I'm a final-year PhD student in Computer Science at UC Berkeley,
advised by Professor Aditya Parameswaran.
My research focuses on developing software solutions for facilitating machine learning and data analytics.
I developed Helix to accelerate
machine learning model development through intelligent materialization and reuse of intermediate results.
Updates
Our paper “Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities” has been accepted at SIGMOD ‘21!
Our vision for the future of dataframe research has been presented at VLDB ‘20 by Devin Petersohn. Paper: Towards Scalable Dataframe Systems. Video.
We presented our work “Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development” virtually at HILDA 2020. Slides.
Our work titled “Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development” has been accepted as a full paper and will be presented virtually at HILDA 2020.