HR job title
- Professor
- Contact Info
- 1 979 862 6441
- Websites
Braga Neto, Ulisses Professor
Positions
My research interests focus on statistical signal processing and control, and pattern recognition and machine learning, with applications in bioinformatics, materials informatics, and epidemiological models.
Research Areas
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Overview
Publications
selected publications
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academic article
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Coutinho, E., Dall'Aqua, M., McClenny, L., Zhong, M., Braga-Neto, U., & Gildin, E.
(2023).
Physics-informed neural networks with adaptive localized artificial viscosity. Journal of Computational Physics.
489, 112265-112265.
-
Guido, R. C., Adali, T., Bjornson, E., Blanc-Feraud, L., Braga-Neto, U., Ghoraani, B., ... Zhu, X.
(2023).
IEEE Signal Processing Society: Celebrating 75 Years of Remarkable Achievements (Part 2). IEEE Signal Processing Magazine.
40(5), 8-11.
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Guido, R. C., Adali, T., Bjoernson, E., Blanc-Feraud, L., Braga-Neto, U., Ghoraani, B., ... Zhu, X.
(2023).
IEEE Signal Processing Society: Celebrating 75 Years of Remarkable Achievements [From the Guest Editors]. IEEE Signal Processing Magazine.
40(4), 3-6.
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Yadav, P. K., Thomasson, J. A., Hardin, R., Searcy, S. W., Braga-Neto, U., Popescu, S. C., ... Wang, T.
(2023).
Detecting volunteer cotton plants in a corn field with deep learning on UAV remote-sensing imagery. Computers and Electronics in Agriculture.
204, 107551-107551.
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Yadav, P. K., Thomasson, J. A., Hardin, R., Searcy, S. W., Braga-Neto, U., Popescu, S. C., ... White, E. L.
(2023).
Plastic Contaminant Detection in Aerial Imagery of Cotton Fields Using Deep Learning. Agriculture (Switzerland).
13(7), 1365-1365.
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Castanha, P., Tuttle, D. J., Kitsios, G. D., Jacobs, J. L., Braga-Neto, U., Duespohl, M., ... Marques, E.
(2022).
Contribution of Coronavirus-Specific Immunoglobulin G Responses to Complement Overactivation in Patients with Severe Coronavirus Disease 2019. Journal of Infectious Diseases.
226(5), 766-777.
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Tan, Y., Neto, F., & Neto, U. B.
(2022).
PALLAS: Penalized mAximum LikeLihood and pArticle Swarms for Inference of Gene Regulatory Networks From Time Series Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
19(3), 1807-1816.
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Yadav, P. K., Thomasson, J. A., Searcy, S. W., Hardin, R. G., Braga-Neto, U., Popescu, S. C., ... Wang, T.
(2022).
Assessing the performance of YOLOv5 algorithm for detecting volunteer cotton plants in corn fields at three different growth stages. 6, 292-303.
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Dhal, S. B., Bagavathiannan, M., Braga-Neto, U., & Kalafatis, S.
(2022).
Nutrient optimization for plant growth in Aquaponic irrigation using Machine Learning for small training datasets. 6, 68-76.
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Ghane, P., Zarnaghinaghsh, N., & Braga-Neto, U.
(2021).
Comparison of Classification Algorithms Towards Subject-Specific and Subject-Independent BCI. 00, 342-347.
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Tan, Y., Iii, D. C., Ndeffo-Mbah, M., & Braga-Neto, U.
(2021).
A stochastic metapopulation state-space approach to modeling and estimating COVID-19 spread. Mathematical Biosciences and Engineering.
18(6), 7685-7710.
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Davi, C., & Braga-Neto, U.
(2020).
A Semi-Supervised Generative Adversarial Network for Prediction of Genetic Disease Outcomes
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McClenny, L., Haile, M., Attari, V., Sadler, B., Braga-Neto, U., & Arroyave, R.
(2020).
