News
Feb 26, 2026
New Biomimicry Technology Can Increase Safety in Autonomous Vehicles
New research from Electrical and Computer Engineering Professor Ravinder Dahiya has the potential to make self-driving cars safer. This new technology mimics how a human retina analyzes images by using synaptic transistors, devices used to simulate neural pathways, that significantly reduces processing time to machines like autonomous vehicles.
Feb 24, 2026
Patent for a Faster and More Efficient Way to Create High Definition Images
ECE Distinguished/Khoury Professor Yun Raymond Fu was awarded a patent for “System and method for image super-resolution.”
Feb 17, 2026
Yehoshua Publishes Book on Machine Learning Foundations
ECE Associate Teaching Professor Roi Yehoshua published a book on “Machine Learning Foundations, Volume 1: Supervised Learning.”
Feb 17, 2026
2026 Goldwater Scholarship Nominees
Megan Farrington, E’27, electrical engineering and physics, and Maren Ritterbuck, E’27, bioengineering and biochemistry were nominated for the 2026 Barry Goldwater Scholarship—a highly competitive, merit-based award for outstanding students in mathematics, the natural sciences, and engineering who are interested in pursuing careers in research.
Feb 17, 2026
Patent for Faster and More Efficient AI Applications on Smartphones
ECE Professor Yanzhi Wang was awarded a patent for “Computer-implemented methods and systems for DNN weight pruning for real-time execution on mobile devices.”
Feb 13, 2026
Patent for a Scalable and Sustainable Approach to High Performance Computing
ECE Associate Professor Cristian Cassella was awarded a patent for developing a “Low power Ising system.”
Feb 13, 2026
Shrivastava and Zheng Receive MassCEC Funding for Climate Tech Advancement
ECE Associate Professor Aatmesh Shrivastava’s start-up, Think Analog, Inc., and MIE Associate Professor Yi Zheng were each awarded $75,000 as part of a $4.5 million Massachusetts Clean Energy Center (MassCEC) investment for 23 clean energy and climate technology projects.
Feb 03, 2026
Optimizing Training Signals for Millimeter Wave Power Amplifier Modeling
ECE Professor Miriam Leeser’s research on “Training Signal Optimization for Behavioral Modeling and Digital Predistortion of RF Power Amplifiers” was published in IEEE Microwave Magazine.