Brin Postdoctoral Fellow Agnieszka Zelerowicz took a chance by leaving Poland, and it set her on a challenging new path.

Brin Postdoctoral Fellow Agnieszka Zelerowicz was first drawn to mathematics in college when she discovered the theoretical side to math. 

“I was always good at math, but it was just not very interesting to me until I took some advanced courses,” Zelerowicz recalled. “It was intro to topology or something, and it was so different from anything else. I think the abstraction of it is what drew me in.”

While others in her class struggled with the more abstract subjects, Zelerowicz found they came easily to her, and she began to recognize her strength in mathematics. 

“Agnieszka has many original ideas and is not afraid to stand by them,” said Dmitry Dolgopyat, Zelerowicz’s mentor at the University of Maryland.

Zelerowicz is one of five Brin Postdoctoral Fellows who are supported by a generous gift from Mathematics Professor Emeritus Michael Brin. The Brin Postdoctoral program in UMD’s Department of Mathematics supports young mathematicians whose work shows remarkable promise in mathematical research.  

“Agnieszka shows curiosity and fearlessness in attacking new problems, which has led in a short time to a remarkable breadth in her research,” said UMD Mathematics Professor Giovanni Forni. “She has great technical skills and the ability to work very hard, qualities that are important to succeed in mathematical research. Among the promising aspects of her work, she has pushed the boundaries of fundamental tools to study chaotic systems using tools of geometry.”

Zelerowicz works in the area of ergodic theory and thermodynamic formalism. Both are areas of mathematics that focus on understanding dynamical systems. In mathematics, these systems can be described by determining the location in space of a given point at a given moment in time. (Think of models that predict the motion of a pendulum or the diffusion of a particle of smoke into a room). 

“This work is theoretical, and it deals with mathematical models, not physical objects,” Zelerowicz explained. “But it has very strong connections to physics, so it borders on being applied.”

One of the applications of the mathematics she works on can be useful in studying electricity and conductive metals. Imagine a billiard table where a tiny particle representing an electron bounces around between the billiard balls, which represent the atoms of metal. Although the electron’s behavior may look random, mathematics can describe the probability of the electron taking various paths depending on a variety of factors, such as where it originates, its velocity, the temperature in the room, among other things. Using these probabilities, mathematicians can build a model of the electron’s behavior under different conditions. 

Applying this idea, Zelerowicz is collaborating with Assistant Professor of Mathematics Rodrigo Trevino on a new model for studying how electricity moves through materials with long-range structure, such as certain types of crystals.

“It is challenging to find this middle ground in mathematics—to find a problem that would be difficult enough so that it would be interesting, but still something that is not impossible to solve,” she said. 

As Zelerowicz searches for her next problem to solve, she is also looking for her next career step after she completes her postdoctoral fellowship in summer 2022. She is investigating opportunities throughout the U.S., but also countries like Brazil. It’s a surprising twist for someone who never imagined living outside of Poland. 

Zelerowicz grew up in Rutki-Kossaki, a small town in Poland where her parents ran a bakery and her entire extended family has lived for generations. After high school, she went to the University of Bialystok in Poland and earned a bachelor’s degree in financial mathematics, followed by a master’s degree in mathematics in engineering from the Warsaw University of Technology. 

“I never really considered moving abroad, but when I was doing my master’s, I met a lot of people who were planning to study abroad or who already did study abroad,” Zelerowicz explained. “At first, I was almost startled by the whole idea, by the very thought of moving to a country where I was asked to speak a foreign language the whole time. I thought it would be very uncomfortable. But then over time I thought, ‘Wait, I'm just as smart as those other people.’”

When it came time to apply for her Ph.D., Zelerowicz threw just one arrow outside of Poland, aiming at The Pennsylvania State University. 

“I didn't even view it as a realistic goal,” she remembered. “I think I had all the intentions of staying in Poland. Applying to Penn State was just an experiment to see what would happen.”

Her arrow hit a bullseye, and she packed her bags and moved to Pennsylvania in 2013. After earning her Ph.D. in mathematics, she came to UMD in 2019. New to Maryland, Zelerowicz had a tough time when the COVID-19 pandemic hit in 2020. She hadn’t built her social network here, and she was unable to visit her family in Poland. To combat the isolation, Zelerowicz leaned into the physical fitness and outdoor activities she had come to love at Penn State, especially rock climbing.

“Climbing is a lot like solving a math problem in the way that you position your body and solve a challenging route,” she said. “Sometimes when certain transitions or moves on a route seem very hard and almost impossible, but then you change the angle of your body a little bit and move your foot a very little bit to the side, and then suddenly it becomes easy.”

In climbing, as in mathematics, things become easy only through hard work, ample technical skills and a bit of fearlessness—qualities that should help Zelerowicz continue to succeed in the years ahead. 

Written by Kimbra Cutlip

Ren uses statistics to make sense of a messy world.

Joan Jian-Jian Ren is a problem-solver. The University of Maryland mathematics professor develops tools to analyze large, messy biomedical datasets. Although much of her work delves deep into theoretical statistics, her research has real-world applications for helping make sense of the enormous volumes of data collected today.

