Nikitha Rao

Nikitha Rao

PhD Student at Carnegie Mellon University

About me

I am a PhD student at the Software and Societal Systems Department (formerly known as the Institute for Software Research), School of Computer Science, Carnegie Mellon University where I am adviced by Prof. Vincent Hellendoorn and Prof. Claire Le Goues. My research interests include Artificial Intelligence for Code, Large Language Models, Generative AI.

Previously, I spent two years as a Research Fellow at Microsoft Research Lab - India where I was fortunate to work with Chetan Bansal on using Machine Learning techniques to aid the Software Developement process. I have also had the opportunity to collaborate with Dr. Sreangsu Acharyya, Dr. Subho Mukherjee, Dr. Nachi Nagappan and Dr. Tom Zimmermann on several projects.

Prior to the fellowship, I attended PES University where I obtained a Bachelor’s in Technology (B.Tech) in Computer Science and Engineering with a specialization in Data Science in 2019. I am grateful to have had the opportunity to work with Dr. Gowri Srinivasa on my Bachelor’s thesis.

Meet my puppy, Flynn!! Follow Flynn’s adventures on Instagram!

UPDATE: I am on the job market looking for research based industry roles starting mid 2025! Please reach out if you think I’d be a good fit for your team. Here is my CV.

News

  • [Oct 2024] Invited to attend the Dagstuhl Seminar on Automated Programming and Program Repair as a Young Researcher!
  • [May 2024] Will be interning with the RiSE group at Microsoft Research for the summer where I will be working with Sarah Fakhoury and Nikhil Swamy.
  • [April 2024] Gave a talk titled “User Intent and Needs for Code Search” at a Dagstuhl Seminar on Code Search.
  • [December 2023] Gave a talk titled “Beyond Syntax: Navigating Challenges in AI-Generated Code” at Microsoft Research.
  • [December 2023] Paper titled “AI for Low-Code for AI” accepted at IUI 2024. (Preprint)
  • [November 2023] Gave a talk on “CAT-LM: Training Language Models on Aligned Code And Tests” at JetBrains Research. (Recording)
  • [September 2023] Paper titled “CAT-LM: Training Language Models on Aligned Code And Tests” accepted at ASE 2023. (Preprint)