Key research themes
1. How can pattern matching algorithms efficiently detect and correct mismatches in strings, including handling wild cards and thresholds on mismatch counts?
This research area investigates algorithmic solutions to the string pattern matching problem with mismatches, focusing on efficient detection of approximate matches allowing a certain number of mismatched characters. The challenges involve minimizing computational complexity despite the combinatorial explosion in possible mismatches, extending approaches to handle wild cards (characters matching any symbol), and providing both exact and approximate matching capabilities. These methods underpin applications in text retrieval, computational biology for DNA/protein sequence analysis, and error-resilient data processing.
2. What are the computational frameworks and mathematical foundations for detecting and quantifying inconsistencies and mismatches in pairwise comparisons and model designs?
This theme focuses on theoretical and practical frameworks for formally quantifying inconsistency and mismatch in matrices representing pairwise comparisons, as well as in software models. The motivation is to detect violations of consistency constraints that can propagate errors in decision-making, software engineering, and data integration. The area explores algebraic structures (such as abelian groups), inconsistency indicators, and algorithmic frameworks that provide flexible, extensible, and precise mismatch detection applicable to both abstract mathematical objects and practical software models.
3. How do neurocognitive and behavioral studies elucidate the mechanisms and effects of mismatch detection in auditory and language processing?
This theme explores empirical research examining the brain's pre-attentive and attentional responses to auditory mismatches and language-related mismatches, such as phonological or lexical deviations. These studies employ electrophysiological methods like event-related potentials (ERPs) and pupillometry to understand automatic mismatch negativity (MMN), attention switching, and associated cognitive processes across different populations including adults and young children. Insights inform theories of sensory processing, attention, language acquisition, and cognitive load measurement.