Jeremy Juybari: From defense research to fighting breast cancer with AI

For Jeremy Juybari, the path from managing a defense research company to developing artificial intelligence (AI) models has been anything but ordinary. Now a Ph.D. candidate at the University of Maine, he is pushing the boundaries of AI to help improve breast cancer detection and save lives.

While pursuing his bachelor’s, master’s and doctoral degrees, Juybari, a San Diego native, worked for Faster Logic LLC, a small defense-focused research and development company in his hometown, providing web and engineering support. Two semesters into his Ph.D. program in 2021, Juybari paused his studies for five months to serve as the company’s acting CEO after its founder, Raymond Moberly, unexpectedly passed away. Juybari led the company through a government audit and handled operations and personnel.

“Stepping into that role was unexpected, but it was important to me to support the work Raymond had built over seven years,” Juybari said. “It was a demanding time, and I learned a great deal about leadership, people and how research moves from concept to real-world development. After working through circumstances beyond my control, the company ultimately dissolved. Once things settled, I returned to UMaine to continue my Ph.D., which had always been my long-term plan.”

After completing his undergraduate economics and interdisciplinary studies degree at San Diego State University, he sought to expand his technical knowledge and research capabilities, which ultimately led him to pursue graduate study at UMaine. Once he completed the math degree, Juybari immediately began his Ph.D. in electrical and computer engineering. 

“When you have a good background in math, it makes learning AI much easier,” Juybari said. “You start to realize AI is a bunch of matrix multiplications. Without that strong foundation, it can look like magic.”

While working at the CompuMAINE Lab on coding and AI research, he learned how this technology could help save lives through improved AI for cancer diagnosis and reduce healthcare disparities. 

“I originally wanted to study economics, but it was math that brought me here,” Juybari said. “As I got deeper into research, I realized how many people die from cancer, sometimes simply because they were missed due to healthcare disparities. That really stuck with me.”

Juybari’s Ph.D. research focuses on AI for medical imaging and cancer detection. He developed the Context-Guided Segmentation Network (CGS-Net), a model that combines detailed tissue features with broader contextual regions to improve the identification of cancerous tissue in microscopic images of biopsied tissue.

Earlier this year, Juybari and his colleagues published their research in the journal Scientific Reports (part of the Nature portfolio) in a paper titled “Context-guided Segmentation for Histopathologic Cancer Segmentation.” The paper was featured by the National Cancer Institute for its innovative approach to improving AI accuracy in medical imaging. The study introduced a novel method in which the model learns how to integrate both local tissue features and broader contextual information, demonstrating how careful model design can enhance predictions in complex histological datasets.

“One of the biggest challenges I’ve seen in medical AI is the lack of common benchmarks,” Juybari said. “It’s kind of like the wild west, where researchers use different datasets, and  medical image datasets are often large and complex.”

UMaine’s mentorship and resources have been central to Juybari’s success. His co-advisors, Andre Khalil and Yifeng Zhu, offered both guidance and freedom, allowing Juybari to explore ambitious ideas. The Advanced Research Computing, Security, and Information Management (ARCSIM) group provided the computing power and collaborative environment that enabled his research.

Collaboration has defined his graduate journey. Juybari’s partnership with fellow Ph.D. student Josh Hamilton has been a cornerstone of his research and personal life. They’ve spent long nights tackling complex coding challenges, and have even shared key life moments.

“I couldn’t imagine UMaine without Josh,” Juybari said. “We work together on a majority of our research. Our strengths and weaknesses complement each other. We laugh a lot, it’s fun.”

Juybari also met his wife, Simona Mitevska, while living in Stodder Hall in 2019. He was studying mathematics then, and she was pursuing master’s degrees in economics and global policy. Their shared love of numbers and research turned into a lasting relationship. Today, Mitevska works as a senior research analyst in UMaine’s Office of Institutional Research and Assessment.

For Juybari, an interdisciplinary background and collaborative mindset are what drive him forward — whether leading a company or developing AI to fight cancer.

“You can’t know it all,” Juybari said. “Even within AI, there are so many different parts to one model. You could be well-versed with one part, have an understanding of another, but not be an expert in everything. You have to work with teams and trust that others will know things you don’t. If you try to do everything yourself, then what’s the point of working in a team?”

Looking ahead, Juybari remains open to where his path leads next.

“I like to keep an open mind,” Juybari said. “My interdisciplinary background has taught me to see challenges from different angles. I’m driven more by curiosity and problem-solving than by following a fixed path, and I’m excited to see where that leads next. ” 

Story by William Bickford, graduate student writer. 

Contact: Marcus Wolf, 207.581.3721; marcus.wolf@maine.edu