Music, biking and family keep former mathematics department chair busy

When Scott Wolpert first heard his two tween daughters practicing clarinet, it was like a squeaky, off-key invitation to join them.

“I was listening to them and thinking, ‘I’m sure I can play like that,’” Wolpert remembered. “So, I started taking lessons with them.”

That was more than 20 years ago, and Wolpert, who retired from the University of Maryland as a professor emeritus of mathematics in September 2020, continued to take clarinet lessons on and off ever since. He is known for teaming up with other faculty members like Harry Tamvakis and Bill Goldman (who also happens to be his brother-in-law) to play music. Wolpert even convinced the chair’s office coordinator, Stephanie Padgett, to perform with him at the department holiday party in 2017, her first year at UMD.

That was “classic Wolpert,” according to Wolpert’s colleagues who gathered on Zoom for a virtual conference in March 2021 to celebrate his retirement and 70th birthday. “He’s such a nice guy, he’s hard to say no to,” one of the participants remarked as others chuckled in agreement. 

More than just a nice guy, Wolpert is also an accomplished mathematician and a dedicated educator who made significant contributions to the university and the department. During his tenure as department chair from 2013 to 2019, the number of math majors increased by 31%, including a 23% increase in women. The number of bachelor’s degrees awarded in mathematics also grew, with a 48% increase overall and a 57% increase in the number awarded to women. Wolpert also hired eight assistant professors and 15 long-term lecturers, and the annual credit hours taught by mathematics increased by 12,000 during his leadership.

As the associate dean for undergraduate studies from 2000 to 2009, Wolpert was instrumental in reorganizing the campus Individual Studies Program, which enables students to customize their major to their own cross-disciplinary interests. He also cultivated stronger relationships with community colleges to encourage their students to continue their education at UMD. As a professor in the 1990s, Wolpert introduced a calculus workshop aimed specifically at helping underrepresented minorities succeed in calculus.

For these and other contributions, Wolpert received a UMD Distinguished Scholar-Teacher Award in 1992-93 and the Kirwan Undergraduate Education Award in 2016. 

Wolpert came to UMD in 1976 as an assistant professor, after earning his M.S. and Ph.D. in mathematics from Stanford University. He earned his B.S. in mathematics from Johns Hopkins University. A Fellow of the American Mathematical Society and recipient of a Sloan Research Fellowship, Wolpert’s research focused on the geometry of hyperbolic shapes—think of the shape of a concave disc or a saddle. Among his peers in hyperbolic geometry, he is best known for a collection of findings about how changes in shape affect the path of light across a surface. 

In the broader math world, Wolpert is known for helping to answer the question of whether mathematicians could predict the shape of a drum based on the sound it makes. For most drum shapes, Wolpert found, they can’t. It’s an important question with practical implications for any technology that analyzes signals resonating off a surface, like an MRI for medical imaging. 

But when asked what he is most proud of, Wolpert refers to his accomplishments as an educator and administrator. He is adamant about the importance of focusing on the student experience. 

“On a day-to-day basis, the most important thing a faculty member does is teaching in the classroom,” he said. “Even my colleagues who are hardcore focused on their research totally agree with that statement.”

Wolpert traces his passion for math education to the influence of excellent teachers, especially math teachers, throughout his high school years. They helped him recognize the importance of an effective learning environment and good mentors. It also helped that he grew up in a mechanically inclined family. His father was an engineer who always spoke highly of mathematics, and his mother was a registered nurse and a homemaker with a talent for sewing who instilled in him a curiosity for how things work. 

“Sometimes when my mom was using her sewing machine, she'd say, ‘Hear that sound, that means it needs to be oiled,’” Wolpert remembered. “And she’d get out her oil can and just flip this old Singer over and point to where it needed oil. So, there was always an inclination toward the mechanical growing up.”  

Wolpert may have had strong influences directing him toward a STEM career, but there was always something about mathematics in particular that appealed to him.

“I've always loved what mathematicians call the purity of it,” he said. “For example, when you talk about points and lines and planes, these are pure concepts. We know what they are. We don’t need a model to understand them. And as mathematicians, we don’t need them to physically exist to work with them. I was always fascinated by that aspect of math.”

In his retirement, Wolpert continues to be involved with mathematics education as a senior consultant for Transforming Post-Secondary Education in Mathematics (TPSE Math). Directed by William Kirwan, University System of Maryland chancellor emeritus and UMD professor emeritus of mathematics, TPSE Math promotes activities that prepare students to use mathematics productively regardless of the field they choose. 

