Around 280 U-M faculty members from over 60 departments are affiliated with MIDAS.

Use this box to search by name, department, or other keyword. Use the filters below to search by major data science methodologies or applications.


Filter

Methodologies

Applications

Filter by last name:

  • All
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • X
  • Y
  • Z

Srijan Sen

Gene-environment interaction and their effect on stress, anxiety and depression

Prasad R. Shankar

Patient-centered high-value radiology through big data

Matthew Shapiro

Improving the quality of national economic statistics

Taysseer Sharaf

Developing statistical methods using artificial intelligence

Kerby Shedden

Applied statistics, data science and computing with data

Siqian Shen

Optimization and risk analysis of energy, cloud-computing and transportation, healthcare

Jie Shen

Digital diagnosis of material damage based on large-scale data

Shu-Fang Shih

Theory-based health programs for the public

Yuki Shiraito

Bayesian statistical models and large-scale computational algorithms for political science

Ginger Shultz

Analysis of course placement, skills transfer and scientific reasoning

Yajuan Si

Bayesian, confidentiality protection, missing data, statistics, survey

Kathleen Sienko

Automating and Personalizing Home-Based Balance Training

Mehrdad Simkani

Rational approximation in the complex domain

Stephen Smith

Using large data to examine rates and modes of evolution

Peter X. K. Song

Theory and methodology for environmental health sciences and nutritional sciences

Reza Soroushmehr

Algorithm design and implementation for healthcare