Paulo Cesar G. Costa

Paulo Cesar G. Costa

Research Interests

The major area of my research is on the use of Bayesian probabilistic reasoning as a means to achieve better information technology systems, with a special focus on decision support and multi-source data fusion. As a result, I am interested on the diverse areas of knowledge that contribute to this broad challenge (e.g. Data Mining, Utility theory, Markov processes, Game theory, etc), while also flirting with the different domains in which I believe Bayesian reasoning can make a difference (e.g. BioGenetics, C3I systems, Web applications, etc). At present time, I am working on:

Academic Service

Major Projects in which I have some degree of participation

PR-OWL

One of the major limitations within the development efforts of the Semantic Web is the lack of a comprehensive, principled formalism for representing and reasoning under uncertainty. That is, current SW research is focused on classical logic and some of its variants, failing to provide a means to deal with the many forms in which knowledge cannot be discharged or ignored (e.g. incomplete, ambiguous, or dissonant evidence).
PR-OWL (Probabilistic OWL) is one of the approaches aimed to solve the above limitation using Bayesian methods for representing and reasoning under uncertain knowledge. The framework of PR-OWL is Multi-Entity Bayesian Networks (MEBN), a First-Order Bayesian Logic that provides the mathematical basis for merging the expressiveness of Classical First-Order Logic with the power and flexibility of Bayesian Probability.
Information on both PR-OWL and MEBN can be found on the PR-OWL website.

UnBBayes-MEBN

UnBBayes is a probabilistic network framework written in Java. It's composed by a inference engine, a GUI editor, an API, and a learning environment. The algorithms used are based on strong junction tree method and measure and search (K2 & B).
Currently I am working with the UnBBayes team at the University of Brasilia in the development of a GUI and a reasoner for opening, creating, saving, and reasoning with probabilistic ontologies in PR-OWL format. Files saved in UnBBayes-MEBN are backward compatible with "legacy" (non-probabilistic) ontologies so it can be opened in ontology editors such as Protègè or Swoop.

ETURWG

I am the Principal Investigator of a project funded by the Army Research Office (ARO), which is focused on the mathematical foundations of uncertainty reasoning. In this project, im responsible for the coordination of a working group addressing the growing issue of data deluge and the need for handling information fusion in complex networks (the ETURWG). Our research involves (A) establishing features required of any quantitative uncertainty representation for exchanging soft and hard information in a net-centric environment; (B) developing a set of use cases involving information exchange and fusion requiring sophisticated reasoning and inference under uncertainty; (C) defining evaluation criteria supporting an unbiased comparison among different approaches applied to the use cases; and (D) examining in detail how two popular formalisms, Bayesian and Dempster-Shafer, address the requirements of high-level information fusion in complex networks. The goal is to establish a commonly agreed understanding of the fundamental aspects of uncertainty representation and reasoning that a theory of hard and soft high-level fusion must encompass. Successful completion involves an unbiased, in-depth analysis of the abovementioned enabling technologies, and a formalization of the fundamental principles associated with HLIF.

PROGNOS

PROGNOS stands for PRobabilistic OntoloGies for Naval Operations Systems. I've been working as a systems architect, responsible for overall system design and implementation. The project is supported by the Office of Naval Research (ONR) via its thrust area: Automated Information Integration (sub-area: Predictive Situation Assessment to Provide Impact Assessment). The project is largely based on my work in probabilistic ontologies. In this project, the GMU team is developing mathematically rigorous and computationally efficient algorithms, techniques, and tools to characterize and distinguish situational conditions for predictive analysis and impact assessment under various behaviors and environments.

URSW

The focus of the Uncertainty Reasoning for the Semantic Web workshop (URSW) is to address the challenge of representing and reasoning with incomplete, uncertain information in the context of Semantic Web development. The workshop is held at the International Semantic Web Conference (ISWC).
ISWC is a major international forum for presenting visionary research on all aspects of th Semantic Web. The Uncertainty Reasoning Workshop is an exciting opportunity fo collaboration and cross-fertilization between the uncertainty reasoning community and the Semantic Web community.
The first workshop (URSW 2005) was held on the fourth ISWC, in Galway, Ireland. The second workshop (URSW 2006) was held at the fifth ISWC, in Athens, GA, USA. The third workshop (URSW2007) will be held at the sixth ISWC, in Busan, Korea.

URW3-XG Incubator Group

I have worked as an invited expert in the W3C's Uncertainty Reasoning for the World Wide Web (URW3) Incubator Group, which is part of the Incubator Activity. The group's mission was to better define the challenge of reasoning with and representing uncertain information available through the World Wide Web and related WWW technologies. More information can be found in the URW3-XG Charter, and the group conclusions can be found on its final report.

Contact Me | ©2005-2011 Paulo C. G. Costa | Last Updated on November 22, 2011.

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