“We want to make sure that the math curriculum at universities gives students the skills and know-how to take advantage of the opportunities available to them in today’s job market,” Wolpert said. “This aligns with the kind of work that I’ve always done, so I’m very committed to continuing with this goal.”

In addition to spending more time with TPSE Math since he retired, Wolpert spends much more time on his bicycle. He’s always been an avid bicyclist, riding both road and mountain bikes. In the past few years, he focused on road riding, and throughout much of 2020, Wolpert and his daughter biked together daily, averaging around 80 miles a week. 

And, of course, he’s taking music lessons. In fact, his daughters convinced him to start his own YouTube channel to share his practice sessions. It’s called “Baroque my heart.” So far, he hasn’t persuaded any other faculty members to join him in his videos, but he’s just getting started and he’s looking for a vocalist.

Written by Kimbra Cutlip  

The Distinguished University Professor will deliver the prestigious Gibbs Lecture at the 2022 American Mathematical Society meeting

Eitan Tadmor will tell you that success in mathematics comes not from calculating the correct answer, but from finding the right question. 

“I could ask a million questions and do the calculations to answer them, but this is not the point,” said Tadmor, who is a Distinguished University Professor of Mathematics at the University of Maryland. “The point is to find the most natural question. Maybe you start with one idea and you see your question needs to be reformulated, maybe relaxed, maybe strengthened. You try different approaches until you get the right equilibrium.”

When the question is right, everything falls into place. Tadmor likens it to a composer striking the perfect combination of piano keys to complete a beautiful symphony. 

“It doesn’t happen many times, but when you get it right, the feeling in that exact moment is incomparable,” he said. 

Tadmor has experienced that feeling of success on more than one occasion. His ideas on the theory and computation of differential equations have contributed to groundbreaking results in multiple arenas, from shock waves and digital image processing to flocking behavior and emerging consensus of opinions.

Well-known and respected for his contributions to mathematics and his leadership in the field, Tadmor was invited by the American Mathematical Society to give the prestigious Josiah Willard Gibbs Lecture in 2022. He will be the fourth Gibbs Lecturer on the UMD faculty, following in the footsteps of Jan Burgers in 1959, Elliott Montroll in 1982 and Michael Fisher in 1992. The public lecture, which over the years has been given by Fields medalists and Nobel laureates, including Albert Einstein, was established in 1923 to share mathematics’ important societal contributions with the public. 

It should come as no surprise that Tadmor was selected. His research has addressed issues at the forefront of many fields of scientific research important to modern society. And throughout his career, he has been instrumental in fostering collaborations across disciplines that apply mathematics to some of society’s most pressing concerns.

His current research in kinetic theory uses mathematics to describe and model how small fluctuations translate into the properties observed in large systems. One example of kinetic theory is how flocks of birds appear to move as one flowing entity even though each bird behaves as an individual and is aware only of the movement of its neighbors. 

Tadmor recently became interested in using kinetic descriptions to understand how groups of people form consensus. He is finding, for example, that consensus is more likely to form in communities whose members tend to seek out other individuals with views that differ from their own, compared with communities where members seek out others with the same opinions.

“It’s fascinating that when I started talking to people about this work of so-called collective dynamics, I realized that almost everyone has an opinion about opinions,” Tadmor said. “This topic is very important to people, and it is way more engaging to the general public than anything I have done before.” 

Understanding how large groups of people form opinions and build consensus is increasingly important in the age of social media and political division around the globe. Tadmor’s research in this area will be especially appropriate for his Gibbs Lecture, which draws a large public audience. 

Coincidentally, Tadmor has a direct connection to the mathematical work of Josiah Gibbs, the namesake of the talk. Gibbs was a highly esteemed American mathematical physicist, who first pointed out one of the key challenges in using high-resolution mathematical descriptions of shock waves—something Tadmor helped find a solution for early in his career. 

Shock waves are formed by passing through sharp transitions, the way a supersonic jet creates a shock wave when it accelerates beyond the speed of sound. The sound barrier the jet passes through may be invisible, but the transition is real and distinct. And that type of sharp transition creates challenges for mathematicians trying to make computations to describe shock waves at high resolution. Those challenges are known as Gibbs oscillations because Gibbs described them in 1899. In the 1980s, Tadmor was among the mathematicians who helped overcome the challenges created by Gibbs’ oscillations. 

