Sanguthevar Rajasekaran
Department Head & Distinguished Professor/Computing
Storrs Mansfield
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Scholarly Contributions
239 Scholarly Contributions
Identifying suitable attributes for Record Linkage using Association Analysis
Research Type: Conference Proceedings
Improved algorithms for finding edit distance based motifs
2024
Research Type: Conference Proceedings
Improved algorithms for parsing ESLTAGs: a grammatical model suitable for RNA pseudoknots.
2010
Research Type: Journal Article
Indoor radon exposure and its correlation with the radiometric map of uranium in Sweden
2022
Research Type: Journal Article
Information centric approach to analysing security threats and node behaviour in underwater sensor networks
2018
Research Type: Journal Article
Integrating Equilibrium Assignment in Game-theoretic Approach to Measure Many-to-Many Transportation Network Vulnerability
2024
Research Type: Conference Proceedings
JUMP: A fast deterministic algorithm to find the closest pair of subsequences
2024
Research Type: Conference Proceedings
Latent Autoregressive Student-t Prior Process Models to Assess Impact of Interventions in Time Series
2024
Research Type: Journal Article
Leg Cycling Dynamics Of Individuals With Spinal Cord Injury During Stationary Leg Cycle Ergometry
2005
Research Type: Journal Article
MSPP: A Highly Efficient and Scalable Algorithm for Mining Similar Pairs of Points
2024
Research Type: Conference Proceedings
Machine Learning Techniques in Structure-Property Optimization of Polymeric Scaffolds for Tissue Engineering
2024
Research Type: Conference Proceedings
Many-to-Many Game Theoretic Approach to Measuring Transportation Network Vulnerability
2011
Research Type: Digital and Electronic Media, Social Media, Blog, Podcast, Magazine/Trade Publication
Metabolic pathway predictions for metabolomics: a molecular structure matching approach
2015
Research Type: Journal Article
Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences
2012
Research Type: Journal Article