Research Teaching Publications Advisees & Collaborators DB Group MKSE Program
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Zachary G. Ives

Associate Professor and Markowitz Faculty Fellow
Computer & Information Science Department
University of Pennsylvania

Associated Faculty, Penn Center for Bioinformatics
Distinguished Research Fellow, Annenberg Center for Public Policy
Undergraduate Chair, Singh Program on Networked & Social Systems Engineering

On sabbatical leave at Google, Inc., until Sept 2013

 

Contact Information

576 Levine Hall North
Computer and Information Science Department
University of Pennsylvania
3330 Walnut Street
Philadelphia, PA 19104-6389
zives@cis.upenn.edu
(215) 746-2789    Fax: (215) 898-0587

Biographical Sketch

Zachary Ives is an Associate Professor and the Markowitz Faculty Fellow at the University of Pennsylvania. His research interests include data integration and sharing, "big data", sensor networks, and data provenance and authoritativeness. He is a recipient of the NSF CAREER award, and an alumnus of the DARPA Computer Science Study Panel and Information Science and Technology advisory panel.  He has also been awarded the Christian R. and Mary F. Lindback Foundation Award for Distinguished Teaching. He serves as the undergraduate curriculum chair for Penn's Singh Program in Networked and Social Systems Engineering. He is a co-author of the textbook Principles of Data Integration.

Research

My research interests lie in the areas of databases and distributed systems, especially as they relate to the Web, Web-scale information sharing, and distributed networks of devices (e.g., sensors, actuators). I am a member of the database, wireless/mobile systems, systems, and market and social systems engineering research groups at Penn. My research projects relate to making it easier to exchange, locate, and analyze networked information.

ORCHESTRA focuses on the problem of collaborative data sharing:  exchanging data and updates among loose confederations of databases, when the different database owners have different schemas and different ideas of what is the "right" content. We have developed techniques to map data and updates among different sites, maintain data provenance, and use the data provenance as the basis of assessing trust and ultimately to resolve conflicts.  We specifically target biological data sharing applications.  See here for an overview paper. Funded by NSF CAREER #IIS-0477972.
The Q query system addresses the challenges of querying in a system like Orchestra, when one does not know apriori where to find the most relevant data.  Q takes as input a keyword query, which it matches against schema elements to produce potential data integration queries.  The system returns answers from the most promising queries and takes user feedback on the results.  This feedback is used to learn which sources are most relevant to the information need that motivated the query.  Funded by NSF CAREER #IIS-0477972 and SEIII #IIS-0513778.
Aspen addresses the problem of programming and integrating large-scale and complex sensor networks. The system focuses on a setting in which large numbers of distributed sensors, with varying capabilities, must be coordinated in order to manage and reason about collections of physical entities and phenomena. My focus is on sensor data integration, i.e., integration of data streams from multiple sensor (and other) sources. A target application is data center monitoring for energy, temperature, load, and other factors. Different aspects of the research are funded by NSF III #IIS-0713267, NOSS #CNS-0721541, and a University Research Initiative grant from Lockheed Martin.
The new Concerto system builds upon the ideas of Q and ORCHESTRA to build a network of interlinked data sources and "live ranked views." More details will be forthcoming shortly. Funded in part by IIS-1050448.
The IEEG Web Portal, in collaboration with Prof. Brian Litt of Bioengineering and Neurology, and Prof. Greg Worrell at Mayo Clinic, seeks to enable cloud-hosted science for epileptic seizure prediction (and beyond). IEEG also serves as a testbed for our data integration research. Funded by an NIH U24 grant.

Acknowledgments: I have also received grants from DARPA CSSG (#HRO011-06-1-0016 and HRO1107-1-0029), Penn ISTAR, the State of Pennsylvania, Amazon, Google, and Lockheed Martin, and software donations from MarkLogic, Electric Software, and IBM Corp.

Teaching

I am the Undergraduate Curriculum Chair for Penn's Singh Program on Networked and Social Systems Engineering (currently on sabbatical leave; Ali Jadbabaie has graciously agreed to step in). This Internet-centered degree program looks at how people and systems interact over networks. It combines computer science (algorithms, distributed systems) with sociology, incentives (game theory), and dynamic systems. The overall program is directed by Michael Kearns and Ali Jadbabaie. New MKSE courses I co-developed include MKSE 212 "Scalable and Cloud Computing" and MKSE 150 "Market and Social Systems on the Internet".

Selected recent courses and seminars:

Detailed information is here.

Textbooks and Monographs

 Principles of Data Integration, with AnHai Doan and Alon Halevy. This textbook gives a comprehensive academic treatment of the wide range of topics related to research in data integration: mappings and data transformations, query rewriting, adaptive query processing, XML and streaming data, probabilistic mappings, keyword search, data provenance, and much more. We also describe research challenges, real systems, and implementation techniques. Lecture slides are available from Elsevier. Available from Amazon in hardcopy or Kindle form; from Google Play store in e-book form; from Barnes & Noble in hardcopy or Nook form.
Adaptive Query Processing, with Amol Deshpande and Vijayshankar Raman. Foundations and Trends in Databases, Vol. 1 No. 1, 2007. Hardcopy available at a discount from Now Publishers; see here.

Selected Publications

A complete list is here.

Current Postdoc, PhD, and MS Research Advisees

Alumni — Students and Postdocs

Frequent Collaborators

Tips on Interviewing

Finishing your PhD and going on the job market? I have previously compiled a list of reverences on interviewing, which you can find here.