More than a decade later, Tadmor applied the same theory and technology he used to compute shock waves to processing high-resolution digital images. He recognized that from a mathematical standpoint, the visual appearance of edges in images—the edge of a nose or the outline of a jaw, for example—could be handled much like the sharp transitions of a shock wave. 

Digital images are made of thousands of tiny pixels on a screen or page, and it is the sharp variation in the intensity of side-by-side pixels that gives the appearance of edges. To create high-resolution digital pictures, those sharp transitions must be managed mathematically during image processing. Tadmor accomplished that by introducing a novel method of processing images which uses hierarchical composition to adapt to the shockwave-like sharp transitions in images. 

Throughout his career, Tadmor has been known for thinking outside the box and for bringing experts from different disciplines together to help them apply rigorous mathematics to important scientific challenges. In 2002, he came to UMD to direct the Center for Scientific Computation and Mathematical Modeling (CSCAMM), which he led until 2016. CSCAMM encouraged cross-fertilization of research activities between different scientific fields utilizing scientific computation and mathematical modeling, which fit perfectly with Tadmor’s natural inclinations to create and foster cross-disciplinary collaborations. 

He also directed Ki-Net, a National Science Foundation (NSF)-funded network for research and collaboration in kinetics descriptions and their applications, from 2012 to 2020. Tadmor established Ki-Net as an expansion of an NSF-funded focus group he led from 2008 to 2012.

Ki-Net brought together over 1,000 researchers—including physicists, chemists, socials scientists and mathematicians—who studied everything from how cells organize to form organs and tumors to how traffic flows to how weather develops and the dynamics of quantum systems. 

Prior to joining UMD, Tadmor co-founded the NSF-funded National Institute for Pure and Applied Mathematics at UCLA in 2001. With such a long track record of applying mathematics across many different disciplines, it might be easy to assume Tadmor is one of those mathematicians who sees the world largely through equations and numerical models. But he rejects that characterization. 

“Math is first and foremost a language,” he said. “It happens to be the language with which we effectively describe physical phenomena in our world, and it’s enriching to understand how these processes work. But there are many dialects to math, and I think the most fascinating aspect of mathematics is the imagination it requires. When you think about problems that are ignited by practical issues, and they translate into mathematical language, which is very formal, and then you have to use your imagination in order to reveal some sort of connection to or expansion of the underlying phenomena, I think it's fascinating.”

No matter what he’s doing, the language of mathematics is always running on a loop in the back of Tadmor’s mind. 

“I am definitively the person who wakes up every morning with my mind completely bothered by the problem that I was thinking about at the end of last night,” he said. “And this is fantastic, because it is like my hobby. I would be doing it no matter what. And here I am, getting paid to think about these things.”

Written by Kimbra Cutlip

Yuan will take the National Defense Science and Engineering Graduate Fellowship to the University of Illinois at Urbana-Champaign

In high school, many students are drawn to competitive sports. Some play football, some play basketball or lacrosse. Linden Yuan’s sport was math.

“In high school I participated in math competitions. I found math fun. I would have to answer a series of math questions individually under a certain amount of time,” he said.

Yuan, a senior mathematics major, carried his passion for math with him throughout his time at the University of Maryland. When he isn’t in his math classes, he reads books about math for fun.

“I love math because mathematics gives us the power to formulate precise statements of vague or complicated ideas,” he said. “We can also use math to design detailed and sophisticated ways to answer questions.”

Yuan has been doing that during his research experiences at UMD, including investigating queueing theory with Smith Chair of Management Science Michael Fu in the Robert H. Smith School of Business, examining machine learning techniques with the Mathematics Professor Wojciech Czaja, and analyzing data from high-energy physics in the Honors seminar, "Cracking the Secrets of the Universe with Computers," where he worked with Physics Professor Kaustubh Agashe.

Yuan will continue his research career in graduate school, thanks to the Department of Defense’s National Defense Science and Engineering Graduate (NDSEG) Fellowship he received. The program, established in 1989 by direction of Congress and sponsored by the U.S. Army, Navy, and Air Force, serves as a means to increase the number of citizens trained in science and engineering disciplines of military importance. 

Landing this fellowship reminded Yuan of the mathematics competitions he participated in over the years. But this time, his competition was the rest of the nation. The NDSEG fellowship is highly competitive, having awarded just over 4,000 fellowships out of 60,000-plus applications since the program’s inception. 

