k-Regret Queries with Nonlinear Utilities. - Taylor Kessler Faulkner; Will Brackenbury; Ashwin Lall (Proc. VLDB Endow., 2015)

Draining the Data Swamp: A Similarity-based Approach. - Will Brackenbury; Rui Liu 002; Mainack Mondal; Aaron J. Elmore; Blase Ur; Kyle Chard; Michael J. Franklin (HILDA@SIGMOD, 2018)

CYADB: A Database that Covers Your Ask. - Zechao Shang; Will Brackenbury; Aaron J. Elmore; Michael J. Franklin (Proc. VLDB Endow., 2018)

How Users Interpret Bugs in Trigger-Action Programming. - Will Brackenbury; Abhimanyu Deora; Jillian Ritchey; Jason Vallee; Weijia He; Guan Wang; Michael L. Littman; Blase Ur (CHI, 2019)

Files of a Feather Flock Together? Measuring and Modeling How Users Perceive File Similarity in Cloud Storage. - Will Brackenbury; Galen Harrison; Kyle Chard; Aaron J. Elmore; Blase Ur (SIGIR, 2021)

KondoCloud: Improving Information Management in Cloud Storage via Recommendations Based on File Similarity. - Will Brackenbury; Andrew M. McNutt; Kyle Chard; Aaron J. Elmore; Blase Ur (UIST, 2021)

Explaining Why: How Instructions and User Interfaces Impact Annotator Rationales When Labeling Text Data. - Jamar L. Sullivan Jr.; William Brackenbury; Andrew McNut; Kevin Bryson 002; Kwam Byll; Yuxin Chen 001; Michael L. Littman; Chenhao Tan; Blase Ur (NAACL-HLT, 2022)

Summarizing Sets of Related ML-Driven Recommendations for Improving File Management in Cloud Storage. - Will Brackenbury; Kyle Chard; Aaron J. Elmore; Blase Ur (UIST, 2022)