Get to Know Noblis: Brianna, Machine Learning and Computer Vision Researcher

Computer vision and machine learning tools are making the impossible possible. It’s really promising to see the future in terms of keeping the U.S. safer.”  – Brianna, Principal Scientist, Machine Learning and Computer Vision Researcher 

Meet Brianna, a machine learning and computer vision researcher at Noblis. Read below to learn how her work and research advances biometric practices for national security clients.

What does your role at Noblis entail? What is your favorite part about your job?
As a Machine Learning and Computer Vision Researcher in the biometrics field, most of Brianna’s work is centered on pushing and improving facial recognition algorithms. “We seem to have a good perspective of constrained images, but when they are unconstrained photos, taken from various angles and with other difficult conditions present, it takes more to recognize the subjects in the image and that’s the basis of what I work to solve,” said Brianna.

When she’s not curating data or developing tools for clients, Brianna is an integral part of Noblis Sponsored Research (NSR) program.

“I really enjoy the variety in my work, whether that’s getting to work on-site with clients or internal research. It’s rewarding to know that either way, I’m contributing to a strong mission,” said Brianna.

What are some of the impacts the field of Biometrics that non-experts would understand?
Brianna explained that some of the uses of Biometrics can make great differences in national security and law enforcement. “Unconstrained facial recognition algorithms enable us to identify individuals in challenging operating environments, such as the Boston bombing incident,” she said.

Her efforts are also being used to help build aging models and further missing persons cases. In her current research, Brianna is working to build models to age individuals so that criminals on the run or missing people can be found.

Computer vision and machine learning tools are making the impossible possible,” said Brianna. “It’s really promising to see the future in terms of keeping the U.S. safer.”

What do you think gives Noblis an edge in the industry, as it relates to the field of Biometrics?
“Our people are our greatest asset,” shared Brianna. “We have tons of biometrics experts in-house, but also experts in fields outside the biometrics domain, too, which lets us realize the need and usefulness of collaboration. We learn from our peers and address problems from different perspectives, as a result. Working with statisticians and linguists, for example, can help further the work I do in biometrics.”

Personally, what has been your biggest accomplishment?
“When my efforts have resulted in new approaches to solving challenges in my field, it’s really rewarding to disseminate the knowledge to our clients and to the research community,” said Brianna. “That’s why seeing my work published in peer-reviewed journals, or presenting at peer-reviewed conferences like the International Conference on Biometrics (click to read whitepaper), have been some of my most proud accomplishments.”

Why is continuous education important to you and what advice would you give other women in STEM?
Brianna believes that learning “on the job” enabled her to discover what she was really passionate about.

“Through working [at Noblis], I found a passion for machine learning and artificial intelligence, which led me to where I am in my career today,” explained Brianna. Since starting her career at Noblis, Brianna has earned her Masters’ and is working on her Ph.D.“The advice that I would give to women in STEM, or anyone in general starting out their career is to network and establish a team for yourself to utilize and constantly learn from,” said Brianna. “It’s important to build your own support system.”

Brianna currently serves as Machine Learning and Computer Vision Researcher in the Intelligence & Analytics mission area, responsible for the curation of the largest publicly available unconstrained face dataset, testing unconstrained facial recognition algorithms, and developing facial recognition tools. She holds a B.S. in Computer Engineering, a Master’s in Electrical Engineering, and is pursuing a PhD in Electrical Engineering from West Virginia University.