Rate My Professor Carlos Riveros

Riveros specializes in bioinformatics and health informatics, providing data analysis services for omics sequencing data, integrative analysis, network-based analysis, and business intelligence tools for health data. His research interests include machine learning, statistics, algorithms, multi-dimensional clustering and classification in large to very large datasets, integration of data from multiple domains, and high-performance computing techniques such as massively parallel systems (GPUs) and heterogeneous distributed computing. With 47 peer-reviewed articles, his work has garnered over 1,594 citations (Google Scholar h-index 20, i10-index 37). Key publications encompass 'Identification of genome-wide SNP-SNP and SNP-clinical Boolean interactions in Age-related Macular Degeneration' (2015), 'The MST-kNN with paracliques' (2015), 'Entropy-based High Performance Computation of Boolean SNP-SNP Interactions Using GPUs' (2014), 'kNN-MST-Agglomerative: A fast and scalable graph-based data clustering approach on GPU' (2012), 'A new high-performance computing approach to screen all pairs of SNPs for epistatic interactions' (2010), and recent contributions like 'Inflammation-induced loss of CFTR-expressing airway ionocytes in non-eosinophilic asthma' (2025) and 'Polygenic prediction of body mass index and obesity through the life course and across ancestries' (2025). He has taught courses including Computer Graphics (2008) and Personal Software Process (2008), and co-supervises PhD students.