Eric Zelikman

I’m an incoming Stanford CS PhD student (and Symbolic Systems graduate) fascinated by how (and whether) algorithms can learn meaningful representations. Perhaps the most daunting exciting gap between biological and machine learning is the ease with which we learn to create and apply concepts about our world from experience: not only do we need much less experience to construct these concepts, but our understanding is flexible in novel situations, robust to slight changes, and generally disentangled.

Ultimately, I hope machine learning can teach us about non-machine learning and help us overcome the challenges facing humanity.

Also, I love baking bread, cooking, and exploring nature!

Selected Works

  1. ICLR 2021
    Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y Ng, Gunnar Carlsson, Stefano Ermon,
    International Conference on Learning Representations 2021
  2. ICML Workshop
    Eric Zelikman, Christopher Healy, Sharon Zhou, Anand Avati,
    ICML Workshop on Uncertainty & Robustness in Deep Learning 2020
  3. NeurIPS Workshop
    Eric Zelikman*, Sharon Zhou*, Jeremy Irvin*, Cooper Raterink, Hao Sheng, Jack Kelly, Ram Rajagopal, Andrew Y Ng, David Gagne,
    NeurIPS Workshop on Tackling Climate Change with Machine Learning 2020
  4. CVPR Workshop
    Xinlei Pan, Yulong Cao, Xindi Wu, Eric Zelikman, Chaowei Xiao, Yanan Sui, Rudrasis Chakraborty, Ronald S. Fearing,
    Short Paper in CVPR Workshop on Adversarial Machine Learning in Computer Vision 2020
  5. Honors Thesis
    Eric Zelikman (advised by Nick Haber),
    Undergraduate Honors Thesis 2020
  6. Eric Zelikman, Richard Socher,
    arXiv 2018


Stanford University
Doctoral Student
Computer Science
September 2021 -

Stanford University
Bachelor of Science
Symbolic Systems with Honors
September 2016 - June 2020


Deep Learning Engineer Lazard July 2020 – Present
GANs Curriculum Developer DeepLearning.AI June – October 2020
Machine Learning Intern Argo AI June – September 2019
Machine Learning Intern Uncountable June – September 2018
& April – June 2019
Software Engineer Philometrics October 2016 – July 2017


Editor and 2019 Editor-in-Chief Stanford Undergraduate Research Journal 2016 – 2020
Teacher Stanford Splash 2016 - 2020
Section Leader Stanford Code in Place April - May 2020
TreeHacks, HopHacks, Cal Hacks, etc. Hackathons 2016 - 2020
Cofounder - Machine Learning Lead (defunct) January - July 2020