Deep Multimodal Transfer-Learned Regression in Data-Poor Domains
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Kunselman, C., Attari, V., McClenny, L., Braga-Neto, U., & Arroyave, R.
(2020).
Semi-supervised learning approaches to class assignment in ambiguous microstructures. ACTA MATERIALIA.
188, 49-62.
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Imani, M., Dougherty, E. R., & Braga-Neto, U.
(2020).
Boolean Kalman filter and smoother under model uncertainty. Automatica.
111, 108609-108609.
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McClenny, L., & Braga-Neto, U.
(2020).
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism
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Bahadorinejad, A., Imani, M., & Braga-Neto, U. M.
(2020).
Adaptive Particle Filtering for Fault Detection in Partially-Observed Boolean Dynamical Systems. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
17(4), 1105-1114.
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Davi, C., Pastor, A., Oliveira, T., Neto, F., Braga-Neto, U., Bigham, A. W., ... Acioli-Santos, B.
(2019).
Severe Dengue Prognosis Using Human Genome Data and Machine Learning. IEEE Transactions on Biomedical Engineering.
66(10), 2861-2868.
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Imani, M., & Braga-Neto, U. M.
(2019).
Control of Gene Regulatory Networks Using Bayesian Inverse Reinforcement Learning. 16(4), 1250-1261.
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Imani, .., & Braga-Neto, U. M.
(2019).
Point-Based Methodology to Monitor and Control Gene Regulatory Networks via Noisy Measurements. IEEE Transactions on Control Systems Technology.
27(3), 1023-1035.
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Hajiramezanali, E., Imani, M., Braga-Neto, U., Qian, X., & Dougherty, E. R.
(2019).
Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty. BMC GENOMICS.
20(Suppl 6), 435.
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Karbalayghareh, A., Braga-Neto, U., & Dougherty, E. R.
(2019).
Classification of Single-Cell Gene Expression Trajectories from Incomplete and Noisy Data. 16(1), 193-207.
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Xie, S., & Braga-Neto, U. M.
(2019).
On the Bias of Precision Estimation Under Separate Sampling. Cancer Informatics.
18, 1176935119860822-117693511986082.
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Imani, M., & Braga-Neto, U.
(2018).
Gene regulatory network state estimation from arbitrary correlated measurements. 2018(1), 22.
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Imani, .., & Braga-Neto, U. M.
(2018).
Control of Gene Regulatory Networks With Noisy Measurements and Uncertain Inputs. 5(2), 760-769.
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Bahadorinejad, A., & Braga-Neto, U. M.
(2018).
Optimal Fault Detection and Diagnosis in Transcriptional Circuits Using Next-Generation Sequencing. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
15(2), 516-525.
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Atashpaz-Gargari, E., Reis, M. S., Braga-Neto, U. M., Barrera, J., & Dougherty, E. R.
(2018).
A fast Branch-and-Bound algorithm for U-curve feature selection. Pattern Recognition.
73, 172-188.
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Imani, .., & Braga-Neto, U. M.
(2018).
Finite-horizon LQR controller for partially-observed Boolean dynamical systems. Automatica.
95, 172-179.
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Karbalayghareh, A., Braga-Neto, U., & Dougherty, E. R.
(2018).
Intrinsically Bayesian robust classifier for single-cell gene expression trajectories in gene regulatory networks. BMC Systems Biology.
12(Suppl 3), 23.
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Imani, .., & Braga-Neto, U. M.
(2018).
Particle filters for partially-observed Boolean dynamical systems. Automatica.
87, 238-250.
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Nagaraja, K., & Braga-Neto, U.
(2018).
Bayesian Classification of Proteomics Biomarkers from Selected Reaction Monitoring Data using an Approximate Bayesian Computation-Markov Chain Monte Carlo Approach. Cancer Informatics.
17, 1176935118786927-117693511878692.
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Karbalayghareh, A., Braga-Neto, U., Hua, J., & Dougherty, E. R.
