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Julia Stoyanovich, PhD Receives NSF and BSF Grants to Improve Preference Data Analysis

August 18, 2015

Drexel University College of Computing & Informatics (CCI) Assistant Professor Julia Stoyanovich, PhD is the recipient of 2 two-year grants from the National Science Foundation (NSF) and a two-year grant from the US-Israel Binational Science Foundation (BSF) in support of her research on preference data management and analysis.

From the project website: “Preferences are orders among a collection of items attributed to a population of judges. Preference data comes in a variety of forms, such as ranked lists and pairwise comparisons, and is ubiquitous in a plethora of applications across different domains. Over the past decade, there has been a sharp increase in the volume of preference data, in the diversity of applications that use it, and in the richness of preference data analysis methods. Examples of applications include rank aggregation in genomic data analysis, management of votes in elections and recommendation systems in e-commerce.”

The first aspect of the work, funded by a grant of $174,888 from the NSF Division of Information and Intelligent Systems, involves enriching the relational database model with extensions that are specialized for handling preference data.

The second aspect of the work, in collaboration with Associate Professor Benny Kimelfeld, PhD of the Technion - Israel Institute of Technology, will focus on developing novel analytics that are geared towards incomplete preferences. The group received two grants to support this work: a BSF grant of $150,000 (with Drexel’s share at $75,000) and a supplemental grant from NSF’s Division of Computing and Communication Foundations ($50,000).

Stoyanovich's research is in data and knowledge management. She focuses on developing novel information discovery approaches, with the goal of helping the user identify relevant information, and ultimately transform that information into knowledge.  

Stoyanovich holds doctorate and master of science degrees in computer science from Columbia University, and bachelor of science degrees (magna cum laude) in computer science and in mathematics and statistics from the University of Massachusetts Amherst.

For more information about this research, please visit the project website at