“There are many situations where we don’t have methods to analyze the data that we have,” Ren said. “People are collecting huge volumes of data, but if we can’t analyze it properly, then we can’t really get useful information out of it or come to the most accurate possible conclusions.”

Take vaccination data, for example. The U.S. Department of Health and Human Services houses a database with more than a half-million reports on the adverse effects of vaccines but extracting a clear story from the data isn’t easy. 

“The structure of this data is very complex,” Ren said. “For example, when you take your kid to get vaccines, they will get maybe three or four shots at one time. So, when they get a fever or some other adverse reaction, how do we know which vaccine triggered it? Or, if the reaction comes three days or four later, how do we know what variables are involved in causing that reaction?”  

To answer those questions, Ren applies statistics and data visualization tools she develops with colleagues from the University of Michigan Medical School and the University of Maryland School of Medicine. They are beginning to find patterns that indicate which vaccines cause which types of reactions. Ren also develops statistical methodologies to better analyze and understand data on AIDS and certain cancers. Their findings may eventually help regulatory agencies set medical standards and make recommendations for treatments and preventions. 

That’s exactly what happened when Ren dug into the data on breast cancer screenings two decades ago. Scientists had been struggling to determine how frequently women needed to have mammograms and at what age to detect the earliest stages of breast cancer. Ren and colleagues from the University of Nijmegen in the Netherlands concluded that mammogram screenings once every two years was sufficient for early detection of breast cancer in women over 70 years of age, but not in women under 70. 

“Our research concluded that every two years was not frequent enough for detecting primary cancer in women under 70,” Ren said. “And it opened the debate about the appropriate frequency of screening mammograms in women under 70.”

Guidelines still vary widely among different institutions and agencies, but Ren’s work had real-world applications, because most recommendations suggest less frequent mammograms for women over 70. 

“I find it very exciting to use mathematics in a meaningful way that can really help people,” Ren said. “It is always rewarding to work on a challenging mathematics problem, and it makes me happy to see the significance and importance of the results.” 

Ren discovered the rewards of solving difficult math problems when she was still in high school in Beijing, China. She did well in mathematics competitions and often found herself helping friends work through challenging math problems. She enjoyed the feeling of being good at math, but when she realized it was something she wanted to pursue as a career, Ren had to navigate a critical non-mathematical problem.

“My mother really didn’t want me to study math,” Ren recalled. “In China, girls were not encouraged to do math. It was seen as something girls didn’t do.”

Ren was good at foreign languages and writing, and her mother tried to persuade her to become a translator or something more traditionally associated with women’s jobs in China. 

“That was a huge fight. It was a very difficult decision for me,” Ren remembered. “Then my high school math teacher got involved. He had a meeting with my mother, and she laid off after that.”

Thanks to her math teacher, Ren studied mathematics at Peking University. In 1985, she moved to the United States to earn her Ph.D. in theoretical statistics from the University of North Carolina at Chapel Hill. There, she found very different attitudes toward women in mathematics.

“One of the biggest differences when I came to this country is I felt that, overall, they supported women much more,” Ren said. “All my professors were very supportive, and I don’t feel that they treated me differently as a girl or that I didn’t belong in math because I was a girl.”

After earning her Ph.D. in 1990, Ren joined the faculty at the University of Nebraska–Lincoln and then moved to Tulane University and the University of Central Florida. She earned tenure in Nebraska and was a professor before coming to UMD in 2011.

“Her work in biostatistics was very exciting, and she was really an expert at what she was doing,” said UMD Mathematics Professor Benjamin Kedem, who recruited Ren to UMD. They met when she was giving an invited talk at an international statistics conference in Washington, D.C. 

“Jian-Jian’s work refined a well-known statistical model called the Cox proportional hazards model, and with her expertise and talent I knew it would be a benefit to the department to have her here,” Kedem said.

The Cox proportional hazards model is used in medicine to determine survival rates or hazard risks (such as a person’s risk of dying of cardiovascular disease over the next five or 10 years) based on different variables. 

The move to Maryland turned out to be a good decision for Ren and her young son. The department welcomed her warmly and supported her work, and her son was able to excel in the local school system. He will soon graduate from UMD with a B.S. in mathematics at just 19 years old. 

As a soon-to-be empty-nester, Ren may have more time for playing tennis and piano. But one thing is certain, she will continue to be motivated by the big questions that lie hidden in biomedical data, just waiting for someone like her to help tease out the answers. 

“Statistics is only going to become more and more important in the era of big data,” Ren said. “I would love to see more statisticians here at Maryland working with experts from other departments to understand how to analyze and understand the data. There are a lot of problems big data can help solve but only with the right tools.”

Written by Kimbra Cutlip

An internationally renowned mathematician in probability theory, Freidlin was once a Russian “refusenik.”

After more than 30 years at the University of Maryland, Distinguished University Professor Emeritus of Mathematics Mark Freidlin retired on July 1, 2021. After being barred from leaving his home country 40 years ago and shut out of academic life for nearly a decade, Freidlin moved to Maryland and traveled the world as an invited speaker at prestigious mathematical conferences and research institutions. 

