Nate Gillman Howdy!! I'm a machine learning engineer at Akkio. We're developing an AutoML platform so that the capabilities of AI can be accessible to everyone. Check us out!!

Before working at Akkio, I was a PhD student at Brown University, where I was fortunate to be advised by Chen Sun and Carsten Eickhoff. I studied machine learning, computer vision, and natural language processing. My projects focused on time series forecasting using generative models, applied to various domains. For one of my projects, I researched 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. After getting my masters degree in mathematics in spring 2022, I took a professional leave of absence to join Akkio's engineering team.

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.

Resume  /  Google Scholar  /  Github  /  arXiv  /  LinkedIn

ngillman@brown.edu


Updates

  • [Aug-2022] I joined Akkio as a machine learning engineer. I'm helping to build out the AutoML engine.
  • [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.