Shreya Shankar

Moving Fast with Broken Data

with Labib Fawaz, Karl Gyllstrom and Aditya G. Parameswaran.

Operationalizing Machine Learning: An Interview Study

with Rolando Garcia, Joseph M. Hellerstein and Aditya G. Parameswaran.

Towards Observability for Machine Learning Pipelines

with Aditya G. Parameswaran.
To appear at VLDB 2023.

Bolt-on, Compact, and Rapid Program Slicing for Notebooks

with Stephen Macke, Sarah Chasins, Andrew Head and Aditya G. Parameswaran.
To appear at VLDB 2023.

Rethinking Streaming Machine Learning Evaluation

with Bernease Herman and Aditya G. Parameswaran.
ICLR 2022: Workshop on ML Evaluation Standards.

Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming

with Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy R Bunel, Jacob Steinhardt, Ian Goodfellow, Percy S Liang and Pushmeet Kohli.
NeurIPS 2020.

Adversarial examples that fool both computer vision and time-limited humans

with Gamalelden F. Elsayed, Brian Cheung, Nicolas Papernot, Alexey Kurakin, Ian Goodfellow and Jascha Sohl-Dickstein.
NIPS 2018.

No classification without representation: Assessing geodiversity issues in open data sets for the developing world

with Yoni Halpern, Eric Breck, James Atwood, Jimbo Wilson and D. Sculley.
NIPS 2017: Workshop on Machine Learning for the Developing World.