Open Early Stage Researcher/PhD Position at Universidade de Santiago de Compostela (USC), Spain, for the NL4XAI project
Reference number: NL4XAI- ESR2
PhD research topic: From grey-box models to explainable models
Objectives: To define, design, develop and implement an agnostic-based approach for providing Natural Language explanations of Bayesian Networks reasoning using a linguistic imprecise knowledge representation and reasoning method. Taking as a starting point the interpretation of Bayesian variables, values and probability functions as imprecise quantified statements, the Bayesian reasoning process will be modelled as a quantified syllogism, which can be solved as a mathematical programming problem.
The target is to propose, test and validate models for explaining in Natural Language different reasoning schemes, such as predictive, diagnostic or inter-causal, with an efficient implementation for addressing scalability problems which may occur in large Bayesian Networks. The explanation models will be based both in the agnostic-based approach herein considered as well as in the results of ESR3.
The theoretical contributions of this research will be validated in:
- academic use cases provided by the state of the art graphic tools for Bayesian Reasoning; and
- a real use case (“Experiences, offering, demand and classification in semantic-search processes applied to business processes”) defined in one of the inter-sectoral secondments (Indra).
More information and applications here
Deadline for applications is August 15, 2021, at 23h59 CEST (UCT + 02:00)