Texas ECE held a Virtual Honors event on Tuesday, December 8 to honor students in the graduating class of Fall 2020.

"We celebrate your accomplishments and thank everyone who has made your journey possible, your family and friends, everyone who’s been a source of inspiration and support during this successful, yet not always easy, journey," Said department chair and professor Diana Marculescu. "Congratulations on this wonderful achievement – you’ve made it!"

Their project intends to develop new computational microscopy techniques for reconstructing a sample’s 3D light scattering potential, in order to completely characterize the multiple-scattering behavior of light that passes through a sample and use it to digitally correct scattering effects.

Prof. Deji Akinwande of Texas ECE has been elevated to a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) for 2021 for "contributions to wafer-scale graphene synthesis and application to flexible devices."

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. 

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

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.

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 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.”