Master’s students shine at engineering research symposium
For the first time, the annual event was expanded beyond joint doctoral students. Eighty students participated.
Sara Herrera demonstrated her work on a device for monitoring small changes in glucose levels in diabetic and pre-diabetic individuals, and Henry Casarez III gave a presentation on simulation software he's using to study ways to make metals last longer.
They were among 80 students from San Diego State University’s College of Engineering participating in a newly rebranded Graduate Research Symposium Nov. 8 at Conrad Prebys Aztec Student Union. Formerly limited to joint doctoral program engineering students, the expansion of the research symposium to master’s students roughly doubled the number of presenters.
Participants lined Montezuma Hall from one side to the other with their posters, mostly on highly technical subjects, for a roving audience of fellow students, alumni and industry representatives.
Temesgen Garoma, associate dean of graduate studies and research in the college, said the rebranding after 17 years of doctorate-level-only presentations reflects the significant contributions master’s students are making to research productivity, and “shows the growth of the college.”
“Our students get feedback on the research,” Garoma added. In addition, “they are creating connections with potential employers. It creates a collaboration between our faculty and potential industry sponsors for research.”
The event followed a morning meeting of the engineering Dean’s Advisory Board, with briefings from Dean Eugene Olevsky and other officials on upcoming initiatives.
At the engineering research symposium, the newly invited master’s students said it felt great to be part of the show. For some, it was a warm-up to the more intense and wider-ranged SDSU Student Symposium that occurs in the spring semester.
“It’s exciting,” said Herrera, a San Diego native who got her bachelor’s degree in 2023 and is scheduled to complete her master’s work in May. “It feels nice as a master’s student to get that second opportunity. It’s nice to practice my presentation skills more. On the academic side, it also motivates me to get my work done faster so I have something to show.”
Casarez, who earned his bachelor’s degree at the University of California Riverside, presented his work with software studying how to prevent hydrogen embrittlement ― the loss of strength and ductility in metals absorbing hydrogen atoms ― at the molecular level. It’s a field of materials science that could be applicable on products ranging from automobiles to nuclear facilities.
The student said he appreciated the chance to show his work without the pressure a Ph.D student might face. “I want to go into design and manufacturing in the industry,” he said, “and hopefully be able to gain knowledge so we can design products well.”
At the advisory board meeting, Olevsky said the college is in the process of filling four open tenured or tenure-track faculty positions, and is part of a multi-college search at SDSU for an additional faculty member in the rapidly emerging science of artificial intelligence, he said.
In addition, SDSU Imperial Valley is hiring two assistant professors as part of an expanded program in electrical engineering, he said.
Garoma said the college now has a record-high number of students in joint doctoral programs, who are “contributing significantly to the research activity of the college.”
Kate Carinder, senior director of development, said the college’s endowment, raised through The Campanile Foundation, more than doubled the total from six years ago. Endowments support a variety of professorships, scholarships, and lab space, she noted.
Four “Best Poster” awards at the symposium all went to joint doctoral students. They were:
- Adrian Rivera, Structural Engineering
Effect of Manufacturing Imperfections in Sandwich Composites with Aluminum Honeycomb in Multi-Axial Loading - Mani Amani, Electrical and Computer Engineering
BIM-based Safe and Trustworthy Robot Pathfinding using Scalable MHA* Algorithms and Natural Language Processing - Jingxiao Tian, Electrical and Computer Engineering
Ultra low-power, wearable, accelerated shallow-learning fall detection for elderly at-risk persons - Esra Karabay Tiftik, Bioengineering
Multi-Scale Modeling to Predict Cancer Cell Mechanics and Migration Based on Transcriptional State and Microenvironment
