Michigan AI Laboratory
Prospective graduate students
This collaborative environment, coupled with our diverse perspectives, leads to a valuable interchange of ideas within and across research groups.
Emotion recognition has a privacy problem – here’s how to fix it
Researchers have demonstrated the ability to “unlearn” sensitive identifying data from audio used to train machine learning models.
Generating realistic stock market data for deeper financial research
A team at Michigan proposed an approach to generating realistic and high-fidelity stock market data to enable broader study of financial markets.
Jenna Wiens recognized with Sloan Research Fellowship
She was recognized for her work harnessing patient data to improve healthcare outcomes.
How can machine learning impact healthcare?
Prof. Jenna Wiens uses machine learning to make sense of the immense amount of patient data generated by modern hospitals. This can help alleviate physician shortages, physician burnout, and the prevalence of medical errors.
Can we trust a robot?
Prof. Benjamin Kuipers discusses how advances in AI and robotics have raised concerns about the impact on our society of intelligent robots, unconstrained by morality or ethics.