Elle O'Brien
Behavioral Science, Biological Sciences, Complex Systems, Engineering, Healthcare Research, Informatics, Social Science
Artificial Intelligence, Bayesian Methods, Causal Inference, Computing, Data Mining, Databases and Data management, Information Theory, Machine Learning, Mathematical and Statistical Modeling, Natural Language Processing, Statistics, Survey Methodology
Relevant Projects:

MI Lighthouse COVID-19 vaccination tracking, Data Version Control

Elle O’Brien

Lecturer III; Research Investigator

School of Information

Lecturer III in Information and Research Investigator, School of Information

My research focuses on building infrastructure for public health and health science research organizations to take advantage of cloud computing, strong software engineering practices, and MLOps (machine learning operations). By equipping biomedical research groups with tools that facilitate automation, better documentation, and portable code, we can improve the reproducibility and rigor of science while scaling up the kind of data collection and analysis possible.

Research topics include:
1. Open source software and cloud infrastructure for research,
2. Software development practices and conventions that work for academic units, like labs or research centers, and
3. The organizational factors that encourage best practices in reproducibility, data management, and transparency

The practice of science is a tug of war between competing incentives: the drive to do a lot fast, and the need to generate reproducible work. As data grows in size, code increases in complexity and the number of collaborators and institutions involved goes up, it becomes harder to preserve all the “artifacts” needed to understand and recreate your own work. Technical AND cultural solutions will be needed to keep data-centric research rigorous, shareable, and transparent to the broader scientific community.

View MIDAS Faculty Research Pitch, Fall 2021