Yuan will be taking his fellowship to the University of Illinois at Urbana-Champaign, where he will pursue a Ph.D. in electrical and computer engineering. The fellowship will support him for three years and pays for full tuition and all mandatory fees; it also offers a monthly stipend and travel expenses.

“I’m so thankful for this opportunity and the freedom that this fellowship offers me,” Yuan said. “Now I don’t have to worry about paying for school or finding a job. I only have to focus on my research.”

Yuan will study information flow on complex mathematical networks for his Ph.D. research. 

“Imagine someone starts spreading information from a given point in the network. Then, you make observations at other points, farther away in the network,” he explained. “Using these observations, what can you say about the original starting point? I'll be using tools from electrical engineering and discrete probability to answer that question.”

Because math is Yuan’s favorite sport, an opportunity like this is like going to the championship. He looks forward to seeing his mathematical research make a difference in a real-life scenario.

“My application for the fellowship included a research proposal where the Department of Defense saw real-world value in my work,” Yuan said. “I’m so grateful that the fellowship allows me to do the research that I want to do and that it can be applied to real life.”

Written by Chelsea Torres

The scholarship encourages students to pursue advanced study and research careers in the sciences, engineering and mathematics.

University of Maryland junior Naveen Raman was awarded a scholarship this year by the Barry Goldwater Scholarship and Excellence in Education Foundation, which encourages students to pursue advanced study and research careers in the sciences, engineering and mathematics.

Raman is a computer science and mathematics double major who is also a member of the Advanced Cybersecurity Experience for Students in the Honors College. 

Raman was among the 410 Barry Goldwater Scholars selected from 1,256 students nominated nationally this year. Goldwater Scholars receive one- or two-year scholarships that cover the cost of tuition, fees, books, and room and board up to $7,500 per year. These scholarships are a stepping-stone to future support for the students’ research careers. The Goldwater Foundation has honored 73 UMD winners and five honorable mentions since the program’s first award was given in 1989.

Raman, who is a President’s Scholarship recipient from Derwood, Maryland, began working with UMD computer science faculty members in 2018. Since then, he has published four papers and submitted a fifth for publication.

He began by developing algorithms to identify cancer mutation signatures with Distinguished University Professor Aravind Srinivasan and former Assistant Professor Max Leiserson and moved on to working with Assistant Professor John Dickerson to develop policies that balance fairness and profit in ride-pooling systems.

He’s also currently working with Associate Professor Jordan Boyd-Graber to improve question answering systems by leveraging data from trivia competitions. Raman’s focus is on advancing so-called named entity linking algorithms, which connect names found in a question to larger repositories of data about them like Wikipedia. These advances will ultimately help question answering systems perform better on a diverse set of questions.

“Naveen Raman is a clear star researcher—and practitioner—in the making,” Dickerson said. “He is driven, questioning, curious and technically talented, as well as a young adult with a strong sense of civic duty and commitment to using technology for social good.”

In Summer 2019, Raman worked to detect rudeness, toxicity and burnout in open-source communities as a participant in Carnegie Mellon University’s Research Experience for Undergraduates in Software Engineering program. Last summer, he worked at Facebook to develop a user interface for debugging machine learning models and learned about important societal issues that machine learning can help solve, such as hate speech detection.

An active competitor, Raman’s team won the National Academy Quiz Tournaments’ Division 2 Intercollegiate Championship Tournament during his freshman year. In 2020, he and two classmates received an honorable mention award in the 72-hour Mathematical Contest in Modeling for their project that analyzed the effect that rising global temperatures have on herring and mackerel fishing along the Scottish coast. He also received an outstanding award in the 2020 SIMIODE Challenge Using Differential Equations Modeling for his team’s work on modeling interactions in refugee camps.

He has been a teaching assistant for a programming languages class and the lead student instructor for a class on algorithms for coding interviews. He also serves as vice president of UMD’s Puzzle Club.

Off campus, Raman teaches literacy skills to underprivileged elementary school students in the Maryland Mentor Program and volunteers at the College Park Academy charter school helping students improve their math skills.

He has been awarded the Brendan Iribe Endowed Scholarship, Capital One Bank Dean’s Scholarship in Computer Science and Corporate Partners in Computing Scholarship.

Raman plans to attend graduate school to pursue a Ph.D. in computer science, with a focus on the fairness of artificial intelligence algorithms in critical fields such as criminal justice, job markets and health care.

