Professor Kevin Ashley received an NSF EAGER (Early Concept Grants for Exploratory Research) award in September 2010.
- EAGER: Modeling Interpretive Argument with Case Analogies and Rules of Ill-Defined Domains. The work will contribute to the fields of AI, argumentation theory, AI and Law, and case-based reasoning, and it aims in the longer term to contribute to intelligent tutoring systems that will prepare students for making effective, supportable and otherwise rational arguments, and to design artificial agents as proxies and advocates for humans engaged in disputes.
Professor Peter Brusilovsky received two NSF EAGER (Early Concept Grants for Exploratory Research) awards in September 2010.
- EAGER: Personlization and Social Networking for Short-Term Communities, Co-PI Assistant Professor Jung Sun Oh, will support a project exploring personalization and social netsworking for short-term communities. Using academic research conferences as a test bed, Brusilovsky will explore new methods to leverage information about user interests (available from multiple external resources) and develop techniques to facilitate use of existing social technologies.
- EAGER: Modeling and Visualization of Latent Communities will look at how to model and visualize latent communities - those groups of people who form communities based on their similar interests. This work will consider how to elicit latent communities from various kinds of data about individuals available in the modern social Web and deliver the results in a manner suitable for interactive exploration through interactive visualization. See more information about Peter Brusilovsky's research on his personal website.
- Google Research Grant to study personalized social systems, Personalized Social Systems for Local Communities. The grant, for $55,000, will support efforts to increase user participation in social systems designed for local communities. The contribution-driven mechanism of modern social systems requires a high level of user activity, which is typically not available in small location-bound communities. In the course of the project, Brusilovsky and his team will explore two innovative ideas for increasing participation. The first idea is to provide access to information "beyond the desktop," by adding a mobile location-based interface to access information. This will increase both the number of active users and the volume of their contributions. The second idea is to provide personalized access to information to increase the chance to gather relevant information. This work will be based on two existing social systems that were developed and maintained by Brusilovsky's lab: the CoMeT system for sharing infromation about research talks at Carnegie Mellon and University of Pittsburgh and Eventur, a social system for recommending cultural events in the Pittsburgh area. The project will incorporate practical testing of both interfaces in the target communities in order to explore the value of these innovations. The Google Research Awards program aims to identify and support world-class, full-time faculty pursuing innovative research in areas relevant to Google's mission.
Professor Gregory Cooper has six projects spanning from two to five years in length. A brief description of each follows:
- National Institutes of Health -- Predicting Patient Outcomes from Clincial and Genome-Wide Data. The objective of this project is to develop, implement, and evaluate new computer-based methods to predict diseases and outcomes in individuals based on the use of both traditional clinical data and data about the individual's genome in the form of SNP-array data. (9/1/2009 - 8/31/2011) Dr. Cooper's role: PI
- Center for Disease Control -- University of Pittsburgh Center for Advanced Study of Informatics in Public Health Informatics. The overall purpose of this application is to create a Center for Advanced Study of Informatics in Public Health (CASIPH) at the University of Pittsburgh to bring together a diverse group of investigators to carry out resarch focusing on improving the nation's ability to detect and characterize cases of disease and outbreaks of disease as quickly as possible. (9/1/2009-8/31/2014) Dr. Cooper's role: PI.
- National Science Foundation -- Discovering Complex Anomalous Patterns. The goals of this project are to develop, implement, and evaluate a general and widely applicable framework for capturing potentially complex statistical patterns in large databases. (9/1/2009-8/31/2012) Dr. Cooper's role: Co-PI
- National Institutes of Health/NIGMS -- Detecting Deviations in Clinical Care in ICU Data Streams. The goal of this project is to use advanced machine-learning methods to detect anomalous clinical decisions making in acutely ill patients. (9/1/2009-6/30/2012) Dr. Cooper's role: Co-Investigator
- National Institutes of Health/NLM -- Using Medical Records Repositories to Improve the Design of Alerting Systems. The main objective of this project is to develop, implement, and evaluate new methods for the off-line evaluation and tuning of clinical alerting systems with the help of electronic health records (EHR) databases. (9/30/2009-9/29/2012) Dr. Coopers Role: Co-Investigator
- National Institutes of Health/NLM -- Decision Making in Biosurveillance. The long-term objective of this research is to advance the use of decision analysis in biosurveillance. The specific aims of the research are to (1) construct decision analyses of representative biosurveillance decision problems using standard decision analytic techniques, and (2) deploy the underlying decision models in a decision-support system for analysts and epidemiologists. (9/30/2008-9/29/2012) Dr. Cooper's role: Co-Investigator.
Professor Milos Hauskrecht received two NIH awards.
- Detecting Deviations in Clinical Care in ICU Data Streams will study the computational methods for detecting deviations in clinical care in intensive care unit (ICU) data with colaborator, Professor Gilles Clermong in the Department of Critical Care.
- Using Medical Records Repositories to Improve the Alert System Design will develop and study a new computational framework for off-line evaluation and optimization of clinical alerting systems based on retrospective electronic health record data.
Professor Daqing He received a grant from the NSF's Division of Information & Intelligent Systems.
- EAGER: Tapping into Public Academic Information on the Social Web: Towards a Novel Academic Recommendation Framework will explore the emerging phenomenon of public academic information resources on the social web. The project aims to develop an assessment and association identification framework for online academic information, to facilitate researchers in accessing, organizing, utilizing, and exchanging all types of academic information.
Professor Diane Litman has received three new research grants in the last two years.
- Dr. Litman is principal investigator on an NSF Award in the Robust Intelligence and the Human-Centered Computing Programs. An Affect-Adaptive Spoken Dialogue System that Responds Based on User Model and Multiple Affective States is a three-year project with co-principal investigator Katherine Forbes-Riley, Research Associate at the Learning Research and Development Center (LRDC), University of Pittsburgh.
- She is also co-principal investigator on a three-year IES award. Improving a Natural-language Tutoring System That Engages Students in Deep Reasoning Dialogues About Physics is a three-year project in collaboration with Sandra Katz (PI, LRDC), Pamela Jordan (LRDC and ISP PhD graduate), and Michael Ford (School of Education), University of Pittsburgh.
- Finally, in conjunction with ISP faculty Kevin Ashley and Christian Schunn, Litman is PI on a two-year award from the Learning Research and Development Center (LRDC) on Improving Learning from Peer Review with NLP and ITS Techniques.
Professor Jan Wiebe receives NSF grant.
- Dr. Wiebe and collaborator Rada Mihalcea of the University of North Texas receive $500,000 from the National Science Foundation to study Word Sense and Multilingual Subjectivity Analysis