About James Pai

James Pai was born in Whittier, California, and raised in Taiwan. He identifies with American and Taiwanese culture and has been a citizen of the United States since birth.

At thirteen, James returned to the United States with his brother, speaking limited English. When his mother was diagnosed with breast cancer shortly after, the plan for their parents to follow fell apart, and the brothers learned to manage on their own. James found footing in a high-school woodshop class. The work was exacting—measure, cut, check, redo—and a teacher there noticed how James approached it: patiently, precisely, willing to remake something until it held. That teacher became a mentor, helping James through the hard time and sharpening his English, until the habit of careful building became something he could carry through uncertainty.

That builder’s mindset carried into biology. James earned a bachelor's degree in biochemistry and cell biology at the University of California, San Diego, and later completed a master’s degree in biological sciences there. Drawn to the idea that DNA is code, he wanted to apply that logic to a problem with clear stakes. He joined Omar Akbari’s lab to work at the intersection of genome engineering and global health, developing CRISPR-based mosquito population-suppression systems for malaria control and helping identify a female-lethal target that could support a more practical approach.

That work also revealed a bottleneck: CRISPR can cut DNA precisely, but inserting larger genetic cargo remains difficult. To expand what genome engineering could do, James joined Patrick Hsu’s lab at the Arc Institute, where he helped characterize bridge editing, an RNA-guided recombinase system for programmable DNA insertion and rearrangement. By the time he left Arc, he felt the toolbox was catching up, but biology still lacked the predictive understanding needed to know what to reprogram.

James is now pursuing a PhD in Iain Clark’s lab, where he is developing scalable ways to measure how genetic and chemical changes reshape cell state. He hopes these datasets will help build virtual cell models that can predict responses to perturbations, moving biology toward a more reliable engineering discipline.