Written by Abby Robinson

Tasha Inniss (Ph.D. ’00) and her classmates Sherry Scott and Kimberly Weems were the first Black female mathematicians to earn doctorates from UMD.

Tasha Inniss didn’t plan to make history when she began pursuing her Ph.D. in mathematics at the University of Maryland in 1995, but she ended up doing just that. In 2000, Inniss and two of her classmates—Sherry Scott and Kimberly Weems—became the first group of Black female mathematicians to earn Ph.D.s from UMD. Inniss and Weems earned their doctorates in applied mathematics and Scott earned hers in mathematics. 

“As I was submitting my paperwork for graduation, the woman processing it said, ‘I think you might be the first Black woman to get a Ph.D. in math from Maryland,’” Inniss recalled. “I didn’t believe it at first, but once it got closer and closer to graduation, we found out that it was true." 

Inniss, a New Orleans native, loved math as a child and later discovered she enjoys helping others understand math.

“I’ve loved math since the fourth grade. It was fun to me, like putting together a puzzle,” she said. “When I went to college, my friends used to ask me to help them with math, and that was when I realized I was good at helping people understand it. So, it was around then that I decided that I wanted to teach math on the college level, and I needed a Ph.D. to do that.”

Inniss went to college at Xavier University of Louisiana, the only historically Black Catholic university in the country.

“Xavier is a family school. My aunts and uncles went to Xavier, and my Uncle Clarence is a mathematician and taught in the math department long before I got there,” she said. “I applied to many schools, but once I attended a summer program at Xavier, I knew it was where I needed to be. It felt like home.”

After graduating summa cum laude with a bachelor’s degree in mathematics from Xavier in 1993, Inniss earned her master’s degree in applied mathematics from the Georgia Institute of Technology. 

“Applied math is where my heart is,” Inniss explained. “I really wanted to do math that helped the world. With operations research and optimization, parts of applied math, it's all about modeling real-world systems to make them better, which is why I love it.”

When Inniss began looking for Ph.D. programs to apply to, one of her friends encouraged her to consider UMD.

“One of my friends who I went to Xavier with had gone to Maryland and said that I should consider the school and that they were really supportive of Black students there,” she said. “I also met the chair of the department, Raymond Johnson, who is an African American man, at a conference for Black mathematicians and he was really passionate about helping people learn and understand math. I said to myself, ‘If he is the chair of the department, then it is probably a really good place to learn.’”

When Inniss arrived in College Park, she was pleased to find such a large community of Black math graduate students.

“There were at least 20 of us, if I recall correctly, and we had a great community,” Inniss said. “We would hold study groups and prepare for our qualifying exams together. We supported each other to help us get to the final prize of our receiving Ph.D.s. in mathematics.”

Johnson was also a huge part of why Black students felt supported in the math department, Inniss recalled.

“Dr. Johnson was the reason why we were all there,” she said. “He was very intentional about diversifying the department and recruiting Black students. Once a month he would hold open dialogue sessions with students to see how things were going and how the department could improve. He was someone that we trusted, so we felt we could be honest and transparent with our feedback.”

As Inniss reached the end of her Ph.D. studies, Scott and Weems were finishing up theirs as well.

“We didn’t plan for it to happen this way, but we actually ended up defending our theses within one week of each other,” she said. “When we got to the end, I thought ‘Wow, we’re really going to finish together and we’re going to be the first Black women to do this.’ We had no idea in the beginning that it was going to be historic.”

After graduating from Maryland, Inniss went on to have an impressive career in mathematics. In 2001, she was appointed the Clare Boothe Luce Professor of Mathematics at Trinity Washington University (then Trinity College) in D.C. The Clare Boothe Luce Program awards annual grants to support professorships and scholarships for women in the sciences and mathematics. After three years at Trinity, Inniss landed her dream job.

“My dream job has always been to teach at Spelman College,” she explained. “Spelman has such a rich legacy and I loved having the opportunity to not only teach math to fellow Black women, but also prepare them for life as mathematicians outside of Spelman.”

Inniss enjoyed exposing students to the beauty of operations research and optimization and its interesting real-world applications.

“Some of my students went on to do amazing projects using applied mathematics, such as how to optimize the schedules for the campus tour guides and creating an evacuation model for the city of New Orleans following Hurricane Katrina,” she recalled. “I loved teaching at Spelman. I had the chance to mentor students and expose them to the beautiful parts of math. It was an amazing experience.”

