Combining Visualization and Statistical Analysis to Improve Operator Confidence and Efficiency for Failure Detection and Localization. - Peter Bodík; Greg Friedman; Lukas Biewald; Helen Levine; George Candea; Kayur Patel; Gilman Tolle; Jonathan Hui; Armando Fox; Michael I. Jordan; David A. Patterson 001 (ICAC, 2005)

Active Sensing for High-Speed Offroad Driving. - Kayur Patel; Walter Macklem; Sebastian Thrun; Michael Montemerlo (ICRA, 2005)

Personalizing routes. - Kayur Patel; Mike Y. Chen; Ian E. Smith; James A. Landay (UIST, 2006)

Examining Difficulties Software Developers Encounter in the Adoption of Statistical Machine Learning. - Kayur Patel; James Fogarty; James A. Landay; Beverly L. Harrison (AAAI, 2008)

Intelligence in Wikipedia. - Daniel S. Weld; Fei Wu 003; Eytan Adar; Saleema Amershi; James Fogarty; Raphael Hoffmann; Kayur Patel; Michael Skinner (AAAI, 2008)

Investigating statistical machine learning as a tool for software development. - Kayur Patel; James Fogarty; James A. Landay; Beverly L. Harrison (CHI, 2008)

VoiceLabel: using speech to label mobile sensor data. - Susumu Harada; Jonathan Lester; Kayur Patel; T. Scott Saponas; James Fogarty; James A. Landay; Jacob O. Wobbrock (ICMI, 2008)

Detecting digital chameleons. - Jeremy N. Bailenson; Nick Yee; Kayur Patel; Andrew C. Beall (Comput. Hum. Behav., 2008)

Amplifying community content creation with mixed initiative information extraction. - Raphael Hoffmann; Saleema Amershi; Kayur Patel; Fei Wu 003; James Fogarty; Daniel S. Weld (CHI, 2009)

Lowering the barrier to applying machine learning. - Kayur Patel (CHI Extended Abstracts, 2010)

Gestalt: integrated support for implementation and analysis in machine learning. - Kayur Patel; Naomi Bancroft; Steven Mark Drucker; James Fogarty; Amy J. Ko; James A. Landay (UIST, 2010)

Using Multiple Models to Understand Data. - Kayur Patel; Steven Mark Drucker; James Fogarty; Ashish Kapoor; Desney S. Tan (IJCAI, 2011)

Lowering the Barrier to Applying Machine Learning. - Kayur Patel (2012)

Corporate learning at scale: lessons from a large online course at google. - Arthur Asuncion; Jac de Haan; Mehryar Mohri; Kayur Patel; Afshin Rostamizadeh; Umar Syed; Lauren Wong (L@S, 2014)

Scalable and Interpretable Data Representation for High-Dimensional, Complex Data. - Been Kim; Kayur Patel; Afshin Rostamizadeh; Julie A. Shah (AAAI, 2015)

App Usage Predicts Cognitive Ability in Older Adults. - Mitchell L. Gordon; Leon A. Gatys; Carlos Guestrin; Jeffrey P. Bigham; Andrew Trister; Kayur Patel (CHI, 2019)

Understanding and Visualizing Data Iteration in Machine Learning. - Fred Hohman; Kanit Wongsuphasawat; Mary Beth Kery; Kayur Patel (CHI, 2020)

The Future of Notebook Programming Is Fluid. - Mary Beth Kery; Donghao Ren; Kanit Wongsuphasawat; Fred Hohman; Kayur Patel (CHI Extended Abstracts, 2020)

Tempura: Query Analysis with Structural Templates. - Tongshuang Wu; Kanit Wongsuphasawat; Donghao Ren; Kayur Patel; Chris DuBois (CHI, 2020)

mage: Fluid Moves Between Code and Graphical Work in Computational Notebooks. - Mary Beth Kery; Donghao Ren; Fred Hohman; Dominik Moritz; Kanit Wongsuphasawat; Kayur Patel (UIST, 2020)

The Disagreement Deconvolution: Bringing Machine Learning Performance Metrics In Line With Reality. - Mitchell L. Gordon; Kaitlyn Zhou; Kayur Patel; Tatsunori Hashimoto; Michael S. Bernstein (CHI, 2021)

Jury Learning: Integrating Dissenting Voices into Machine Learning Models. - Mitchell L. Gordon; Michelle S. Lam; Joon Sung Park; Kayur Patel; Jeffrey T. Hancock; Tatsunori Hashimoto; Michael S. Bernstein (CHI, 2022)

Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labels. - Jochen Görtler; Fred Hohman; Dominik Moritz; Kanit Wongsuphasawat; Donghao Ren; Rahul Nair; Marc Kirchner; Kayur Patel (CHI, 2022)