Research
I am currently working on adaptive query processing for hybrid crowd-machine database systems. More details on this project here.
My research interests include integrating human computation into databases systems; scalable databases and cloud computing. My publications, grouped by topic:
Crowdsourcing and Databases
Doren Lan, Katherine Reed, Austin Shin, Beth Trushkowsky. Dynamic Filter: Adaptive Query Processing with the Crowd. In Fifth AAAI Conference on Human Computation, pp.118-127, 2017.
Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar, Venketaram Ramachandran. Crowdsourcing enumeration queries: Estimators and interfaces. IEEE Transactions on Knowledge and Data Engineering, 27(7), pp.1796-1809, 2015.
Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar. Crowdsourced Enumeration Queries. ICDE 2013. Best Paper Award.
Gianluca Demartini, Beth Trushkowsky, Tim Kraska, Michael J. Franklin. CrowdQ: Crowdsourced Query Understanding. CIDR 2013.
SCADS
Beth Trushkowsky, Peter Bodik, Armando Fox, Michael J. Franklin, Michael I. Jordan, and David A. Patterson. The SCADS Director: Scaling a distributed storage system under stringent performance requiremen ts. In 9th USENIX Conference on File and Storage Technologies (FAST '11).
Michael Armbrust, Stephen Tu, Armando Fox, Michael J. Franklin, David A. Patterson, Nick Lanham, Beth Trushkowsky, and Jesse Trutna. 2010. PIQL: a performance insightful query language. In Proceedings of the 2010 international conference on Mana gement of data (SIGMOD '10). (demonstration)
Michael Armbrust, Armando Fox, David A. Patterson, Nick Lanham, Beth Trushkowsky, Jesse Trutna, Haruki Oh: SCADS: Scale-Independent Storage for Social Computing Applications. CIDR 2009.
DisputeFinder
Rob Ennals, Beth Trushkowsky, and John Mark Agosta. 2010. Highlighting disputed claims on the web. In Proceedings of the 19th international conference on World wide web (WWW '10).
CoBib
Extended abstract: Beth Trushkowsky, Kamaria Campbell, and Jeffrey Forbes. An architecture for a collaborative bibliographic database. In Proceedings of the 2007 conference on Diversity in computing (Tapia 2007).