UCF researcher gets $1M for chip project

The National Science Foundation is paying a University of Central Florida researcher $1 million to boost hurricane-prediction models and cyberdefense systems.

Associate professor Sumit Jha will work to create faster computer chips that will be able to process big amounts of data without overheating.

For decades up until 2010, the processing power of the leading computer chips has grown exponentially, with every couple of years bringing marked improvement, Jha said.

Then, during the last couple of years, that pace slowed.

“In the last decade, even if you have bought a new laptop or desktop, the processing speed has not gone up,” Jha said. “This is a huge problem for society.”

Jha’s process puts a computer’s memory and its processors on the same chip.

Right now, each of the components is housed in separate locations.

If successful, Jha sees the technology being useful in more industries, including self-driving cars and smartphones.

“I think one of the unique things about this project is that we do not want to change the software stack,” Jha said. “Let’s start with what people have and then do the hardware design require to run it on a new processor.”

Jha and his team have run simulations, but the grant will enable a live test by researchers at SUNY Polytechnic Institute with work expected to start in October.

A potential artificial intelligence-based weapon against lung cancer cells has been under development by University of Central Florida researchers.

The tool can detect tiny specks of lung cancer-infected tissue on a CT scan with a 95 percent accuracy rate, which exceeds the 65 percent accuracy rate of the human eye, according to the scientists behind the research.

Engineers at the school’s Computer Vision Research Center announced the development Wednesday.

Facial recognition and brain development in humans guided the work, said Rodney LaLonde, who was on the team.

“You know how connections between neurons in the brain strengthen during development and learn? We used that blueprint, if you will, to help our system understand how to look for patterns in the CT scans and teach itself how to find these tiny tumors,” LaLonde said in a press release.

More than 1,000 CT scans were fed into a scanner to analyze patterns and help the computer learn how to find tumors.

Non-cancerous masses and tissue, along with nerves, were ignored by the computer system.

“I believe this will have a very big impact,” UCF assistant professor Ulas Bagci said in the release. “Lung cancer is the number one cancer killer in the United States and if detected in late stages, the survival rate is only 17 percent. By finding ways to help identify earlier, I think we can help increase survival rates.”