Lucy Gao has hardly stopped to take a breath since she accepted a role as an assistant professor of statistics at the Faculty of Mathematics. She graduated with a doctorate in biostatistics from the University of Washington in June 2020 and joined the Faculty a month later. “There are a million things I’m doing for the first time, from working with students in an advisory role to applying for grants,” she shared.
Only two months into her new role, Gao applied for a discovery grant from the National Sciences and Engineer Research Council of Canada (NSERC). “It was intimidating to apply for funding that could support my work for five years into the future, but I’ve received so much support from the Faculty of Mathematics,” she said. “Countless colleagues have been willing to review my application with a fine-toothed comb and provide input.”
As an undergraduate student, Gao was drawn to statistics for its practical scientific value. “A lot of people don’t think of statistics as a science, but to answer any scientific question, you have to be able to collect and analyze data,” she explained. “That’s what the field of statistics gives us the tools to do.”
Currently, Gao spends her time developing new statistical methods that mathematicians and scientists can use to solve complex problems. Several months ago, she published a paper that focused on double dipping—the concept of performing an exploratory data analysis to generate a hypothesis before testing that hypothesis on the same data. “Traditionally, it’s a problem to use the same data set to identify a question to ask and then answer that question,” she explained. “You have to correct for the fact that a single opinion is way more likely to agree with itself.” In her research, Gao developed a way to mitigate the problems inherent in double dipping to make statistical analysis more effective.
Gao is primarily focused on developing statistical methods for problems found in the genome sciences. In the past several decades, researchers have developed technologies to measure the activity of every gene in the human genome. “Once you’ve gathered all those measurements, it’s hard to know what questions to ask,” she reflected. “My goal in developing new statistical tools is to identify interesting patterns in the data that help me ask the right questions.”
In addition to the support she has received from her colleagues in the Faculty of Mathematics, Gao points to the variety of her work as the highlight of her time at Waterloo so far. “It’s incredible to have so much freedom and flexibility to explore research directions that interest me,” she concluded. “I’m looking forward to what’s ahead.”