Nate Gillman Howdy!! I'm a PhD student at Brown University, where I'm fortunate to be advised by Chen Sun and Carsten Eickhoff. I'm supported by Brown's Department of Mathematics and Department of Computer Science. I study machine learning, computer vision, and natural language processing. Current projects of mine focus on time series forecasting using generative models, applied to various domains. For example, I'm currently researching pedestrian trajectory forecasting, in collaboration with the Honda Research Institute. In the past I also did work in cryptography and pure mathematics, including number theory, algebraic geometry, and geometric measure theory.

I completed my undergraduate degree at Wesleyan University. During my time in college I spent one semester at the Math in Moscow program and another at the Budapest Semesters in Mathematics program. My undergraduate math research advisor was Ken Ono, I spent two summers doing research with him at Emory University's Research Experience for Undergraduates.

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  • [Jun-2022] In summer 2022, I'm doing an machine learning internship at American Express in New York. I'm in the Global Decision Science business unit, and my project involves working to improve chatbots for consumer services.
  • [May-2022] My collaborator William Rudman presented our IsoScore paper at ACL 2022.
  • [Aug-2021] Our arXiv preprint shows that previous metrics have been used incorrectly to analyze word embedding spaces. We provide a mathematically sound method, which we call IsoScore. We give rigorous proofs and we share an efficient Python implementation.