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Panel on Paths in Mathematics After Undergrad
October 20, 2021 @ 4:30 pm - 5:45 pm
Panelists: Tatiana Bradley, Michelle Goodwin, Isys Johnson, John Lentfer, and Matthew vonAllmen
We will have a panel discussion with graduates from the Claremont Consortium who have taken different pathways after graduation. After introductions, there will be time for open questions from the audience.
Afterward, breakout rooms will be open for a casual discussion with the panelists and more participants.
Including a breakout room on the “4+1” Master’s Program at CGU, with current and past students.
Panelist Bios:
Tatiana Bradley is a Software Engineer at Google in New York City. She received a bachelor’s degree in Math at Scripps College, and a PhD in Computer Science (specializing in cryptography) at UC Irvine. At Google, she works on protecting user data from insider risk.
Michelle Goodwin is an Associate Vice President at Barclays Investment Bank in San Francisco. She received a bachelor’s degree in Pure Mathematics from Claremont McKenna College in 2016. For Barclays, she sells institutional investors (e.g. pension funds, insurance companies, and hedge funds) securitized products.
Isys Johnson is a graduate of Pomona College where she double majored in Computer Science and Mathematics. Isys is currently pursuing a PhD in Computer Science at the State University of New York at Buffalo. She is interested in structured linear algebra with applications in machine learning and works as a research assistant for Dr. Atri Rudra.
John Lentfer graduated from Harvey Mudd College in 2021, where he majored in mathematics. John is currently a first-year mathematics PhD student at UC Berkeley. He is interested in combinatorics and he is also exploring some related areas as he decides what topic to focus on.
Matthew vonAllmen is a graduate of Pitzer College. He majored in CS-Math through Harvey Mudd College and Mathematical Economics at his home campus. Currently, he’s pursuing a computer science PhD at Northwestern University, where his research focuses on interdisciplinary CS-Econ questions of mechanism design and collective prediction.
