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.
I am currently working on a no-code automated machine learning system with a serverless backend
that enables seamless collaboration between the human and the machine.
Updates
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.
I was invited to present our work on Helix (VLDB ‘19) at Google. Lots of interest in making maching learning development more agile and efficient!
Our work on enabling accelerated machine learning inference in RDBMS was presented at CIDR 2020. Paper