BDSI Faculty and Topics
2017 Faculty
Courses are taught by University of Michigan faculty members from the Departments of Biostatistics, Electrical Engineering & Computer Science, and Statistics:
- Jacob Abernethy (EECS)
- Eytan Adar (EECS)
- Philip Boonstra (BIOS)
- Jason Estes (BIOS)
- Stephen Gliske (NEURO)
- Hui Jiang (BIOS)
- Timothy Johnson (BIOS)
- Kelley Kidwell (BIOS)
- Rod Little (BIOS)
- Harsha Madhyastha (EECS)
- Bhramar Mukherjee (BIOS)
- Kayvan Najarian (CCMB)
- Long Nguyen (STAT)
- Karandeep Singh (NEPH)
- Ambuj Tewari (STAT)
- Lu Wang (BIOS)
- Jenna Wiens (EECS)
- Sebastian Zoellner (BIOS)
2017 Topics
- Data Acquisition, Database Management
- Common computing platform, Linux environment
- Data Structures
- Data Security, Privacy and Linkage
- Data Visualization
- Probability and Statistical Inference
- Cloud, Parallel and Distributed Computing
- Optimization
- Sampling Methods: Markov Chain, Monte Carlo
- Medical Informatics/Computing
- Matrix Computation
- Bias and Confounding, Missing Data, Causal Inference
- Machine Learning, Graphical Models, Sparse Learning with Matrices, Social Network Analysis, Imaging