Women in Optimization: Dr. Sophie Huiberts

This article is the second in our new series, “Women in Optimization.” Although these articles will highlight women, we hope the stories will encourage all individuals who might want to pursue a career in optimization.

One of the most fundamental algorithms in operations research and optimization, the simplex method has been applied to many different fields—from economics to engineering and logistics.

However, from a theoretical perspective, this notorious algorithm has long been a mystery: It works incredibly well in practice, but its worst-case performance is exponential—which means that in some cases, it can take an extremely long time to find a solution.

For decades, researchers have tried to explain this phenomenon, but with relatively little progress.

Determined to find answers, Sophie Huiberts used her groundbreaking PhD work to take the research community’s understanding of the simplex method to new heights, ultimately opening up new directions for research.

Learning to Love the Simplex Method

As a Research Fellow at France’s National Centre for Scientific Research (CNRS), Huiberts spends her time proving theorems about algorithms—something she’s been passionate about for years.

“I knew that I wanted to get into algorithms pretty much as soon as I got access to a computer,” says Huiberts. “I’ve always found it super interesting how computers work and do all the things they do.”

She did not, however, always have a passion for the simplex method.

“During my undergraduate studies, I took a class on mathematical optimization—specifically, the simplex method,” she explains. “I hated every second of it. I didn’t understand a thing, and I actually failed the class.”

So what changed?

While pursuing her master’s degree in mathematical sciences at Utrecht University, she took a course on modern approaches to algorithm analysis, led by Daniel Dadush, who would later supervise the work for both her master’s and PhD theses.

“It’s a good thing I didn’t know the class would be on the simplex method, because I might not have signed up. But I learned so much more about research and the questions that exist today around optimization algorithms. I just fell in love with it,” says Huiberts. “And these days, most people know me because of my work on the simplex method.”

Indeed, for her master’s thesis on the smoothed analysis of the simplex method, Huiberts and Dadush worked through the existing proof, seeking ways to improve on the previous results and make it easier to understand. And for her PhD research on the subject, Huiberts was awarded the Gijs de Leve Prize 2020-2023—the first woman to take the prestigious prize.

“Smoothed analysis has always had a reputation for being very difficult, because if you actually wanted to do these calculations and prove this type of upper bound on the running time of the simplex method, the full proof is something like 60 to 100 pages. So people seemed to be very grateful to have this line of work become slightly less scary,” she recalls.

Finding Her Voice—And Her Passion

Despite her revolutionary work on the simplex method and an astonishing list of career achievements, Huiberts admits she is no stranger to imposter syndrome.

“For about half of my projects, I feel super on top of everything that we’re doing, and I have the easiest time in the world with my research,” she explains. “But in the other half, I feel like I’m just way out of my depth, like I’m just along for the ride to learn what my co-authors have to teach me.”

It’s a feeling she’s learned to grow comfortable with, and one she believes many in her field experience regularly—even if they’re less vocal about it.

Because after all, as Huiberts says, “Research is all about discovering new things. And if the question you’re answering is easy, then you should question whether it’s really research to begin with.”

Now, as a full-time researcher, Huiberts finds herself facing a different type of challenge: saying no.

“Recently, I’ve been saying yes to too many things—serving on committees for conferences, reviewing papers, or traveling to give talks. My past few months have been a whirlwind, so saying no is a skill I’m still working on,” she shares.

Still, she finds time to ponder the complex questions that her work demands answers to. And lately, she’s also been nurturing other interests.

“I’ve been learning a lot about women’s history,” she says. “For example, at one of my recent talks, I spent the first 10-15 minutes discussing the first human computers—and how they were typically women or minorities—all of whom were good at math, but because of the barriers that existed at the time, they couldn’t get a job as a mathematician. So I’ve been shining a light on that.”

As for her career plans, Huiberts is content with her work and intends to stay in this field for the foreseeable future.

“Honestly, I can see myself doing what I’m doing for years ahead. Who knows? At some point, maybe something else will cross my path, but for now I’m in a good place. I really like what I’m doing right now, and I’m happy to keep doing it,” she says.

Her advice to students and anyone seeking a career in research or optimization is to “not be afraid to take up space.”

“At the beginning of my PhD, I felt like I was intruding in a space that I wasn’t supposed to be in. I was very nervous about just being there, about having opinions,” she shares. “Over time, I just grew more comfortable, and started to actually feel like part of the research community. So my advice to anyone starting out in their career is to dare to take up space, and don’t be afraid to make your voice heard.”

To learn more about Sophie Huiberts and her latest projects, visit sophie.huiberts.me. And keep an eye out for more Women in Optimization articles this year.