The Department of Computer Science at the University of Virginia has been awarded a large Principles and Practice of Scalable Systems grant from the National Science Foundation for collaborative research.
As the lead institution, UVA will receive $3 million of the total $4,999,995 award. The partner institutions, the University of Pittsburgh and Saint Louis University, will receive $1.8 million and $199,995 respectively.
Aidong Zhang, the William Wulf Faculty Fellow and professor of computer science, biomedical engineering and data science, is the principal investigator on the project, Co-designing Hardware, Software and Algorithms to Enable Extreme-Scale Machine Learning Systems. Zhang leads a team that includes four co-PIs and two senior personnel from the UVA Department of Computer Science.
Contributing for UVA are:
- Kevin Skadron, Harry Douglas Forsyth Professor of Computer Science
- Matt Dwyer, Robert Thomson Distinguished Professor, computer science
- Ashish Venkat, William Wulf Career Enhancement Assistant Professor, computer science
- Brad Campbell, assistant professor, computer science and electrical and computer engineering
- Tianhao Wang (senior personnel), assistant professor, computer science
- Yonghwi Kwon (senior personnel), John Knight Career Enhancement Assistant Professor, computer science
The technologies of the “internet of things” – the vast network of connected products that make our cars, homes, businesses and cities more efficient – and artificial intelligence are converging into emerging systems computer science researchers refer to as the “artificial intelligence of things” and the “internet of senses.”
The first concept combines internet-of-things objects or networks, for example your internet-connected home thermostat or a diabetic patient’s glucose monitor, with AI technology. The second concept, the Internet of Senses, captures the billions of connected devices that enhance our senses and move them beyond the boundaries of our bodies, giving us augmented vision, hearing, touch and smell.
“Together, these technologies will enable us to blend multisensory digital experiences with our local surroundings and interact with remote people, devices and robots as if they were right beside us,” Zhang said.
These systems rely on machine learning, the use of algorithms and other computational processes to analyze data, recognize patterns and draw inferences with increasing accuracy without being programmed to do so. Artificial intelligence is the ability of machines to behave like humans. Machine learning is the part of AI that enables the machine to “think” like a human – in other words, to acquire intelligence.
Zhang and her colleagues posit the integration of the internet of things, the internet of senses and artificial intelligence will make these emerging systems “smart, communicative and powerful by processing data and making intelligent decisions” – if the systems can operate at the scale that will be required as billions of mobile and embedded devices multiply into the trillions.
Learn more about this project here.