Lei Ying
(734) 647-4031 4423 EECS1301 Beal AvenueAnn Arbor, MI 48109-2122

News

Fifteen papers by ECE researchers to be presented at the Conference on Neural Information Processing Systems

Topics of accepted ECE NeurIPS papers include diffusion models, large language models, multi-armed bandit models, and more.

Leveraging artificial intelligence for early detection of lung cancer

Predictive models developed by an interdisciplinary U-M research team have improved early lung cancer detection beyond traditional measures, with the potential to save lives.

Fourteen papers by ECE researchers to be presented at the International Conference on Machine Learning

Accepted papers for the ICML conference span topics including deep representation learning, language model fine-tuning, generative modeling, and more.

Linking online and offline social networks to better predict real world impact

Prof. Lei Ying leads a new MURI that is focused on the interplay between online and offline networks and how they could impact disruptive behavior and events.

Congrats ECE alumni who joined academia

Congratulations to these ECE graduates who have recently joined academia as faculty members!

Teaching Machine Learning in ECE

With new courses at the UG and graduate level, ECE is delivering state-of-the-art instruction in machine learning for students in ECE, and across the University

Lei Ying named IEEE Fellow for fundamental research in cloud computing systems and wireless networks

Prof. Ying’s theoretical research addresses a broad range of fundamental problems arising from big-data analytics.

$20M NSF AI-EDGE Institute aims to transform 5G and beyond networks

University of Michigan is a core member of a new NSF-led Institute that is a collaboration between 11 institutions, three government research labs, and four global companies

Tracking COVID-19 spread faster, and more accurately

A new application for an ongoing NSF project could bolster contract tracing efforts.

ECE welcomes four new faculty for 2019

With research expertise in the areas of robotics, computer vision, control systems, and big data – these faculty are working to improve rehabilitation and autonomous systems, make systems safer, and process big data for a wide variety of applications.