Texas ECE PhD student Tianlong Chen is the lead author of a study in artificial intelligence that posits that hidden within massive neural networks, leaner subnetworks exist that can complete the same task more efficiently. The study is co-authored by Texas ECE assistant professor Zhangyang "Atlas" Wang with others.

His research competition title is "Light in Artificial Intelligence: Efficient Neuromorphic Computing with Optical Neural Networks”.

The award is the highest recognition for research achievements in Data Mining, and is annually given to one individual or one group who has made influential research contributions to the field of Data Mining. 

Akinwande’s device falls under the category of memristors, a popular area of memory research, centered around electrical components with the ability to modify resistance between its two terminals without a need for a third terminal in the middle known as the gate.

A new device created by researchers at The University of Texas at Austin can overcome challenges like bad weather to deliver more secure, reliable communications.

A new light-emitting-diode (LED) could greatly improve the cost and efficiency of remote sensing systems and infrared screens.

The team received a five year, $2.97 million grant from the National Institute of Diabetes and Digestive and Kidney Diseases to address this problem.

Prof. Atlas Wang of Texas ECE received a Data Science research Award from Adobe for his work on “Towards Automated Design of Efficient Deep Multi-Modal Recommendation Models.”

Intel's Rising Star Faculty Award program selects 10 university faculty members who show great promise in developing future computing technologies.

Texas ECE professor Ananth Dodabalapur and Praveen Pasupathy, a research associate in Texas ECE, along with chemistry professor Eric Anslyn have received a $1 million grant from the W.M. Keck Foundation to create a new data storage and retrieval paradigm centered around synthetic polymers.