Machine Learning

From the internships that inspired her interest in signal & image processing and machine learning to late night study sessions at the Duderstadt to her background in classical dance, Master’s student Rucha Apte shares her journey with us.

Qu’s research has applications in imaging sciences, scientific discovery, healthcare, and more.

Prof. Mingyan Liu is a key member of a project to mitigate bias in Artificial Intelligence and Machine Learning systems for long-term equitable outcomes.

To improve the prediction and identification of stem-like cancer cells, Prof. Euisik Yoon’s group developed a method that is 3.5 times faster than the standard approach.

Zhang is working to improve data security and address important ethical issues related to AI and discriminatory data sets.

Kim takes an interdisciplinary approach to tackle challenges in heterogeneous classes of energy-efficient and versatile communication systems.

Prof. Hun-Seok Kim helped design iGYM, an augmented reality system that allows disabled and able-bodied people to play physical games together.

Prof. Euisik Yoon and his team developed a new machine learning tool that enables large-scale testing of cancer drug effectiveness with microfluidics.

Hero and Lindquist took a few minutes to talk about the impact of machine learning on Signal Processing and Control Systems, and what they plan to do about it

Her research deciphering messy data sets will first tackle applications in genetics and computer vision.

Zhang is recognized with the Chia-Lun Lo Fellowship for his work designing hardware solutions that could help support computer vision and machine learning.

Inspired by startup funding models, Michigan Engineering reinvents its internal R&D grant structure.

The most exciting use of AI for me focuses around a better collective use of our available resources, says Corso.

Mingyan Liu, recipient of the 2018 Distinguished Innovator of the Year award, gave a talk about her startup company and participated on a panel discussing data science commercialiation.

Students in EECS 556: Image Processing, explore methods to improve image processing in applications such as biomedical imaging and video and image compression

Wagenmaker will utilize the award as he pursues his doctoral degree at the University of Washington.

DARPA is trying to build a system that can turn large data sets into models that can make predictions, and U-M is in on the project.

Liu’s most recent research involves online learning, modeling of large-scale internet measurement data, and incentive mechanisms for security games.

The goal of Steven’s research is to improve vision-based perception systems on cars and to create an extra layer of safety.

Prof. Corso believes that this research could make it easier to search for certain types of videos on the web.

Prof. Scott’s research is in the field of machine learning, and his paper builds upon “supervised pattern classification.”

Michigan is one of seven universities IBM is partnering with to give students access to the technology.