AI and LLM Research Grows at the Hall With Data Science Expert Siyao Gu

As a new hire in August 2024, Siyao Gu came to Seton Hall with both corporate and academic expertise in electrical engineering and computer science. Now an assistant professor of computer science, he brings expertise in research focused on artificial intelligence and machine learning, specifically applied to the sciences. Gu’s dissertation, which he earned from the University of Texas, is in electrical engineering, and he focuses on researching renewable energy, nuclear technology, semiconductors, military contracting, robotics and computational biology. Primarily, he explores the application of AI and machine learning on smart grid innovation, sensor networks for nuclear security and X-ray science. Gu’s current research includes the application of LLMs for optimizing organizational stability and sustainability.

Gu came to Seton Hall last year because of its long-established computer science program and its status as an R2 institution. Research projects are key to Gu’s work. “There's a lot of opportunity to actually be able to go in and create something out of whatever background we come from,” he said. “It’s a privilege to work for Seton Hall.”

The transition from big business to university life was interesting, Gu said. “It's certainly different than in the corporate world, where you are expected to take care of a lot of the peripherals yourself,” he noted. “For example, within the hardware team at IBM, we ran a very small group of about five or six people, and you had to take care of a lot of these small things that nobody expected you to do, but you had to do it anyway.” Essentially, there wasn’t a lot of hand-holding, but “for academia, there is: when you're working in a university environment, they take care of you a lot more in terms of what you need for research and allow you to stretch out by giving you the tools that you need to go forward, then create your own journey.”

In college, Gu’s father, a mechanical engineer, encouraged him toward computer science. Interested in hardware more than software, Gu built his own circuit boards “from the ground up,” learning to solder in an electronics class. Later, he worked for IBM in what the company called the “power system” used to fuel data centers in the 1990s. “They had something called the Watson,” Gu said. It was a supercomputer named after IBM’s first CEO, Thomas J. Watson Sr., and could answer many questions it was posed. Gu worked on the Watson project on the back end, the hardware portion, he said. At the time, computers were not typically capable of understanding questions asked by humans in spoken language as they are now, yet they were very accurate—well before the internet, AI and search engines.

Gu, in his work with AI, feels we are in what he calls an “experimental phase for these types of emerging technologies.” Data, he says, “is something that everybody will work with, but machine learning will select what kind of data is best for the interest of companies or the universities, or those utilizing AI.”

Now, Gu is conducting research and building on his experience at the University of Texas, San Antonio, and Southern Illinois University, where he taught courses on electromagnetics, signal systems, applied physics and AI. At Seton Hall, he has taught computer architecture, C++, information technology and cybersecurity and is now focused on a class in computer science for engineers and mathematicians and a data science for cybersecurity course, which he feels is a very important subject right now for students—no matter their major.

“That course deals with how we're planning to apply the paradigms we learned from machine learning to actually make sure that sites are more secure and free from data crimes,” Gu said, so they can prepare for the issues that might come up in their everyday lives, since many students aren’t technologists. “They come in here fresh, without having any background in technology, and I hope to get them to walk away with a sense of what is it that they're looking at nowadays when it comes to today's digital world.”

For all the time Gu spends focused on the world of artificial intelligence and its development, he says the best way to keep pace with machine learning and data science is to remember that AI is just a tool created to make people’s lives easier. “Not more complex,” he notes, and it has been around for years in the form of data sequencing—it is just evolving. He gives the example of “personalized medicine” that has been around since the 1990s, using AI to create medical solutions for people and institutions. “There’s a whole world of applications within AI,” Gu said. “So for the students that are interested in or actually fascinated by this material, I would say just leave your preconceived notions at the door and just come in and explore what it is.”

Categories: Science and Technology