(2018).
Classification of State Trajectories in Gene Regulatory Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
15(1), 68-82.
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Imani, M., Dehghannasiri, R., Braga-Neto, U. M., & Dougherty, E. R.
(2018).
Sequential Experimental Design for Optimal Structural Intervention in Gene Regulatory Networks Based on the Mean Objective Cost of Uncertainty. Cancer Informatics.
17, 1176935118790247-117693511879024.
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Imani, .., & Braga-Neto, U. M.
(2017).
Maximum-Likelihood Adaptive Filter for Partially Observed Boolean Dynamical Systems. IEEE Transactions on Signal Processing.
65(2), 359-371.
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Mcclenny, L. D., Imani, M., & Braga-Neto, U. M.
(2017).
BoolFilter: an R package for estimation and identification of partially-observed Boolean dynamical systems. BMC Bioinformatics.
18(1), 519.
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Oliveira, R., Cordeiro, M. T., Moura, P., Baptista Filho, P., Braga-Neto, U., Marques, E., & Gil, L.
(2017).
Serum cytokine/chemokine profiles in patients with dengue fever (DF) and dengue hemorrhagic fever (FHD) by using protein array. Journal of Clinical Virology.
89, 39-45.
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Chen, T., & Braga-Neto, U. M.
(2016).
Bayesian estimation of the discrete coefficient of determination. EURASIP Journal on Bioinformatics and Systems Biology.
2016(1), 1-19.
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Chen, T., & Braga-Neto, U. M.
(2015).
Statistical Detection of Intrinsically Multivariate Predictive Genes. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
12(4), 951-963.
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Banerjee, U., & Braga-Neto, U. M.
(2015).
Bayesian ABC-MCMC Classification of Liquid Chromatography-Mass Spectrometry Data. Cancer Informatics.
14(Suppl 5), 175-182.
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Braga-Neto, U. M., Zollanvari, A., & Dougherty, E. R.
(2014).
Cross-validation under separate sampling: strong bias and how to correct it. Bioinformatics.
30(23), 3349-3355.
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Vu, T., Sima, C., Braga-Neto, U. M., & Dougherty, E. R.
(2014).
Unbiased bootstrap error estimation for linear discriminant analysis. EURASIP Journal on Bioinformatics and Systems Biology.
2014(1), 15-14.
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Afsari, B., Braga-Neto, U. M., & Geman, D.
(2014).
Rank discriminants for predicting phenotypes from RNA expression. Annals of Applied Statistics.
8(3), 1469-1491.
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Atashpaz-Gargari, E., Braga-Neto, U. M., & Dougherty, E. R.
(2014).
Modeling and systematic analysis of biomarker validation using selected reaction monitoring. EURASIP Journal on Bioinformatics and Systems Biology.
2014(1), 17-12.
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Chen, T., & Braga-Neto, U. M.
(2013).
Statistical detection of boolean regulatory relationships. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
10(5), 1310-1321.
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Chen, T., & Braga-Neto, U. M.
(2013).
Maximum-Likelihood Estimation of the Discrete Coefficient of Determination in Stochastic Boolean Systems. IEEE Transactions on Signal Processing.
61(15), 3880-3894.
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Xavier Eurico de Alencar, L., de Mendona Braga-Neto, U., Jos Moura do Nascimento, E., Tenrio Cordeiro, M., Maria Silva, A., Alexandre Antunes de Brito, C., ... Marques, E.
(2013).
HLA-B44 Is Associated with Dengue Severity Caused by DENV-3 in a Brazilian Population. 2013, 648475-11.
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Pastor, A. F., Rodrigues Moura, L., Neto, J., Nascimento, E., Calzavara-Silva, C. E., Gomes, A., ... Acioli-Santos, B.
(2013).
Complement factor H gene (CFH) polymorphisms C-257T, G257A and haplotypes are associated with protection against severe dengue phenotype, possible related with high CFH expression. Human Immunology.
