Andrew R. Sedler

Applied ML Science and Engineering


I’m a versatile, organized, and collaborative ML scientist and engineer, actively seeking new opportunities in wearables, health, biotech, or a similar domain. I’m eager to join an experienced and like-minded team.

In recent projects, I’ve led model design and development efforts and engineered scalable training and experiment tracking pipelines for both time series modeling and computer vision.

My dissertation research at Georgia Tech developed models and training techniques for biological neural activity, with applications in brain-computer interfaces and computational neuroscience.

I studied biomedical and electrical engineering at Clemson University after attending the SC Governor’s School for Science and Math in Hartsville, SC. In my free time I enjoy cooking, strength training, travel, and spending time outdoors.


May 5, 2023 I graduated from Georgia Tech’s machine learning PhD program!
Apr 12, 2023 I successfully defended my PhD! Check out the recorded talk on YouTube.
Dec 1, 2022 Our highly collaborative work on AutoLFADS has been published in Nature Methods!

selected publications

  1. lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systems
    Andrew R Sedler, and Chethan Pandarinath
    arXiv 2023
  2. Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time
    Feng Zhu*Andrew R Sedler*, Harrison A Grier, and 5 more authors
    Advances in Neural Information Processing Systems 2021
  3. A large-scale neural network training framework for generalized estimation of single-trial population dynamics
    Mohammad Reza Keshtkaran*Andrew R Sedler*, Raeed H Chowdhury, and 7 more authors
    Nature Methods 2022