UCF Assistant Professor Shruti Vyas was raised to the grade of Senior Member of the Institute of Electrical and Electronics Engineers (IEEE). Only 10% of the nearly half a million members have achieved this level. Promotion to this grade requires a wide breadth of experience and accomplishments.
IEEE is a global network of over 486,000 STEM and engineering professionals. Their primary goal is to promote technological advancement for the betterment of humanity.
“I am honored by this recognition from IEEE. It represents not only a professional milestone but also a reflection of my commitment to advancing interdisciplinary research and collaborations,” Vyas says.
Leading up to this recognition, Vyas says that some of her accomplishments span interdisciplinary research at the interface of artificial intelligence, materials science and chemical engineering.
“I’ve been published in top-tier venues and secured competitive external funding as a principal investigator from Siemens Energy and the Florida High Tech Corridor Council,” Vyas says. “I have also served as a reviewer for major IEEE conferences and journals, contributing to the broader AI and engineering community.”
Several of Vyas’ projects align well with IEEE’s mission of advancing technology for humanity. These involve projects on chemical property prediction that were published at NeurIPS 2025, and studies on photovoltaic fault detection, published in Engineering Applications of Artificial Intelligence (EAAI). Alongside these, the Siemens Energy–funded project that integrates AI research with industrial safety that resulted in numerous publications at the 2025 International Conference of Computer Vision.
Vyas says that working at UCF has presented the opportunity to establish an interdisciplinary research group under the Institute of Artificial Intelligence and to mentor students from both materials science and engineering and computer science.
“My research focuses on developing intelligent systems that bring automation and accelerate scientific discovery,” Vyas says. “Current projects in my group explore image-based geolocalization, AI-driven defect detection in photovoltaic modules, and machine learning for predicting chemical and materials properties. We are particularly interested in adapting foundation models—large AI systems like vision-language models—to scientific domains that require reasoning over structure, chemistry, and physics.”
Moving forward with the recognition, Vyas says that she plans to continue contributing to advancing technology.
“I plan to continue with my research and strengthen my engagement with IEEE by contributing to conferences, reviewing and mentoring early-career researchers,” Vyas says. “This recognition motivates me to further expand my research to foster collaborations that bridge AI with sustainable energy and manufacturing applications.”
- Written by Hannia Gonzalez