74(9), 1225-1230.
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Atashpaz-Gargari, E., Sima, C., Braga-Neto, U. M., & Dougherty, E. R.
(2013).
Relationship between the accuracy of classifier error estimation and complexity of decision boundary. Pattern Recognition.
46(5), 1315-1322.
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Martins, D. C., de Oliveira, E. A., Braga-Neto, U. M., Hashimoto, R. F., & Cesar, R. M.
(2013).
Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables. Information Sciences.
225, 18-34.
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de Melo, A. B., Nascimento, E., Braga-Neto, U., Dhalia, R., Silva, A. M., Oelke, M., ... Marques, E.
(2013).
T-cell memory responses elicited by yellow fever vaccine are targeted to overlapping epitopes containing multiple HLA-I and -II binding motifs. PLoS Neglected Tropical Diseases.
7(1), e1938-e1938.
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Sun, Y., Braga-Neto, U., & Dougherty, E. R.
(2012).
A systematic model of the LC-MS proteomics pipeline. 13 Suppl 6(Suppl 6), S2.
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Allen, C. C., Alves, B., Li, X., Tedeschi, L. O., Zhou, H., Paschal, J. C., ... Amstalden, M.
(2012).
Gene expression in the arcuate nucleus of heifers is affected by controlled intake of high- and low-concentrate diets. Journal of Animal Science.
90(7), 2222-2232.
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Sun, Y., Zhang, J., Braga-Neto, U., & Dougherty, E. R.
(2012).
BPDA2d--a 2D global optimization-based Bayesian peptide detection algorithm for liquid chromatograph-mass spectrometry. Bioinformatics.
28(4), 564-572.
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Zollanvari, A., Braga-Neto, U., & Dougherty, E. R.
(2012).
Exact representation of the second-order moments for resubstitution and leave-one-out error estimation for linear discriminant analysis in the univariate heteroskedastic Gaussian model. Pattern Recognition.
45(2), 908-917.
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Sima, C., Braga-Neto, U. M., & Dougherty, E. R.
(2011).
High-dimensional bolstered error estimation. Bioinformatics.
27(21), 3056-3064.
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Wang, Y., Ghaffari, N., Johnson, C. D., Braga-Neto, U. M., Wang, H., Chen, R., & Zhou, H.
(2011).
Evaluation of the coverage and depth of transcriptome by RNA-Seq in chickens. BMC Bioinformatics.
12 Suppl 10(Suppl 10), S5.
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Wren, J. D., Kupfer, D. M., Perkins, E. J., Bridges, S., Winters-Hilt, S., Dozmorov, M. G., & Braga-Neto, U.
(2011).
Proceedings of the 2011 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference. Introduction. BMC Bioinformatics.
12 Suppl 10(Suppl 10), S1.
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de Melo, A. B., da Silva, M., Magalhes, M., Gonzales Gil, L., Freese de Carvalho, E. M., Braga-Neto, U. M., ... Cordeiro, M. T.
(2011).
Description of a prospective 17DD yellow fever vaccine cohort in Recife, Brazil. AMERICAN JOURNAL OF TROPICAL MEDICINE AND HYGIENE.
85(4), 739-747.
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Zollanvari, A., Braga-Neto, U. M., & Dougherty, E. R.
(2011).
Analytic Study of Performance of Error Estimators for Linear Discriminant Analysis. IEEE Transactions on Signal Processing.
59(9), 4238-4255.
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Dougherty, E. R., Zollanvari, A., & Braga-Neto, U. M.
(2011).
The illusion of distribution-free small-sample classification in genomics. Current Genomics.
12(5), 333-341.
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Chen, T., & Braga-Neto, U.
(2010).
Exact Performance of CoD Estimators in Discrete Prediction. EURASIP Journal on Advances in Signal Processing.
2010(1), 487893.
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Braga-Neto, U., Kuang, R., Lahdesmaki, H., Vikalo, H., & Yoon, B.
