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Tags: Research

Prashant Doshi, a professor in the School of Computing, is transforming artificial intelligence research into real-world applications through his work on human-robot collaboration and inverse reinforcement learning. His research has broad implications across industries, including agriculture, where he is developing AI-driven collaborative robots (cobots) designed to streamline produce processing operations. To bring this technology to market,…
by Mike Wooten, Susan Ambrosetti New grant program builds upon institute’s 40 years of discovery and innovation Four university-wide research projects designed to advance interdisciplinary research in artificial intelligence have been awarded seed grants by the University of Georgia’s Institute for Artificial Intelligence. The grants, the first of their kind from IAI, are the latest step in the university’s strategic efforts to…
By: Alan Flurry As Machine Learning tools become increasingly commonplace, their ubiquity is accompanied by a growing need to use the tools on mobile devices. From the application side, the endless possibilities go well beyond common speech or image recognition. And the growing computational capacity of smartphones creates the necessary room for improved hand-held AI. Researchers at the University of Georgia have recently developed an innovative…
Athens, Ga. – The University of Georgia is joining the NextGenAI consortium, a partnership with 14 other leading research institutions and technology company OpenAI to accelerate AI research and education. OpenAI, known for its generative AI technologies, including ChatGPT, is committing $50 million in research grants, access to OpenAI’s tools, and compute funding through the consortium. The initiative will support the discovery and…
Watch as Prof. Doshi discusses the School of Computing's research on AI and robotics in this College of Engineering-produced video and his philosophy on student success in graduate programs.   The link is to a YouTube video that CENGR produced and is available on their YouTube channel.
Affordable Learning Georgia (ALG) has awarded Dr. Barnes and Dr. Cotterell each a Continuous Improvement Grant in the amount of $8,670 to update the textbook for CSCI 1302 Software Development and continue to offer it to students free of charge as an Open Educational Resource! Together, these two grants constitute $17,340 of the $445,000 in grants that were funded under the 26th round of ALG’s Affordable Materials Grants program.   Each…
SoC's Assistant Professor of Computer Science, Dr. Ninghao Liu, along with his Ph.D. students Yucheng Shi and Tianze Yang, won the Distinguished Paper Award for their co-authored paper, "MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering," at the recent American Medical Informatics Association 2024 Annual Symposium in San Francisco.    Dr. Liu and his team developed a unique method to…
A recent article published by Nature Medicine introduces the world to a recently discovered open-source visual-language foundation model BiomedGPT that has been used for various biomedical applications in the field. As we have witnessed the rise of AI use in various technologies over the past year Dr. Tianming Liu's research team has used this idea and collaborated on using AI techniques in solving tasks within the biomedical field such as…
The University of Georgia received a five-year, $10 million grant from the Institute of Education Sciences to establish a research and development center that will provide national leadership on best practices for using generative artificial intelligence (GenAI) in schools, strengthening competence in GenAI in middle school science classrooms. This project is led by Xiaoming Zhai, an associate professor at the UGA Mary Frances Early College…
Dr. In Kee Kim's research team, with international collaborators, has received the Best Paper Award at IEEE EDGE 2024, held from July 7 to 13 in Shenzhen, China. The award-winning paper is titled “Characterizing Deep Learning Model Compression with Post-Training Quantization on Accelerated Edge Devices.” This work is the first comprehensive characterization study of online model compression on resource-constrained edge devices. The team…

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