Written by Miki and the prize recipients.
The math graduation party took place in the afternoon on Monday, May 19. Congratulations to all seniors!
This year’s mathematics prizes were announced at the party by Professor Rick Kenyon, together with River Newman ‘25, last year’s recipient of the Stanley award.
Each prize recipient shared an anecdote from their time at Yale at the party. For this article, they also wrote about their plans, and shared advice for new math majors.
The DeForest prizes for proficiency in pure and applied mathematics were awarded to Andrei Parfeni ‘25 and Vismay Sharan ‘25.
Andrei will be pursuing a PhD in mathematics at NYU next year. This summer he will visit his family in Romania and plans on learning to cook new recipes. In his free time at NYU, Andrei is looking forward to hiking, going on long walks, and playing chess and table tennis.
Regardless of how well-prepared or experienced you think you are, there will be moments where you feel overwhelmed or unable to understand some new concept or topic you’ve been introduced to. Don’t panic; take a step back and breathe. Nobody is born already knowing all of mathematics. As with any other intellectual topic worthy of study, it takes patience and sustained work to get better at math. Don’t be afraid to spend time thinking about or reviewing what you’ve learned, even if others seem to grasp it immediately; take however long you need to ensure it’s straightforward and intuitive in your mind. If you still have lingering doubts about anything, don’t hesitate to contact your peers and professors! Everyone in the math department wants you to succeed, and they will be happy to give you the advice you need.
Vismay will be pursuing a PhD at the Courant Institute at NYU, with a focus on Probability. This summer he looks forward to spending time in Florida where he hopes to work out, read, and learn how to cook and drive.
Try to give all different areas of math a chance! A subject that may not seem very appealing in an introductory class can often develop into something much more coloring. This will also allow you to gain experience in all subfields of mathematics which can help you see connections between these areas and gain a deeper appreciation for mathematics as a whole.
The George Beckwith prize for proficiency in astronomy or mathematics is awarded to Josh Zeitlin ‘25.
Josh will be pursuing a Masters in mathematics at Cambridge University next year before beginning a PhD at UC Berkeley. This summer Josh will be working at Aalto University in Helsinki on a project involving mathematical methods directed for political science..
My number one piece of advice is to not rush. This advice may sound trite and is certainly hard to do given the social pressure at a school like Yale to be successful. However, in order to get the most out of your mathematical education you have to spend a lot of time with your coursework. Specifically, problem sets are the most important aspect of this. Make sure to not just go through the motions but to really spend a lot of time on problem sets as this is the best way to learn and enhance your understanding of the material.
The Anthony D. Stanley memorial prize, given out to a junior for excellence in pure and applied mathematics, is awarded to June Lee ‘26.
June is a double major in Mathematics and Physics. She is excited to study random conformal geometry in her independent project with Professor Catherine Wolfram. She will also be learning about extremal combinatorics at the IAS/Park City Mathematics Institute. In the meantime, she is excited to visit various art galleries and watch a lot of movies. She plans to pursue a PhD in mathematics.
Sometimes, it might be tempting to focus your studies only in a specific field of math. However, there are often deep connections between concepts that appear unrelated, and you might need a tool from a completely different subfield to solve a problem. This is why having a rounded out background is important - try out and explore as many things as possible. You might end up falling in love with something completely unexpected!
The John Alan Lewis Summer Research Fellowship is awarded to a winning proposal by an undergraduate student majoring in mathematics who wishes to pursue their studies over the summer. This year’s fellowship is awarded to Anh-Thai Le ‘26.
Anh-Thai is a junior interested in statistical mechanics and probability. This summer, he looks forward to continuing some stat mech work with Professor Kenyon and exploring more of the New Haven area/East Coast.
Lattice models in statistical mechanics (e.g. dimer, six-vertex, Ising) are interesting not only as mathematical models of phase transitions, but also for the rich interplay between different areas of math, such as representation theory, combinatorics, and probability. Perhaps the models most interesting to mathematicians are “exactly solvable,” meaning one can compute closed-form expressions for relevant physical quantities (in the thermodynamic limit), such as the model’s free energy. The most ubiquitous tool for computing the free energy is the transfer matrix method, which has a storied history — for example, Onsager (a Yale professor!) used it to solve the two-dimensional Ising model without a magnetic field. This project explores the rich connection between the transfer matrix method and a well-known extension, the algebraic Bethe ansatz. While the transfer matrix encodes information about a model, the Bethe ansatz provides an educated guess for constructing the transfer matrix’s eigenvectors. Our starting point is the dimer model on the honeycomb lattice (equivalently tiling the plane with 60-degree rhombi). In this setting, the Bethe ansatz eigenvectors have a beautiful form, namely a Vandermonde determinant related to the Schur polynomials. From these eigenvectors, we are currently examining determinantal measures, where relevant probabilities are expressed as determinants of matrix minors. Along the way, there are other phenomena we hope to explore, such as limit shapes (that appear as one looks at random model configurations on a very large lattice) and emptiness formation probabilities (that allow for computations on more general domains).
It’s quite fortunate the Yale math community is collaborative and has very supportive professors and ULAs/TAs. Just as you should use these opportunities/resources to improve your math and collaboration skills, don’t forget to contribute back to the math community as well, whether it’s within Yale or beyond, such as mentoring younger students who may be interested in math.