Multivariate techniques are very intuitive methods, but the mathematics behind are sometimes complex. At CoDaS Lab, we enjoy studying matrix algebra problems and machine learning algorithms that deal with clear practical applications. Often, those practical applications come from our collaboration with other researchers or practitioners (biologists, ecologist, medical doctors, network engineers, etc.), and our role is to provide a technical solution for them.

Topics of interest at CoDaS Lab include (but are not limited to) the selection and validation of multivariate models, the development of statistical inference and sample size strategies, the connection between data and covariance/distance matrices, the derivation of computational solutions for Big Data, and the development of new exploratory data analysis techniques, notably of constrained (e.g., sparse) multivariate models for omics data: genomics, epigenomics, metagenomics, metabolomics, etc.

- Camacho, J., Vitale, R., Morales-Jiménez, D., Gómez-Llorente, C.
**Variable-Selection ANOVA Simultaneous Component Analysis**. Bioinformatics, 202339, 39(1):btac795. - Camacho, J., Díaz, C., Sánchez-Rovira, P.
**Permutation Tests for ASCA in Multivariate Longitudinal Intervention Studies**. Journal of Chemometrics, 202237, 37(7):e3398. - Camacho, J., Smilde, A.K., Saccenti, E., Westerhuis, J., Bro, R.
**All Sparse PCA Models Are Wrong, But Some Are Useful. Part II: Limitations and Problems of Deflation**. Chemometrics and Intelligent Laboratory Systems, 2021208, 208:104212. - Tortorella, S., Servili, M., Toschi, T.G., Cruciani, G., Camacho, J.
**Subspace Discriminant Index to Expedite Exploration of Multi-Class Omics Data**. Chemometrics and Intelligent Laboratory Systems, 2020206, 206:104160. - Camacho, J., Acar, E., Rasmunssen, M., Bro, R.
**Cross-product Penalized Component Analysis (X-CAN)**. Chemometrics and Intelligent Laboratory Systems, 2020203, 203:104038. - Camacho, J., Smilde, A.K., Saccenti, E., Westerhuis, J.
**All Sparse PCA Models Are Wrong, But Some Are Useful. Part I: Computation of Scores, Residuals and Explained Variance**. Chemometrics and Intelligent Laboratory Systems, 2020196, 196:1039072. - Fuentes-García, N.M., González-Martinez, J.M., Maciá-Fernández, G., Camacho, J.
**PARAMO: Enhanced Data Pre-processing in Batch Multivariate Statistical Process Control**. Journal of Chemometrics, 201933, 33(12):e3188. - Camacho, J., Maciá-Fernández, G., Fuentes-García, N.M., Saccenti, E.
**Semi-supervised Multivariate Statistical Network Monitoring for Learning Security Threats**. IEEE Transactions on Information Forensics and Security, 201914, 14(8):2179-2189. - Saccenti, E., Smilde, A.K., Camacho, J.
**Group-wise ANOVA simultaneous component analysis for designed omics experiments**. Metabolomics, 201814, 14(6):73.