PVAMU’s CREDIT team from left to right: John Olamofe, Yuzhong Yan, Brandon Williams, Omobayode Fagbohungbe, Damilola Adesina, and Sheikh Reza.
PRAIRIE VIEW, Texas – Out on the open sea, unmanned surface vehicles (USVs) are used to track and monitor shipping vessel traffic to avoid collisions and ensure the safety of ships and crews. This is currently done using highly effective radar systems. However, when there are international conflicts on the high seas, a USV needs to be able to monitor traffic without giving away its location so that it won’t be compromised or destroyed in contested waters.
Enter the Artificial Intelligence (AI) Tracks at Sea Challenge. This national competition was established to find a real-world solution to the USV tracking problem. The Department of the Navy’s Office of Naval Research – Naval Information Warfare Center (NIWC) Pacific sponsored the competition, which was announced last year. Universities from across the country, including Prairie View A&M University (PVAMU), submitted white papers, or technical papers explaining their AI approaches towards addressing the challenge, as well as corresponding working software tools for consideration. Working solutions would share a $200,000 cash prize distributed to each winning university’s research department.
A team of researchers from PVAMU’s Center of Excellence in Research and Education for Big Military Data Intelligence (CREDIT) decided to compete, and they won. Led by AT&T Endowed Professor Lijun Qian, Ph.D., the team from the Roy G. Perry College of Engineering included six graduate students: Brandon Williams, Yuzhong Yan, Sheikh Reza, Damilola Adesina, Omobayode Fagbohungbe, and John Olamofe, along with faculty advisors Xishuang Dong, Ph.D., and Dean Pamela Obiomon, Ph.D. Just a few years ago, another group of students from CREDIT won an Institute of Electrical and Electronics Engineers (IEEE) Big Data competition organized by the IEEE Big Data Initiative.
“This year’s CREDIT team also knew they could use their AI expertise to find a solution, and they were correct,” Qian said. The team was notified recently that their solution took first place out of 31 universities that participated.
“This is a great win for the CREDIT center, the College of Engineering, and Prairie View A&M University,” Qian said. “This again demonstrated the strong research capability and excellent student training in AI of the CREDIT center.”
Participating universities included both private and public institutions, and many were Ivy League, tier-1 research universities, Historically Black Colleges and Universities, and Hispanic Serving Institutions. These research institutions spanned the country, from California to New Hampshire, and most have an emphasis on Science, Technology, Engineering, and Math (STEM) programs.
As first place recipients, the CREDIT team received $55,000 toward further research at PVAMU.
“With 94% of the competitors attending colleges and universities outside of California, this challenge served as an avenue to make broader impacts in STEM,” said Yolanda Tanner, Naval Information Warfare Systems Command (NAVWAR) STEM Federal Action Officer and NIWC Pacific Internship and Fellowship project manager. “It was also a means by which students could further develop their STEM skills while working collaboratively to solve a real-world naval problem.”
PVAMU’s research programs have achieved many accolades in recent years, and work being done through programs like CREDIT are having a real-world impact on the country and world. PVAMU students are participating in groundbreaking research projects, such as this one, all year long.
“[There is] outstanding work being done in the CREDIT research center led by our endowed professor, Dr. Qian,” said Obiomon. “So far, 12 ROTC students have been trained and performed research in the center. Eight Ph.D. and 27 master’s students who conducted research in the center have graduated with expertise in artificial intelligence. Currently, many students work in the center conducting cutting-edge research in artificial intelligence and machine learning. We are excited for what is to come.”
By Jocelyn Kerr
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