News

Nicole Yunger Halpern is part of a team that’s developed a new technique that can reset qubits in quantum computers highly effectively, a critical task for successful quantum computing.

He is profiled in a feature article published by the National Institute of Standards and Technology.

Being conferred Fellow status is the highest grade of IEEE membership, and one that is recognized by the technical community as a prestigious honor and an important career achievement.

Sanjali Yadav has developed a novel machine learning approach that enables adaptive and intelligent hardware, boosting dataflow efficiency and reducing energy consumption.

The papers highlight new innovations involving electric vehicles and the use of digital watermarks in large language models.

The team has developed an AI-driven keyword mnemonic generator designed to make learning more efficient and effective for students.

UMD researchers are using measured water jets to provide lifelike sensory experiences for gamers in virtual reality.

The researchers made the final cut for their innovative work in developing a scalable distributed training framework called AxoNN, which rapidly trains AI-based large language models on thousands of GPUs.

The multi-institutional, open-source project—expected to increase software development productivity by at least tenfold—is supported by a $7M award from the Department of Energy.

UMD information experts are developing novel methods to track down paper documents at the National Archives in College Park.