Freidlin was born in Moscow and began his career in mathematics during the Cold War between the United States and the former Soviet Union. As a professor of mathematics at Moscow State University in the 1960s and ’70s, Freidlin earned both privilege and status in a country that valued higher education and revered rigorous intellectual pursuits. 

But as a person of Jewish descent, Freidlin was also subjected to government harassment, discrimination and policies that limited his professional and economic opportunities. He applied for an exit visa in 1979 with hopes of leaving the Soviet Union with his wife, Lera, who was also a mathematician, and their two children. They were denied an exit visa without an explanation, and they were promptly fired from their jobs and barred from publishing papers in the Soviet Union or attending scientific conferences. 

During those years, the Soviet Union ran a brutal political campaign to separate its citizens and citizens from other East bloc countries from the Western world behind what Winston Churchill called the Iron Curtain. Scientists and mathematicians were often denied permission to leave the country. After Freidlin and his wife requested permission to emigrate, they were labeled “refuseniks”—Soviet citizens denied the freedom to leave their country by the Soviet government. Freidlin was 41 years old.

For eight years, Freidlin and his wife made a living as tutors. Lera also got work translating documents, and Freidlin continued working on mathematics on his own. But he had already earned an international reputation, in part because of a book he and his colleague Alexander Wentzell published right before he was shut out of academia.

“I waited until after the book was published to apply for an exit visa, because I knew if I applied before, the book would never be published,” Freidlin recalled.

The book was first published in Russian in 1979 and was translated into English in 1984. Several editions followed, with the latest published in 2012. The book introduced a theory, now known as the Freidlin-Wentzell theory, which explains how small, seemingly insignificant, perturbations in complicated systems can create critical changes in the system over long time periods. The theory is widely used in mathematical modeling in fields as diverse as physics, biology, economics, and the social sciences.

The Freidlin-Wentzell theory laid the groundwork for much of his later research that seeks to describe the effects of small random fluctuations on dynamical systems. 

“In many mathematical models, if you don’t take into account random perturbations in the system, that may work fine over certain time intervals,” Freidlin explained. “But over longer time intervals, these perturbations can become critical enough to cause a transition from one stable behavior to another stable behavior, and our goal is to describe these transitions.” 

Freidlin would eventually work with Wentzell again, years after the Soviet Union fell and they were both in the U.S., but in the eight years between publication of his first book and his arrival in Maryland, Freidlin was forced to work largely on his own. During that time, his western colleagues helped Freidlin communicate with the outside world. 

Visiting colleagues smuggled Freidlin’s letters and academic papers out of the country, and he remained an important figure in the world of mathematics, publishing several papers in academic journals outside of the Soviet Union during his time as a refusenik.

But those papers represented just a fraction of Freidlin’s work during those years, so he compiled his unpublished works into a second book that his wife translated into English. They had it smuggled out of the country, and his former Ph.D. advisor Eugene Dynkin arranged for it to be published through Princeton University Press. Dynkin left the Soviet Union in 1977 and was teaching mathematics at Cornell University. 

“A colleague carried it out of the country,” Freidlin recalled. “We changed the cover page to make it look as if he was the author of the book so that if he was caught it would not appear to be mine.”

Freidlin’s second book “Functional Integration and Partial Differential Equations” was published in 1985. Two years later, under pressure from the international community, the Soviet government granted Freidlin and his family permission to leave. He and Lera packed up their two children and moved to Maryland in 1987.

“I had some other offers from different countries,” Freidlin recalled, “but various colleagues including Dynkin convinced me to go to Maryland.” 

Lera took a job as a statistician at the National Institutes of Health. And after waiting so many years to leave his homeland, Freidlin embarked on a few years of travel to share his mathematical ideas as an invited speaker in France, Israel, Germany, Italy, England, Canada, and all over the U.S. He was even an invited speaker at the International Congress of Mathematicians in 1998.   

“After eight years, we were happy to come to the United States,” he said. “I had liked to teach students, and I enjoyed teaching again and being able to travel and talk with colleagues openly. I was very happy.” 

During his tenure at UMD, Freidlin mentored more than a dozen Ph.D. students and several postdoctoral associates. He has given more than 170 invited talks around the world and published nearly 100 refereed papers (making a combined total exceeding 150 papers over the course of his career). 

Through these works, Freidlin made prolific contributions to the field of stochastics, which is the study of complex processes that can be analyzed and predicted statistically but defy prediction of precise outcomes. 

“I was very lucky to be a mathematician,” Freidlin said. “It is very interesting work, and it’s a world where you can live outside these other problems you know. There is always something interesting in mathematics that you can be challenged to think about and to solve.” 

Freidlin will continue to work on mathematical theories in his retirement and spend more time with his grandchildren. He also looks forward to resuming travel once the threat of COVID-19 is in the rearview mirror. Hopefully, he should not have to wait eight years.

Written by Kimbra Cutlip