Two ECE faculty members have been appointed to named professorships. Alexandra Boltasseva was appointed the Ron and Dotty Garvin Tonjes Professor of Electrical and Computer Engineering. Anand Raghunathan was appointed the Silicon Valley Professor of Electrical and Computer Engineering.

Google is collaborating with a student team at Purdue University to create open-source TensorFlow models. TensorFlow is a deep learning framework created by Google. The student team will implement recently-published algorithms and methods in machine learning. The implementations will be made available through a public repository called “Model Garden” maintained by researchers and engineers from Google.

The Purdue Board of Trustees has approved the creation of a task force focused on achieving equality for all members of the Boilermaker community. ECE alumnus and university trustee Don Thompson (BSEE '84) will chair the Equity Task Force.

The National Science Foundation (NSF) has chosen Purdue University to participate in a new Engineering Research Center dedicated to advancing sustainable, electrified transportation.

Purdue University innovators are working on inventions to use micro-chip technology in implantable devices and other wearable products such as smart watches to improve biomedical devices, including those used to monitor people with glaucoma and heart disease.

Purdue researchers recently received an award from the Army Research Office (ARO) to conduct theoretical and experimental studies on adversarial robustness of deep neural networks. Over the past decade, deep neural networks have made substantial progress in several areas such as computer vision and speech recognition.

A new quantum random walk technique developed by engineers at Purdue University could eventually allow computers to search through data at speeds beyond that of conventional computers.

Imagine that you are taking photos in the dark. No matter how you adjust your camera, the images will likely be too dark and too noisy to let you see anything. Computer vision scientists have been asking two questions for decades: Can we remove the noise to recover the image? Will our computer be able to recognize the objects from the noisy images?

A self-driving car has a hard time recognizing the difference between a toddler and a brown bag that suddenly appears into view because of limitations in how it senses objects using lidar.