(2010).
Genomic Signal Processing. 2010(1), 137263.
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Vu, T. T., & Braga-Neto, U. M.
(2010).
Small-Sample Error Estimation for Bagged Classification Rules. EURASIP Journal on Advances in Signal Processing.
2010(1), 548906.
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Zollanvari, A., Braga-Neto, U. M., & Dougherty, E. R.
(2010).
Joint Sampling Distribution Between Actual and Estimated Classification Errors for Linear Discriminant Analysis. IEEE TRANSACTIONS ON INFORMATION THEORY.
56(2), 784-804.
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Sun, Y., Zhang, J., Braga-Neto, U., & Dougherty, E. R.
(2010).
BPDA - a Bayesian peptide detection algorithm for mass spectrometry. BMC Bioinformatics.
11(1), 490.
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Braga-Neto, U. M., & Dougherty, E. R.
(2010).
Exact correlation between actual and estimated errors in discrete classification. Pattern Recognition Letters.
31(5), 407-412.
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Banon, G., Braga-Neto, U., & Cesar, R.
(2010).
ISMM 2007 Special Issue. Image and Vision Computing.
28(10), 1427-1428.
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Dougherty, E. R., Sima, C., Hua, J., Hanczar, B., & Braga-Neto, U. M.
(2010).
Performance of Error Estimators for Classification. Current Bioinformatics.
5(1), 53-67.
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Sun, Y., Braga-Neto, U., & Dougherty, E. R.
(2009).
Impact of missing value imputation on classification for DNA microarray gene expression data--a model-based study. 2009(1), 504069-504069.
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Nascimento, E., Braga-Neto, U., Calzavara-Silva, C. E., Gomes, A., Abath, F., Brito, C., ... Marques, E.
(2009).
Gene expression profiling during early acute febrile stage of dengue infection can predict the disease outcome. PLoS ONE.
4(11), e7892-e7892.
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Zollanvari, A., Cunningham, M. J., Braga-Neto, U., & Dougherty, E. R.
(2009).
Analysis and modeling of time-course gene-expression profiles from nanomaterial-exposed primary human epidermal keratinocytes. 10 Suppl 11(Suppl 11), S10.
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Wren, J. D., Gusev, Y., Isokpehi, R. D., Berleant, D., Braga-Neto, U., Wilkins, D., & Bridges, S.
(2009).
Proceedings of the 2009 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference. Introduction. 10 Suppl 11(Suppl 11), S1.
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Zollanvari, A., Cunningham, M. J., Braga-Neto, U., & Dougherty, E. R.
(2009).
Analysis and modeling of time-course gene-expression profiles from nanomaterial-exposed primary human epidermal keratinocytes. BMC Bioinformatics.
10(SUPPL. 11),
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Wren, J. D., Gusev, Y., Isokpehi, R. D., Berleant, D., Braga-Neto, U., Wilkins, D., & Bridges, S.
(2009).
Proceedings of the 2009 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference. BMC Bioinformatics.
10(SUPPL. 11),
-
Nascimento, E., Silva, A. M., Cordeiro, M. T., Brito, C. A., Gil, L., Braga-Neto, U., & Marques, E.
(2009).
Alternative complement pathway deregulation is correlated with dengue severity. PLoS ONE.
4(8), e6782-e6782.
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Serpedin, E., Garcia-Frias, J., Huang, Y., & Braga-Neto, U.
(2009).
Applications of signal processing techniques to bioinformatics, genomics, and proteomics. EURASIP Journal on Bioinformatics and Systems Biology.
2009(1), 250306-250306.
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Vu, T. T., & Braga-Neto, U. M.
(2009).
Is bagging effective in the classification of small-sample genomic and proteomic data?. EURASIP Journal on Bioinformatics and Systems Biology.
2009(1), 158368-158368.
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Cordeiro, M. T., Braga-Neto, U., Nogueira, R., & Marques, E.
