## Research

My main research interests are in Bayesian inference for structured, often high-dimensional, discrete spaces, and Computational Statistics.

**Bayesian Statistics**: Statistical inference (point and interval estimation) on high-dimensional discrete spaces: characterization, algorithms, and applications.*Centroid estimation*.**Objective Bayes**:*Variable selection*from invariance-based priors.**Computational Statistics**: MCMC methods in discrete structures and constrained high-dimensional discrete spaces. Graphical models.**Computational Biology**: Bayesian statistical inference applied to sequence analysis, glyco-proteomics, genome-wide association studies (GWAS), and, more generally, systems biology.**Networks**: Community detection and inference in stochastic blockmodels.*Network modeling, regression and regularization*.**Remote Sensing**: Land cover classification and biomass assessment using satellite image data.**Transportation Engineering**: Origin-destination matrix estimation, link count based inference, traffic assignment.

Here is a **long version of my CV**.

## Publications

I would invite any comments, reviews, critiques, or objections to these papers (especially for submitted or in-preparation papers!); please send them to my e-mail.

### Recent and Selected Articles

- Reynolds, D. and Carvalho, L. E.,
**A Latent Association Graph Model for Frequent Itemset Mining**,*Computational Statistics and Data Analysis*, 160, 107229, 2021.`doi:10.1016/j.csda.2021.107229`

. - Pitombeira Neto, A. R., Loureiro, C. F. G., and Carvalho, L. E.,
**A Dynamic Hierarchical Bayesian Model for the Estimation of Day-to-Day Origin-Destination Flows in Transportation Networks**,*Networks and Spatial Economics*, 20, 499-527, 2020.`doi:10.1007/s11067-019-09490-5`

. - Baccini, A., Walker, W., Carvalho, L. E., Farina, M., and Houghton, R. A.,
**Response to Comment on "Tropical forests are a net carbon source based on aboveground measurements of gain and loss"**,*Science*, 363 (6423), eaat1205, 2019.`doi:10.1126/science.aat1205`

. - Pitombeira Neto, A. R., Loureiro, C. F. G., and Carvalho, L. E.,
**Bayesian Inference on Dynamic Linear Models of Day-to-Day Origin-Destination Flows in Transportation Networks**,*Urban Science*, 2 (4), 117, 2018.`doi:10.3390/urbansci2040117`

. - Klein, J., Carvalho, L. E., Zaia, J.,
**Application of Network Smoothing to Glycan LC-MS Profiling**,*Bioinformatics*, 34(20), 3511–3518, 2018.`doi:10.1093/bioinformatics/bty397`

. - Glanz, H. and Carvalho, L. E.,
**An Expectation-Maximization Algorithm for the Matrix Normal Distribution with an Application in Remote Sensing**,*Journal of Multivariate Analysis*, 167, 31–48, 2017.`doi:10.1016/j.jmva.2018.03.010`

. - Baccini, A., Walker, W., Carvalho, L. E., Farina, M., Sulla-Menashe, D., and Houghton, R. A.,
**Tropical Forests Are a Net Carbon Source Based on New Measurements of Gain and Loss**,*Science*, 358 (6360), 230–234, 2017.`doi:10.1126/science.aam5962`

. - Johnston, I., Hancock, T., Mamitsuka, H., and Carvalho, L. E.,
**Gene-Proximity Models for Genome-Wide Association Studies**,*Annals of Applied Statistics*, 10 (3), 1217–1244, 2016.`doi:10.1214/16-AOAS907`

. - Peng, L. and Carvalho, L. E.,
**Bayesian Degree-Corrected Stochastic Blockmodels for Community Detection**,*Electronic Journal of Statistics*, 10 (2), 2746–2779, 2016.`doi:10.1214/16-EJS1163`

. - Pham, L. M., Carvalho, L. E., Schaus, S., and Kolaczyk, E. D.,
**Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian Hierarchical Approach**,*Journal of the American Statistical Association*, 111 (513), 73–92, 2015.`doi:10.1080/01621459.2015.1110523`

.

### Submitted

- Wang, L. and Carvalho, L. E.,
**Deviance Matrix Factorization**. [ ArXiv ] - Ahelegbey, D. F., Carvalho, L. E., Kolaczyk, E.,
**A Bayesian Covariance Graphical and Latent Position Model for Multivariate Financial Time Series**. [ ArXiv ] - Upton, E. and Carvalho, L. E.,
**Bayesian Network Regularized Regression for Modeling Urban Crime Occurrences**. [ ArXiv ]

## Teaching

**Fall 2022**: *Statistical Practicum 1* (MA 675) and *Applied Statistical Modeling* (MA 678).

**Spring 2023**: *Statistical Practicum 2* (MA 676) and *Data Science with R* (MA 415/615).

Previous courses: Basic Statistics and Probability (MA 213), Applied Statistics (MA 214), Data Science in R (MA 415/615), Linear Models (MA 575), Generalized Linear Models (MA 576), Bayesian Statistics (MA 578), Computational Statistics (MA 589), Statistical Machine Learning (MA 751).

## Students

### Current

- Dan Cunha (PhD)
- Likun Chou (PhD)
- Man Huang (PhD)

### Past

**Liang Wang**(PhD 2022)**Ryan Frost**(PhD 2022, currently Applied Research Scientist, Ethos)**David Reynolds**(PhD 2021, currently Lecturer, Statistics, University of New Hampshire)**Elizabeth Upton**(PhD 2019, currently Assistant Professor, Statistics, Williams College)**Ian Johnston**(PhD 2015, currently VP Data Scientist Manager, Morgan Stanley)**Lijun Peng**(PhD 2015, currently Senior Staff Engineer, LinkedIn)**Hunter Glanz**(PhD 2014, currently Associate Professor, Statistics, Cal Poly San Luis Obispo)

## Software

I am very fond of a powerful, fast, light scripting language called Lua:

- Numeric Lua is a numerical package for the Lua programming language. It includes support for complex numbers, multidimensional matrices, random number generation, and special functions.
- Simulua is a discrete-event simulation library for Lua, in the same tradition and flavor of the SIMULA family of programming languages.

I have also developed a few extensions to PostgreSQL:

- PL/Lua is an implementation of Lua as a loadable procedural language for PostgreSQL: with PL/Lua you can use PostgreSQL functions and triggers written in the Lua programming language.
- PostBio is a set of bioinformatics extensions for PostgreSQL.
- PostStat is a set of statistics extensions for PostgreSQL.