After nearly a decade, Inniss took leave from teaching at Spelman for an opportunity she couldn’t pass up: doing a rotation at the National Science Foundation (NSF), first as a program director and later as a deputy division director (in acting capacity). After that, she was named founding director of education and industry outreach at INFORMS, an international association for professionals in analytics and operations research. She returned to Spelman in 2018.

“I had the opportunity to come back to Spelman and now I'm the associate provost for research,” Inniss said. “I am able to take all of the things I learned at NSF regarding competitive grants and grant writing and use it to help my faculty colleagues and fund undergraduate research here now. It is all coming full circle. Although I don’t get to teach math anymore, I still love math and I still get to do things that will impact and help students.”

As for the next generation of Black female mathematicians, Inniss wants them to know that as long as they truly love math, they can succeed.

“I firmly believe that what you pursue should be your passion,” she said. “You have to be excited about what you're doing because there will be challenges, but you can do it with support, prayer and hard work.”

Written by Chelsea Torres

How Lee Mendelowitz (M.S. ’12, Ph.D. ’15) stepped up to the plate to become the director of baseball research for the Washington Nationals.

Lee Mendelowitz has had a passion for Major League Baseball since he was a kid. But now when he watches a game, he’s looking for a lot more than runs, hits and errors. 

“I used to just watch the game. Now it feels like I’m watching the game within the game,” he said. “There are just so many more details to pay attention to.”

Mendelowitz isn’t just any baseball fan, though, he’s the director of baseball research for the Washington Nationals. And with both a master’s and a Ph.D. from the University of Maryland’s applied mathematics & statistics, and scientific computation (AMSC) program, he understands the value of every little detail. Whether it’s the speed and trajectory of a pitch, the positioning of players on the field or even the parameters of a particular umpire’s strike zone, Mendelowitz’s job is all about crunching the numbers to help his team win. 

“Baseball is like any business where there are decisions to be made and you want to use all the information you have available to make the best decisions,” Mendelowitz explained. “We’re in the business of trying to win baseball games, so we want to use all the data we have available to try to make those decisions.”

Growing up a Yankees fan

Mendelowitz grew up in Bergen County, New Jersey, rooting for the Yankees and going to games with his dad and his brothers.

“I have a distinct memory of 1996,” he recalled. “I was 10 years old and that was Derek Jeter’s rookie year, and the team went on to win the World Series. And that was the year I really became a Yankees fan and a baseball fan. We went to plenty of Yankees games and that was a big part of my upbringing.”

At school, mathematics and science came easily to Mendelowitz, and they quickly became his favorite subjects. 

“There was a point around seventh grade where I realized I was good at math and I was good at physics and other sciences. It all just came naturally to me,” Mendelowitz said. “I realized I was more interested and engaged than other people in the classroom, and it continued from there.”

Pursuing a calling

From math and physics to computer science, Mendelowitz saw his interests coming together through high school. In 2004, he went to Cornell University, where he earned his undergraduate degree in applied physics. Then, in 2008, he accepted an entry-level systems engineering position at Raytheon Technologies in Massachusetts. 

“I was working as a software engineer in the modeling and simulation group,” Mendelowitz said. “We’d write software to model different situations with this Navy project we were working on, which was kind of interesting.”

But he couldn’t stop thinking about an applied math course that captured his interest while he was at Cornell.

“It was a nonlinear dynamics course taught by Professor Steve Strogatz,” Mendelowitz recalled. “It was all about mathematical modeling with differential equations and complex behaviors that can arise from simple sets of equations. I found that fascinating. And I felt a calling—I wanted to go back to school and pursue applied math.”

Mendelowitz and his then-girlfriend, now wife, Diana Cohn, decided to coordinate their search for graduate schools, and the D.C. area was on the list. While she looked at law schools, he applied to the AMSC program at UMD.

“The thing I really liked about the program was the flexibility it offered and the broad scope of applied math research going on at AMSC,” Mendelowitz said. “I really hadn’t made up my mind at this point about what I wanted to pursue for graduate research other than that I knew I wanted it to involve math and programming.”

Python programs and escalator breakdowns

Mendelowitz earned his master’s degree in 2012 and stayed at Maryland for his Ph.D. It was during that time, in 2013, that he developed an interest in a general-purpose programming language called Python. And just for fun, he used it to launch an ambitious side project: tracking escalator breakdowns in the D.C. Metro system. He called it DC Metro Metrics.

