👩🏽💻 About Me
Welcome! I'm Shreya Shankar, a computer scientist (she/they) living in the Bay Area. I am interested in practical applications of machine learning (ML) and solving their annoying data management challenges.
My (in-progress) PhD is in databases at UC Berkeley, and I am fortunate to be advised by Dr. Aditya Parameswaran. Previously, I was the first ML engineer at Viaduct, did research engineering at Google Brain, and software engineering at Facebook.
During my time at Stanford (BS & MS in computer science)—an unnecessarily stressful experience yet a something I look back on very fondly—I helped run a nonprofit called SHE++, an organization that helps to empower underrepresented minorities in technology. I also spent a lot of time as a section leader for CS198 and served as the head TA for CS106B.
I'm working on the following projects:
- A dataflow-based framework to build continually-updating ML pipelines
- Prompt engineering and management tools for large language models
- Mitigating effects of feedback delays on real-time ML performance
- Mining feedback delays to build better ML performance debugging tools
- Interview study on best practices in CI / CD for ML (under revision)
- Interfaces for integrating observability into ML pipelines
If you are interested in working on any of these projects or collaborating, please contact me via email. I am open to undergrads who have taken a databases course and/or a graduate level machine learning course. If you go to UC Berkeley, please mention that in your email. I apologize if I am unable to respond to your email in a timely manner.
To reach me, you can email email@example.com. I am also on Twitter and Github.
My (typically-outdated) CV is available for download here.