: Microenvironment Microarray Spot Based Approach for Cell Prediction
• Estimating Cell Growth with Machine Learning and Data Mining

Additional Resources

• Daily Schedule
• Social Events Schedule