I am a fourth year Ph.D. student working with Prof. Michael Franklin on putting the 'P’ in AMP: that is, taking a systems-oriented approach to using human computation to solve problems in big data. Previously, I worked at the Intelligent Health Laboratory in the Children's Hospital Informatics Program at Boston Children's Hospital designing storage systems, dataflows, and applications for managing patient information, particularly Indivo, an open-source personally controlled health record system. I completed my undergraduate education in the School of Engineering and Applied Sciences at Harvard University in 2010.
I am supported by the National Science Foundation Graduate Research Fellowship Program from 2012–2015.
Ph.D., Computer Science, University of California, Berkeley, Fall 2012–Present
A.B. Cum Laude, Computer Science, Harvard University, Spring 2010
Daniel Haas, Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Eugene Wu. Wisteria: Nurturing Scalable Data Cleaning Infrastructure (Demo). VLDB 2015, Kohala Coast, Hawaii.
Daniel Haas, Jason Ansel, Lydia Gu, Adam Marcus. Argonaut: Macrotask Crowdsourcing for Complex Data Processing. VLDB 2015, Kohala Coast, Hawaii.
Evan Sparks, Ameet Talwalkar, Daniel Haas, Michael J. Franklin, Michael I. Jordan, Tim Kraska. Automating Model Search for Large Scale Machine Learning. ACM SOCC 2015, Kohala Coast, Hawaii.
Shiry Ginosar, Daniel Haas, Timothy Brown, Jitendra Malik. Detecting People in Cubist Art. Visart Workshop on Computer Vision for Art Analysis, ECCV 2014, Zurich, Switzerland.
Daniel Haas, Matthew Greenstein, Kainar Kamalov, Adam Marcus, Marek Olszewski, Marc Piette. Reducing Error in Context-Sensitive Crowdsourced Tasks. AAAI HCOMP 2013, Palm Springs, California. (Microtalk Video).
TaskGrader: Predictive Modeling of Human Task Error. Locu Inc., Cambridge, Massachusetts. July 2013.
CrowdQ: A Search Engine with Crowdsourced Query Understanding. AMPLab Winter Retreat, Squaw Valley, California. January 2013.
Indivo X: The Open-Source Personally Controlled Health Record Platform. O'Reilly Open Source Convention (OSCON), Portland, Oregon. July 2011.