(2009).
Reliable classifier to differentiate primary and secondary acute dengue infection based on IgG ELISA. PLoS ONE.
4(4), e4945-e4945.
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Braga-Neto, U. M.
(2009).
Classification and error estimation for discrete data. Current Genomics.
10(7), 446-462.
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Zollanvari, A., Braga-Neto, U. M., & Dougherty, E. R.
(2009).
On the sampling distribution of resubstitution and leave-one-out error estimators for linear classifiers. Pattern Recognition.
42(11), 2705-2723.
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Martins, D., Braga-Neto, U. M., Hashimoto, R. F., Bittner, M. L., & Dougherty, E. R.
(2008).
Intrinsically Multivariate Predictive Genes. IEEE Journal of Selected Topics in Signal Processing.
2(3), 424-439.
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Acioli-Santos, B., Segat, L., Dhalia, R., Brito, C., Braga-Neto, U. M., Marques, E., & Crovella, S.
(2008).
MBL2 gene polymorphisms protect against development of thrombocytopenia associated with severe dengue phenotype. Human Immunology.
69(2), 122-128.
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Braga-Neto, U.
(2007).
Fads and fallacies in the name of small-sample microarray classification. IEEE Signal Processing Magazine.
24(1), 91-99.
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Xu, Q., Hua, J., Braga-Neto, U., Xiong, Z., Suh, E., & Dougherty, E. R.
(2006).
Confidence intervals for the true classification error conditioned on the estimated error. Technology in Cancer Research and Treatment.
5(6), 579-589.
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Braga-Neto, U. M., & Marques, E.
(2006).
From functional genomics to functional immunomics: new challenges, old problems, big rewards. PLoS Computational Biology.
2(7), e81-e81.
-
Dougherty, E. R., & Braga-Neto, U.
(2006).
Epistemology of computational biology: Mathematical models and experimental prediction as the basis of their validity. Journal of Biological Systems.
14(1), 65-90.
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Braga-Neto, U., & Dougherty, E. R.
(2005).
Classification. Eurasip Book Series on Signal Processing and Communications.
2, 93-128.
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Braga-Neto, U., & Goutsias, J.
(2005).
Object-based image analysis using multiscale connectivity. IEEE Transactions on Pattern Analysis and Machine Intelligence.
27(6), 892-907.
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Sima, C., Braga-Neto, U., & Dougherty, E. R.
(2005).
Superior feature-set ranking for small samples using bolstered error estimation. Bioinformatics.
21(7), 1046-1054.
-
Braga-Neto, U., & Goutsias, J.
(2005).
Constructing multiscale connectivities. Computer Vision and Image Understanding.
99(1), 126-150.
-
Braga-Neto, U., & Dougherty, E.
(2005).
Exact performance of error estimators for discrete classifiers. Pattern Recognition.
38(11), 1799-1814.
-
Braga-Neto, U.
(2005).
Multiscale connected operators. Journal of Mathematical Imaging and Vision.
22(2-3), 199-216.
-
Braga-Neto, U., & Goutsias, J.
(2004).
Grayscale level connectivity: theory and applications. IEEE Transactions on Image Processing.
13(12), 1567-1580.
-
Braga-Neto, U., Choudhary, M., & Goutsias, J.
(2004).
Automatic target detection and tracking in forward-looking infrared image sequences using morphological connected operators. Journal of Electronic Imaging.
13(4), 802-813.
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Braga-Neto, U. M., & Dougherty, E. R.
(2004).
Is cross-validation valid for small-sample microarray classification?. Bioinformatics.
20(3), 374-380.
-
Braga-Neto, U., & Goutsias, J.
(2004).
Supremal multiscale signal analysis. SIAM Journal on Mathematical Analysis.
36(1), 94-120.
-
Braga-Neto, U., & Dougherty, E.
(2004).
Bolstered error estimation. Pattern Recognition.
37(6), 1267-1281.
