DECEMBER 5, 2023 — Devin White ’21 will cross the stage this weekend as one of UTSA’s first graduates with a master’s degree in artificial intelligence, a program that began at the university last fall.
Part of the University College’s degree offerings, the M.S. in Artificial Intelligence (MSAI) is a multidisciplinary degree program with three tracks: data analytics, computer science, and intelligent and autonomous systems.
Students in the program have an opportunity to work with emerging technology in the areas of computer science, mathematics, statistics, and electrical and computer engineering. Additionally, they conduct research alongside nationally recognized professors in MATRIX: The UTSA AI Consortium for Human Well-being, a research-intensive environment that develops sustainable AI solutions that benefit society.
White followed the intelligent and autonomous systems track, studying under the guidance of Yoncan Cao, an associate professor of electrical and computer engineering in the Margie and Bill Klesse College of Engineering and Integrated Design at UTSA.
He began volunteering with Cao on a research project unrelated to AI when he was an undergraduate in electrical and computer engineering at UTSA. Cao immediately saw White’s potential and encouraged him to apply for one of 10 undergraduate research positions available to support an AI-based Research Experiences for Undergraduates (REU) program that is funded by the National Science Foundation and U.S. Department of Defense.
White was selected in summer 2021 and officially joined Cao’s research team in the Unmanned Systems Labon a project to understand robotic systems and their collaboration with humans.
“This was my first experience with AI in practice, and I instantly knew it was something I wanted to pursue as a career,” said White. “I learned about reinforcement learning, machine learning, neural networks and all of that fun stuff.”
Cao, also a core member of the MATRIX AI Consortium, encouraged White to apply to the MSAI program at UTSA. White jumped on the opportunity. He was excited to learn more about the growing, dynamic field of AI and to continue working with Cao, who had become his faculty mentor.
During White’s time in the master’s program, he narrowed his research focus to human-guided reinforcement learning, a subset of machine learning that uses human feedback to train robots to learn complex tasks more effectively as they interact with their environment.
“Devin is a very fast learner and quickly mastered key AI and machine learning tools and software,” said Cao. “Given his strong skillsets and passion in these areas, Devin was chosen to lead our project on human-guided machine learning funded by the Army Research Lab. He has done remarkable work, and I am always impressed by his attitude, ambition, teamwork and eagerness to take new challenges.”
UTSA’s MSAI program has given White the opportunity to meet, work with and learn from many different scholars and professionals across the AI spectrum. These experiences have helped sharpen his career focus and widen his network.
For example, his primary research paper “Rating-based Reinforcement Learning” was accepted into one of the workshops at the 2023 International Conference on Machine Learning (ICML), and he was able to travel to Hawaii to present his work. Long-term, he hopes to see his work incorporated into real-world systems that help people make better decisions or discover new things they like based on their online ratings.
“It was a lot of fun and a new experience presenting work at the ICML workshop,” he reflected. “I got to meet and talk with leading researchers not just in AI but in my specific field of human guided reinforcement learning. I’m so grateful to have had this experience and it is one that I will always remember.”
In addition to leading and assisting on research papers, White also competed on the Silent Siren team in the inaugural UTSA Draper Data Science Business Plan Competition, hosted by the UTSA School of Data Science. Silent Siren received the competition’s honorable mention and bonus prize for its work on an emergency vehicle siren detection application and edge device.
White is one of 15 students enrolled in the first MSAI cohort at UTSA. Luis Barba Reyes, another cohort member, will cross the stage this month while the other members are projected to graduate in 2024.
In addition to the free-standing MSAI degree program, UTSA offers a dual degree program with UT Health San Antonio: the MD/MSAI. Launched this fall, the five-year program will enable physicians trained in San Antonio to uniquely lead the practical use of artificial intelligence to improve diagnostic and treatment outcomes. The program was first piloted in 2021. Two students were accepted and are projected to graduate next May.
In addition to offering an M.S. in artificial intelligence, the University College offers undergraduate degrees in multidisciplinary studies, a Ph.D. in translational science, graduate and undergraduate certificate programs in data science, and undergraduate certificate programs in community engaged leadership and legal studies.
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There are many citation managers. Which one is right for you? This workshop will explain what a citation manager is and how it can help you organize your citations, insert citations as you write your paper, and generate your bibliography. If you plan to attend one of our hands-on Endnote®, Zotero®, or BibTeX® / LaTex® workshops, we recommend that you start with this overview.
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Virtual EventAre you required to use LaTeX for writing your research papers? This workshop is divided into two parts: an introduction to Zotero, a citation management tool, and a demonstration of the features of Overleaf, a free online LaTeX editor.
Virtual EventCome listen to the UTSA Jazz Ensemble at a free event.
UTSA Recital HallLiterature reviews are a key element of evidence synthesis and scholarly inquiry. In this workshop, attendees will learn the differences between systematic, scoping, narrative, and other literature review types. The session will also detail the guidelines and components of various literature reviews, as well as resources to best support each.
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