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. (more details)
My resume (pdf, updated Jan 2019).
- (Aug 2019) Recent work led by Bogdan Kustowski has been featured on Nuit Blanche. It studies how we can leverage transfer learning to bridge the gap between simulation and experiments.
- (Aug 2019) Work led by Sam Jacobs on extremely scalable deep generative models in scientific machine learning has been accepted to IEEE Cluster 2019.
- (Aug 2019) Work led by Shusen Liu on techniques to visualize extremely large datasets has been accepted to IEEE VIS 2019. (arXiv preprint)
- (Aug 2019) Presented ideas and results from our ongoing work on building better ML-based surrogate models at the Inaugural Monterey Data Conference.
- (June 2019) New arXiv preprint: SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation
- (Feb 2019) 4 Papers accepted to ICASSP 2019 —
- Unsupervised Feature Selection using Graph Signal Analysis,
- Autism Spectrum Disorder Classification with Graph CNNs (SOTA on ABIDE dataset)
- Domain Adaptation with Multiple Subspaces (SOTA on Amazon/Caltech datasets).
- Understanding Deep Networks with Input Uncertainties.