“The initial idea I had was to build this Twitter bot that would tweet every time that an escalator stopped working in the D.C. Metrorail system,” Mendelowitz explained. “I was living in D.C., so I was taking Metro to commute every day back and forth to College Park. When you’re commuting, it‘s especially annoying when escalators don’t work and you have to walk up three stories. So, I thought this would be fun and no one else had done anything like it.”

Due to popular demand, he added elevator outages and other information to the escalator breakdowns, posting it all on a website—dcmetrometrics.com. Interest from the public and the press just kept growing.

“We were getting hundreds of page views a day,” Mendelowitz said. “And I did get a lot of emails, too. Some people really relied on it, which kind of surprised me—people who had disabilities who were trying to navigate the Metro system were looking at my website to view the latest outages instead of using the website that Metro provided. It was a fun learning experience because it was the first time that I’d deployed code to the cloud and made use of a database system.”

He kept dcmetrometrics.com up and running for several years until he no longer had the time or energy to maintain it. 

Bringing baseball back into focus

Meanwhile, Mendelowitz moved ahead with his Ph.D., researching software algorithms that work with a particular type of genomic mapping data. He planned to continue his research through the summer of 2014, until he attended a D.C. data science meetup that unexpectedly brought baseball back into focus. During the meetup, Sam Mondry-Cohen, now assistant general manager of baseball R&D with the Washington Nationals, announced an internship opportunity with the team that just happened to fit Mendelowitz’s applied mathematics and data science skillset. He applied and ended up getting the job.

“I remember I had to be talked into the internship a little bit,” he admitted. “I was on the fence because I was concerned about whether it would be a good decision for my professional development. Here I am trying to wrap up my Ph.D. and I take two-and-a-half or three months off to work in baseball, is that going to set me back in my Ph.D. work? I really was not sure, but the experience ended up being incredible.”

For Mendelowitz, it was an opportunity to look at baseball in ways he never had before—using what he’d learned to see the game from the inside.

“I worked on a project where I was modeling the strike zone of each umpire,” Mendelowitz recalled. “For each umpire it’s slightly different—some are friendlier to the pitchers where they call more strikes, some are friendlier to hitters where they call less strikes, but going even further than that, each umpire has a slightly different shape to their strike zone. Given the location of each pitch and who the umpire was, we can then start to model, using predictive models, what each umpire’s strike zone looks like. It was a great learning experience.”

After the internship ended, Mendelowitz stayed with the Nationals as a consultant and after completing his Ph.D. in 2015, he went to work for the team full time as an analyst. By this time, the Nationals and other major league teams had more data to work with than ever before thanks to StatCast, MLB’s player tracking system.

“Now we know where the ball is at all times, we know how players are positioned and moving on the field, so if there’s a line drive to center field and a player has to make a very athletic play to make the catch, we have all these metrics on that play,” he explained. “We know how hard the ball was hit, and in what direction, we know how far the ball traveled, we know how quickly the center fielder reacted and the route he took to try to make the play. The ultimate goal is to use this kind of information to make decisions that translate to wins on the field.”

“I’m still not sure how it happened”

For Mendelowitz, being part of the Nationals’ day-to-day operations is an experience beyond anything he could have imagined—working at the ballpark, going to games and contributing to the success of the team all year-round. Though he always loved baseball, he never considered the possibility of a job in the major leagues until it was right in front of him.

“The truth is no, I really did not ever consider a career in baseball,” he admitted. “I didn’t think, ‘Oh, I want to work in baseball.’ I just thought I’m going to continue being a baseball fan and I’m going to work in data science R&D somewhere else. I didn’t realize that teams were really hiring in this area. And even if they were, there are only 30 teams and I didn’t even know how many jobs would be available. I’m still not sure how it happened, but I’m glad it did.”

Now, after five years with the Nationals—including the thrill of being part of the team’s World Series win in 2019—he is hard pressed to think of a job that would be a better fit. It may not be a career path he expected, but to this lifelong baseball fan, it feels like a home run.

“I feel really lucky. I remember just the randomness of how this all came together,” he said. “I was lucky to get the internship, lucky to get a full-time offer and the Nationals deciding there’s a role for people like me to work in baseball. It’s really a blessing. I feel very fortunate and grateful, that’s for sure.”