Rushil Anirudh

D93CCDC5-529F-4134-A5E8-909F0A40649D


Hi! I am a Computer Scientist with the Data Analysis Group at the Lawrence Livermore National Laboratory, a Federally Funded Research Institute. My research interests broadly include computer vision, machine learning, and high dimensional data analysis. I enjoy collaborating with scientists and researchers across several disciplines of science, and engineering. I also serve as a reviewer for several top machine learning and computer vision publications (NeurIPS, CVPR, ICCV, ICML, AAAI. etc).

My resume (pdf, updated Jan 2020). Contact:undefined

Updates

  • (July 2020) Paper led by Vivek on using GAN priors for unsupervised audio source separation has been accepted to Interspeech 2020! We show that GAN priors easily beat the SOTA among unsupervised methods. [preprint] [code]
  • (July 2020) Paper led by Shusen, on function-preserving linear projections (FPP) for high dimensional scientific domains has been accepted for publication in the journal Machine Learning: Science and Technology! FPP enables linear dimensionality reduction of full dimensional domains to recover functions defined on them. [paper] [code]
  • (June 2020) New preprint on using generative priors based on patches for compressive image recovery — https://arxiv.org/abs/2006.10873 (code/models will be up soon)
  • (June 2020) LLNL has issued a news release about our PNAS paper — link to article.
  • (March 2020) Our paper that proposes a new class of neural network surrogates for inertial confinement fusion (ICF) will appear in the Proc. of the National Academy of Sciences (PNAS)! [arXiv preprint] [published version][code]
  • (Feb 2020) MimicGAN will appear in IJCV’s special issue on GANs! [published version] [arXiv]
  • (Feb 2020) Chairing a special session on Generative modeling for images & videos at Asilomar 2020.