Master’s Student Shivani Bhawsar Presents Her ‘Smart Microscope’ at Prestigious Conference, Leading to Publication
The electrical and computer engineering graduate used artificial intelligence to develop a method that expedites the study of nanomaterials, which she presented at the Materials Research Society fall meeting, then published her findings in MRS Bulletin
While researching nanomaterials in mechanical engineering Professor E.H. Yang’s Advanced Quantum Materials Laboratory, Shivani Bhawsar, M.S. ’24 noted how time-consuming her work was — so she applied her knowledge of artificial intelligence to optimize the process. Her new application, which can be thought of as a “smart microscope,” was so successful that she went on to present her work at the Materials Research Society (MRS) fall 2022 meeting in Boston, Massachusetts — where an editor personally invited Bhawsar to submit her findings to the prestigious journal MRS Bulletin. Published on June 25, 2024, her article sits at the intersection of artificial intelligence (AI), quantum computing, computer science and materials science — offering a glimpse into the rich research world of a master’s student at Stevens Institute of Technology.
Bhawsar, an applied artificial intelligence major in the Department of Electrical and Computer Engineering, has always been drawn to problem-solving and creating solutions. So when she came to Stevens Institute of Technology, engineering felt like a natural fit for her.
“What inspired me to pursue this research was my passion for applying my skills across various scientific domains and seeing tangible outcomes through automation,” she said.
Bridging quantum technology and computer science, Bhawser’s research takes an AI-based approach to characterizing 2D materials — substances that are just one or two atoms thick, essentially forming flat sheets. Her work is paving the way for the development of ultra-thin electronic devices, advanced sensors, and faster and more energy-efficient gadgets.
“My research involves using a special type of computer program to help researchers better understand a group of materials called transition metal dichalcogenides (TMDs),” she explained. “These materials have exciting properties that could be useful in many different technologies, like electronics and energy storage. But studying them can be really time-consuming.”
To optimize the process, she developed a clever way to use artificial intelligence to analyze optical images of these materials, eliminating the need for low-throughput procedures like Raman spectroscopy, photoluminescence spectroscopy and atomic force microscopy.
“Think of it like a super-smart microscope that can look at tiny details in a flash!” she said. “This helps us learn more about TMDs and how they can be used to make cool new stuff.”
Her new method for characterizing TMDs uses a generative, deep learning-based, image-to-image translation method. This technique enables rapid and accurate analysis of optical images and spectroscopic data of TMD samples, making it possible to efficiently identify and characterize them across various layers and compositions. Through this approach, she aims to expedite the study of TMDs and uncover their potential applications.
“By integrating AI-driven image analysis into the characterization of 2D materials like TMDs, we bridge multiple disciplines and unlock new possibilities at the intersection of materials science, quantum technology and computer science,” she said. “AI acts as a bridge here between microscopic images and the properties of 2D materials, expediting the characterization process significantly. By leveraging AI's ability to rapidly extract crucial information from optical images and spectroscopic data, we're not only enhancing our knowledge of TMDs but also paving the way for the development of next-generation quantum devices and computing architectures.”
Yang, who has served as Bhawsar’s advisor, encouraged her to attend the MRS meeting.
“She has made an outstanding research contribution as a master's student volunteer,” he said.
Bhawsar was eager to make the most of this event.
“The opportunity to present my work at the MRS Fall Meeting in Boston was incredibly exciting and important to me,” she said. “It provided a platform to share my research findings with peers and experts in the field, fostering valuable discussions and feedback. Being able to showcase my work at such a prestigious conference was not only a significant milestone in my academic journey but also a rewarding experience that highlighted the impact and potential of my research in advancing materials science.”
That opportunity ultimately led to the publication of her article, “Deep learning-based multimodal analysis for transition-metal dichalcogenides,” in one of the most widely recognized and highly respected publications in materials research.
According to Bhawsar, the process of researching and writing this paper was both challenging and rewarding. Regular weekly meetings with Yang provided an avenue for discussing her progress and refining her understanding of the experiments.
“This collaborative process of learning and refinement paved the way for presenting my work at the MRS conference, where I received feedback from senior researchers in the field. Overall, it was an immensely rewarding and exciting journey, marked by continuous learning, collaboration and recognition,” she said.
As a recent graduate of the Class of 2024, Bhawsar’s goal is to continue to apply her skills to make a positive impact. Already an experienced and published researcher, she is excited about the possibilities ahead.
“Being part of [our lab] has allowed me to immerse myself in the forefront of scientific discovery…I'm immensely grateful for the opportunity to be part of such a dynamic and supportive research community. As I move forward, I'll deeply miss the collaborative spirit and the mentorship that have been integral to my growth and development at Stevens.
“It not only broadened my horizons but also inspired me to pursue interdisciplinary research and a drive to explore new frontiers in science.”
