I grew up in the Soviet Union, where statistics was treated with suspicion and computing power was limited, but I was curious. My first statistics professor was a woman. All other professors at the Moscow State math department were men. She encouraged me and believed I could understand core statistical concepts. Because of her mentorship, I began to appreciate the rigor and definitions that define probability and statistics. That is to say, nothing is random in this world, but it’s a great tool for modeling.
I began my studies at Moscow State University and later transferred to Central Connecticut State University. This was an unexpected path for me, but I accepted it. At Central Connecticut, actuarial science was the suggested path, and I pursued it seriously. I bragged I would place first on the initial exam, and I did. I passed five actuarial exams shortly after and worked in pension benefits consulting in Chicago. The work involved extensive coding and modeling, but it lacked the rigor I desired. I realized I needed a more foundational approach, which led me back to graduate school at The University of Chicago. My adviser, Steven Lalley, was my greatest mentor. He reinforced the importance of rigor in whatever I wanted to pursue next. He made me understand probability theory at the most fundamental level.
I then took a tenure-track faculty position at Columbia. My chair advised me to not have children before tenure—while I was already pregnant. That advice made clear to me what I think many women in academia already know: Tenure is rarely compatible with raising children. So, I focused on teaching and raising my two children, the work I could do best.
I teach with passion and focus on why—why methods are used, why concepts were developed, and why they make sense. I love starting with “this is how we began thinking about it” and “this is why it makes sense historically.” This approach often explains why we think of concepts in a certain way—concepts that are quite contemporary.
My father told me when I was five, “The one who thinks clearly can explain clearly.” I still use that principle to guide my teaching. Students frequently report that my courses changed their learning trajectory and deepened their understanding of statistics. I get gratitude letters from my students, and that warms my heart every semester.
Currently, I teach the second-largest graduate class at Columbia University, after Hillary Clinton. The course began with 35 students and now enrolls more than 250, with a waiting list. I strive to make the classroom rigorous and engaging. I make it available in hybrid mode, so my students can review the lectures later.
I never received tenure, but my focus on teaching has allowed me to create a classroom where statistics is explained clearly and rigorously. For me, that is my greatest professional achievement.
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