Photo graphic with headshots of Jennifer Hasler and Raghupathy Sivakumar.

Hasler and Sivakumar Awarded Regents' Entrepreneur Distinction

Professors Jennifer Hasler and Raghupathy Sivakumar have received the prestigious distinction of Regents' Entrepreneurs by the University System of Georgia Board of Regents, in recognition of their exceptional innovations and achievements in commercial endeavors.

Brendan Saltaformaggio & Amit Sikder DARPA software

‘Distilling’ Outdated Software Could Save Defense Dept. Millions in Time and Money
Aug 16, 2023 —

Brendan Saltaformaggio leads a $10M DARPA-funded effort to update critical defense software.

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ECE and SCS Duo Earns 2023 Qualcomm Innovation Fellowship
Aug 10, 2023 —

Ph.D. candidates Payman Behnam and Jianming Tong recognized for machine learning research on enhanced navigation capabilities of edge applications.

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ECE Team Honored for Groundbreaking Transformer Design
Aug 09, 2023 —

The proposed high-voltage solid-state transformer (SST) offers enhanced flexibility and control for integrating renewable energy sources and electric vehicles in power grids.

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Researchers Awarded EURASIP 2023 Best Paper Prize for Innovative Video Action Recognition Techniques
Aug 09, 2023 —

Professor AlRegib and team received the EURASIP 2023 Best Paper Award for their novel methods to improve action recognition in videos using deep neural networks.

Professor Deepakraj Divan, winner of the 2023 Nari Hingorani Custom Power Award

Divan Honored with Prominent Custom Power Award
Jul 25, 2023 —

Divan received the award in recognition of his, “contributions to distributed and decentralized dynamic control of transmission and distribution systems”.

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Novel Ultrasound Imaging Research Earns Trailblazer Award Funding
Jul 18, 2023 —

Led by Shaolan Li, and in collaboration with Levent Degertekin, the award will provide support to research on compact, energy-efficient integration of ultrasound front-end electronics. 

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Li Earns NSF CAREER Award to Advance Machine Learning in Graph Data
Jul 18, 2023 —

The project aims to develop theoretically principled and robust algorithms that can effectively learn from complex graph-structured data.