Maitreyee Sharma Priyadarshini has been appointed as assistant professor. Upon earning her doctoral degree from the University of Illinois, Urbana-Champaign, she served two years as a postdoctoral research associate at Johns Hopkins University in the department of Chemical and Biomolecular Engineering. Priyadarshini’s research expertise includes hypersonics, physics-informed and data-driven modeling of chemically reacting flows, machine learning and computational materials discovery. 

She completed her Ph.D. and master’s in aerospace engineering from the University of Illinois, Urbana-Champaign and her bachelor’s in mechanical engineering from People’s Education Society Institute of Technology in Bangalore, India. 

Priyadarshini is a member of the American Institute of Aeronautics and Astronautics, the American Institute of Chemical Engineers and the American Chemical Society.

What drew you to Virginia Tech? Share with us what excites you about the department and our students?

Virginia Tech’s vision and expansion in AI/ML areas aligned perfectly with my research interests and vision. I was particularly drawn to the collaborative culture that bridges various departments, fostering interdisciplinary research and innovation. And, of course, I immediately fell in love with the stunning mountain landscape surrounding the campus!

During my interview in the department, I was very happy to see a great balance in the faculty research areas. My work sits at the intersection of hypersonics and materials science, and I was excited to discover several faculty members with whom I could see strong collaborative potential. Moreover, I have interacted with graduate students in CREATe and it has been a pleasure to hear the excitement in their voices when they talk about research. I have also noticed that we have great undergraduate students, who are motivated to work hard and excited to learn things that are beyond the scope of the class they are taking. This strong drive, coupled with the vibrant research community, makes being part of the AOE department at Virginia Tech a journey that I am excited to walk.

What does your research entail? What do you hope will come of it?

My group’s research focuses on the development of computational methods to study fluid and material systems. Our current focus is on developing statistical and machine learning models for hypersonic flows and doing uncertainty quantification for these models. We are also interested in the development of machine learning models for materials discovery and studying materials for energy harvesting. One of the most exciting directions we are pursuing is the study of materials that can be used for in-space solar cell manufacturing which would significantly reduce the payload required to carry heavy solar panels from Earth. From a more fundamental view, I hope my group’s research can improve our understanding of flow physics and material interactions in extreme environments.

What originally got you interested in your work? Tell us about the ‘spark’ that pulled you to your area of research.

I was always fascinated by space, even as a young child. When I started graduate school at the University of Illinois, I was looking for ways to tie together my interest in applied math, chemistry, and aerospace and I found hypersonics research to be the perfect answer. The most motivating incident that pulled me to this research was during my internship at NASA Ames Research Center. There I saw the application of my computational work in explaining experimental results that were previously never modeled. This got me very excited, and I decided to pursue research in the computational modeling of fluids and materials. 

Please share with us what you’d like engineering students to know about your lab and research group?

My group is dedicated to advancing computational methods for studying fluid and material systems, with a strong focus on practical, impactful research. We develop machine learning models to accelerate materials discovery, enabling innovations in hypersonics, energy harvesting, and sustainable aviation. Our research is highly interdisciplinary, and students in our group have the opportunity to gain experience in a variety of advanced computational tools, while also contributing to cutting-edge developments in energy and aerospace technologies. If you are excited about solving complex, real-world engineering challenges using computational methods, statistics, and machine learning, my group offers a stimulating environment where you can learn and make a meaningful impact. Finally, my group is grounded in kindness, honesty, and direct communication and we strive to provide an inclusive and safe environment for all.