Blessy Antony: Crossroads between computer science and biology

This photo shows a young woman with dark hair and glasses standing in front of a tri-fold science fair poster on a desk. — Virginia Tech postdoctoral researcher Blessy Antony poses with her Flip the Fair poster presenting fifth grader-friendly information about her research on using machine learning to understand viruses. Photo by Carrie Kroehler for Virginia Tech.

The following story was written in Spring 2026 by Kailey Watson in ENGL 4824: Science Writing as part of a collaboration among the English department, the Center for Communicating Science, and the U.S. National Science Foundation COMPASS Center. The COMPASS Center is tackling the grand challenge of uncovering the genetic, molecular, cellular, and chemical rules of life underlying virus-host interactions through community-based and ethically grounded research. It is one of four Predictive Intelligence for Pandemic Prevention (PIPP) centers funded by the National Science Foundation.

It’s no big surprise that machine learning has a proven potential to speed up tasks, and one way it's doing so is in predicting viral evolution. Blessy Antony, a postdoctoral fellow at the U.S. National Science Foundation COMPASS Center at Virginia Tech, has dedicated her post-undergraduate research to doing just that. She is working on computational models to study and predict the behavior of viruses that do or could affect humans.

Blessy’s history lies in computer science. She received her undergraduate degree from the University of Mumbai and afterwards worked as a software engineer for JPMorgan & Chase. Wanting more education, she came to Virginia Tech for graduate work and received her Ph.D. degree in December of 2025.

“I like the idea of breaking down problems, developing computational methods, and implementing solutions,” Blessy says. “It has always been computer science since my undergraduate program.”

She shares that she especially enjoys using these skills for human good and is no stranger to adding biology into the mix. During her time as an undergraduate, Blessy completed a capstone project that used machine learning to predict breast cancer from tumor data.

After Blessy started at Virginia Tech, T. M. Murali in the Department of Computer Science introduced her to work in a related field through a course called Computational Systems Biology. The course aims at “system-level understanding of biological systems by analyzing biological data using computational techniques.”

She loved it.

This photo shows a group of 11 people sitting around a restaurant table smiling at the camera. — Blessy Antony (right front) poses with T. M. Murali and some of her fellow researchers in the Murali research group. Photo courtesy of Blessy Antony.

After working on a project predicting how SARS-CoV-2 interacts with the human body, Blessy reached out about joining and has been a part of T. M. Murali’s research group ever since.

Viruses had already been on her mind as a topic of interest because of the COVID-19 pandemic.

“I had to defer my graduate school enrollment due to the pandemic,” Blessy explains. “The embassies were closed. I couldn't complete the visa process. I could see the effects of the pandemic at various scales.”

She began her Virginia Tech journey in the spring of 2021. Blessy shares that it was a strange time to begin an educational journey. There were no labs, classes were held over Zoom, and there was very little socialization.

“It [COVID-19] was the problem to solve, and everyone was so influenced,” Blessy recalls. “I really loved how the entire research community came together from different angles.”

Her angle was working on computational models to accelerate this research. Specifically, she aided in identifying the sometimes lingering symptoms of COVID-19, now known as Long COVID.

This process differed from other projects she had worked on, Blessy explains, in that the electronic health data of patients being used was not publicly available. It was made accessible by the National Center for Advancing Translational Sciences in the National Institutes of Health to a restricted set of researchers and institutions.

This photo shows a group of seven young people posing for a selfie in front of a big screen that has a woman's face on it. — Blessy Antony poses with Anuj Karpatne (left) and some of her fellow researchers in the Knowledge-Guided Machine Learning research group. Photo courtesy of Blessy Antony.

“We would meet virtually through Zoom, look at the data on a web browser together, and work on potential solutions,” Blessy says. “It was a unique experience, as well, because we had computational scientists and doctors on the team . . . now turned computational biologists, getting feedback from everyone, and trying to predict the occurrence of Long COVID.”

Blessy has since moved forward from her work on COVID-19 to a broader area of research. She is now part of the U.S. National Science Foundation Center for COMmunity Empowering Pandemic Prediction and Prevention from Atoms to SocietieS (NSF COMPASS), which fits her interests in a number of ways.

She is also a part of the Knowledge-Guided Machine Learning (KGML) research group led by Department of Computer Science assistant professor Anuj Karpatne.

“I have learned and continue to learn a lot about developing machine learning models that are guided by scientific principles through the mentorship of Karpatne and his research group,” Blessy says, adding that Karpatne has been her co-advisor since 2023.

She is currently developing computational models to learn about the evolution of viruses and predict their potential to infect humans. Her most recent work is aimed at inferring the organisms that a virus can infect.

“Research shows that there are about 1.6 million known animal viruses in nature, but only a couple hundred viruses have been documented to infect humans,” Blessy said. “We don't know what the potential of the remaining animal viruses to infect humans is. We don't even know when the next [human infection] might happen. I believe it's really important to investigate that line and be prepared.”

It is not only important to identify the risk of animal viruses resulting in a human infection, Blessy says, but also to communicate them. It’s a skill she has enjoyed developing through the COMPASS center. One of her favorite events is Flip the Fair, where she presented her research to fifth graders.

“It is a very fulfilling and huge learning experience,” Blessy says. “The students are quick to understand and ask relevant questions that are fundamental to research.” She also trained to communicate her research to a diverse set of audiences through the “Communicating Pandemic Science Workshop Series” offered by the Center for Communicating Science and participated in the Nutshell Games this summer, an event in which she had just 90 seconds to explain her research to a public audience.

This is a picture of a diverse group of 44 scientists standing on a stairwell, smiling and posing for a picture. — Blessy Antony with the NSF COMPASS Center team. Photo courtesy of NSF COMPASS Center.

One of many things she has come to love from her time at Tech is the people.

“I really value the people I work with,” Blessy says. “This factor has guided my decisions so far in life, the other important factor being my research interest in developing computational methods to solve biological problems for the benefit of all. I think that's what brought me here to Tech. And that’s what drew me to my advisors and their research groups, and the NSF COMPASS Center. I’m very grateful for all the people I work with. Everyone is very encouraging and supportive and I learn a lot from each person.”

She hopes to continue researching at Virginia Tech and to focus more on the interpretability of computational models, try her hand at the experimental side of her work, and ultimately keep growing as a researcher.