About Me

I am a sixth year graduate student in computer science at UIUC, advised by Dr. Sarita Adve in the RSim Research Group.

My research is broadly focused on using software-driven techniques to make hardware more reliable. Specifically, I have explored approximate computing and software testing methodologies to improve resiliency analysis; I developed a software-based technique for GPU instruction replication; and I am currently exploring the reliability of neural networks for domain-specific resiliency.

Research Interests:

  • Computer Architecture
  • Reliability
  • Software Testing
  • Machine Learning
  • Approximate Computing


  • New: Received the Certificate of Mentorship from the Graduate College at UIUC for mentoring two undergraduate students in research!
  • “Approximate Checkers” is accepted at WAX 2019!
  • Released PyTorchFI, a runtime error injection tool for PyTorch!
    Go ahead and pip install pytorchfi!
  • Received the Lynn Conway Research Award for Best Technical Demonstration at ADA!
  • Received the Mavis Future Faculty Fellowship Award for 2019-2020!
  • Presented our paper titled, “Minotaur: Adapting Software Testing Techniques for Hardware Errors” at ASPLOS 2019!
  • Invited to attend the 7th Heidelberg Laureate Forum, 1 of 200 young researchers invited worldwide!
  • Presented our paper titled, “Optimizing Software-Directed Instruction Replication for GPU Error Detection” at SC 2018!