It was his need to understand the ‘Why’ of things that drove Aksel Laudon’s interest in the research that has been central to his academic life from his undergraduate to his final year as a medical student.
The fourth-year medical student from Phoenix, Arizona has shown he can do some heavy lifting, balancing the rigors of medical school, the added responsibilities of research (he’s been lead author or co-author on at least a half-dozen papers) while maintaining his status as a star athlete on BU’s indoor and outdoor track teams from his undergraduate years through his graduate years.
“I do think that I’m someone who’s naturally curious, and research is something that I wanted to do as part of my medical training,” said Laudon, who was a student in the BU Modular Medical/Dental Integrated Curriculum (MMEDIC) program and received his undergraduate degree in Biomedical Engineering in 2022. He wants to specialize in neurology, a field he says is rife with research opportunities and unanswered questions.
“Neurology is really rich in terms of innovation and how data science is going to transform the field,” said Laudon. “I’m very excited to be going into a field where I’ll be able to start trying to understand this very complex, very interesting thing that is the human brain.”
But it was the kidney that consumed a lot of his research time at BU. As an undergraduate, he worked in the lab of Weining Lu, MD, professor of medicine, leading a bioengineering team investigating the use of artificial intelligence to automate kidney biopsies to identify diseases.
I’m very excited to be going into a field where I’ll be able to start trying to understand this very complex, very interesting thing that is the human brain.
Aksel Laudon
“During one of the lab meetings, we were talking about how tedious it was for pathologists to look at all the slides of kidney samples…and I thought, that’s something AI can do,” recalled Landon. Throughout medical school he’s continued his research in the Lu Lab using deep learning to teach computer programs to screen for kidney diseases.
He was first author on a paper published in March 2025 that described progress in using AI to measure the width of components of the kidney’s filtration barrier system. This measurement is used as an indicator of the presence and severity of kidney diseases of the filtration barrier, and to gauge the effectiveness of treatments. Pathologists typically use a specialized electron microscope in a process that is so labor intensive, and subjective, that it’s considered a major impediment to diagnosis, treatment and research.
“It’s important in science to be always skeptical of your results and to look for more high-quality evidence,” Laudon said. “Any good scientist will always be hungry for more evidence.”