I am an Applied Scientist at AWS AI working on deep learning and computer vision research. I completed my PhD in the Department of Mathematics at UCLA where I was jointly supervised by Guido Montúfar and Andrea Bertozzi.

During my PhD I was supported by the NSF Graduate Research Fellowship (NSF GRFP) and had the opportunity to conduct research at Snap Research, Samsung ATG, and the AWS AI industry labs.

Before my PhD I was studying (pure) mathematics at UCLA with interest in analysis. I recieved my BS and MA concurrently from UCLA under the Departmental Scholar Program.

Some of my research interests are:

  • Computer vision (including 3D representations)
  • AutoML and data
  • Deep learning theory: Non-convex optimization, Representation learning, Generalization


04/2022 I will be presenting our paper DIVA focused on dataset optimization at ICLR 2022.
04/2022 I joined AWS AI as an Applied Scientist.
12/2021 I successfully defended my PhD Thesis! Big Thank you to my advisors and PhD committee.
07/2021 I'm reviewing for NeurIPS 2021
06/2021 I'll be working at Snap Inc. this summer as a research intern for Snap Research, working in the Creative Vision team.
01/2021 I'll be (remotely) working at Amazon Science this winter as a research intern for AWS, working on AutoML and few shot learning in computer vision.
11/2020 I recieved Research internship offers from Amazon, Microsoft, and Snap!
10/2020 I am a teaching assistant for Math 269A (Graduate course on Advanced Numerical Methods)
09/2020 I'm reviewing for AISTATS 2021
09/2020 I have been selected to serve on the UCLA technology development group oversight committee
08/2020 I am participating in the NSF NRT ICORPS workshop with Yushan Han
07/2020 I'm reviewing for NeurIPS 2020
06/2020 I am a teaching assitant for the first time, teaching Math 33A (Linear Algebra)
06/2020 Our paper Optimization Theory for ReLU Neural Networks Trained with Normalization Layers on theory of normalization methods in deep learning was published at ICML 2020
03/2020 I'm reviewing for ICML 2020
03/2020 Our paper Theory for undercompressive shocks in tears of wine on thin film shocks in the tears of wine phenomena was published a PHYSICAL REVIEW FLUIDS
01/2020 I am working at Samsung's Strategy and Innovation Center as a computer vision research intern at the Advanced Technology Group (ATG) this winter. I will be working on 3D computer vision for self driving preception.
10/2019 I'm reviewing for ICLR 2020
10/2019 Our paper Wasserstein Diffusion Tikhonov Regularization using optimal transport for adversarial robustness was accepted at NeurIPS 2019 workshop on optimal transport and machine learning.
06/2019 Our paper Wasserstein of Wasserstein Loss for Learning Generative Models was published at ICML 2019
04/2019 I will present my work as an invited speaker at the Deep Learning Theory meeting in Leipzig.
04/2018 I was awarded the NSF graduate research Fellowship (NSF GRFP) in Mathematics!
09/2017 I passed my last area qualifying exam, the area qualifying exam in Analysis

Here you can find about my research


Office Currently WFH :):

7630 Math Sciences –>