Adhithya Bhaskar

Hi there! I am a PhD candidate in Industrial and Systems Engineering at USC with experience in computational reproducibility, automated research pipelines, and LLM evaluation.

I design evaluation methods and automated pipelines for extracting evidence, testing research artifacts, and producing transparent, inspectable assessments. My work combines empirical study design, scientific software, text and data pipelines, and evaluation of LLM output consistency and reliability.

My current ReproReady work develops a local, offline, deterministic tool for statically checking computational research artifacts. It is designed to help researchers understand the manual work required to reproduce reported computational results, rather than predict whether the code will run.

ReproReady builds on ReproScreener, my earlier work using LLM-assisted evaluation to assess computational reproducibility evidence in machine-learning artifacts at scale.

I am seeking full-time Research Scientist, Data Scientist, ML Evaluation, and Applied AI roles. I expect to defend my dissertation in December 2026.

You can find my resume here (updated September 1, 2026).

Publications

• Reproscreener: Leveraging LLMs for Assessing Computational Reproducibility of Machine Learning Pipelines
  Adhithya Bhaskar, Victoria Stodden
  ACM REP, 2024
• Learning from reproducing computational results: introducing three principles and the Reproduction Package
  Matthew S. Krafczyk, August Shi, Adhithya Bhaskar, et al
  Phil. Trans. R. Soc. A, 2021
• Scientific Tests and Continuous Integration Strategies to Enhance Reproducibility in the Scientific Software Context
  Matthew Krafczyk, August Shi, Adhithya Bhaskar, et al
  ACM P-RECS, 2019
• Enabling the Verification of Computational Results: An Empirical Evaluation of Computational Reproducibility
  Victoria Stodden, Matthew S. Krafczyk, and Adhithya Bhaskar
  ACM P-RECS, 2018

Awards

• Jenny Wang Excellence in Teaching Award. Viterbi School of Engineering, 2023 and 2026.
• Outstanding Teaching Assistant of the Year. Daniel J. Epstein Department of Industrial and Systems Engineering, 2023 and 2026.