Distribution of MIDAS affiliate faculty by primary college, school, or unit.
Affiliated Faculty
Yearly faculty collaborations on grant proposals since 2018, facilitated by MIDAS. Image credit: Bernardo Modenesi (MIDAS Data Science Fellow), Beth Uberseder (MIDAS Research Manager), and Ken Reid (MIDAS Data Scientist).
Â
MIDAS works to foster interdisciplinary research collaboration across campus with our community of 550 affiliate faculty members, who come from over 60 U-M departments, and include instructional (tenure / tenure track / lecturer), clinical and research track faculty.
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
Christine Aidala
High-energy quantum chromodynamics
Mojtaba Akhavan-Tafti
data analysis and simulations for investigating solar and interplanetary systems
Raed Al Kontar
Smart and connected products and systems
Fadhl Alakwaa
machine learning, personalized medicine, predictive modeling
J. Trent Alexander
Data rescue, and infrastructure building, record linkage
Amal Alhosban
Semantic web, fault management and wireless network
Todd Allen
Advanced nuclear energy, hydrogen, public policy
Jacob Allgeier
Using ecological theory to help solve conservation problems
Mark Allison
Autonomic control of complex cyberphysical systems
Daniel Almirall
Causal inference for longitudinal data
Karen Alofs
Integrating data on environmental change and ecological communities
George Alter
Metadata for demographic behavior, research transparency and data security
M. Reza Amini
Intelligent transportation, autonomous vehicles, connected vehicles, mobility
Nazanin Andalibi
AI ethics, AI justice, social implications of algorithms and AI
Sardar Ansari
Biomedical Informatics, Deep Learning, Electronic Health Records, Natural language processing, Signal and Image Processing, Wearable Devices, machine learning, optimization
Brian D. Athey
Bioinformatics in psychiatric pharmacogenomics; high-throughput image analysis.