-
Braga-Neto, U., Hashimoto, R., Dougherty, E. R., Nguyen, D. V., & Carroll, R. J.
(2004).
Is cross-validation better than resubstitution for ranking genes?. Bioinformatics.
20(2), 253-258.
-
Braga-Neto, U., & Goutsias, J.
(2003).
A theoretical tour of connectivity in image processing and analysis. Journal of Mathematical Imaging and Vision.
19(1), 5-31.
-
Braga-Neto, U., & Goutsias, J.
(2003).
A multiscale approach to connectivity. Computer Vision and Image Understanding.
89(1), 70-107.
-
Han, X., Xu, C., Braga-Neto, U., & Prince, J. L.
(2002).
Topology correction in brain cortex segmentation using a multiscale, graph-based algorithm. IEEE Transactions on Medical Imaging.
21(2), 109-121.
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Braga-Neto, U., & Goutsias, J.
(2002).
Connectivity on complete lattices: New results. Computer Vision and Image Understanding.
85(1), 22-53.
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Candas, A. J., Braga Neto, U., & Carvalho Filho, E.
(1997).
A Mathematical Morphology Approach to the Star/Galaxy Characterization. Journal of the Brazilian Computer Society.
3(3),
-
Coutinho, E., Dall'Aqua, M., McClenny, L., Zhong, M., Braga-Neto, U., & Gildin, E.
(2023).
Physics-informed neural networks with adaptive localized artificial viscosity. Journal of Computational Physics.
489, 112265-112265.
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book
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Braga-Neto, U. M., & Dougherty, E. R.
(2015).
Error Estimation for Pattern Recognition. John Wiley & Sons, Inc..
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Braga-Neto, U. M., & Dougherty, E. R.
(2015).
Error Estimation for Pattern Recognition. John Wiley & Sons, Inc..
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chapter
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Braga Neto, U., & Dougherty, E. R.
(2005).
Classification. Dougherty, E., Shmulevich, I., Chen, J., & Wang, Z. J. (Eds.),
Genomic Signal Processing and Statistics.
(pp. 93-128).
Hindawi Publishing Corporation.
-
Braga Neto, U., & Dougherty, E. R.
(2005).
Classification. Dougherty, E., Shmulevich, I., Chen, J., & Wang, Z. J. (Eds.),
Genomic Signal Processing and Statistics.
(pp. 93-128).
Hindawi Publishing Corporation.
-
conference paper
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Davi, C., & Braga-Neto, U.
(2021).
A SEMI-SUPERVISED GENERATIVE ADVERSARIAL NETWORK FOR PREDICTION OF GENETIC DISEASE OUTCOMES. IEEE International Workshop on Machine Learning for Signal Processing : [proceedings]. IEEE International Workshop on Machine Learning for Signal Processing.
1-6.
-
Tan, Y., Neto, F., & Neto, U. B.
(2018).
INFERENCE OF GENE REGULATORY NETWORKS BY MAXIMUM-LIKELIHOOD ADAPTIVE FILTERING AND DISCRETE FISH SCHOOL SEARCH. IEEE International Workshop on Machine Learning for Signal Processing : [proceedings]. IEEE International Workshop on Machine Learning for Signal Processing.
1-6.
-
Imani, M., Ghoreishi, S. F., & Braga-Neto, U. M.
(2018).
Bayesian control of large MDPs with unknown dynamics in data-poor environments. Advances in Neural Information Processing Systems.
8146-8156.
-
Imani, .., & Braga-Neto, U.
(2018).
Optimal Control of Gene Regulatory Networks with Unknown Cost Function. Proceedings of the ... American Control Conference. American Control Conference.
3939-3944.
-
Hajiramezanali, E., Imani, M., Braga-Neto, U., Qian, X., & Dougherty, E. R.
(2018).
Scalable Optimal Bayesian Classification of Single-Cell Trajectories under Regulatory Model Uncertainty. 596-597.
-
Arslan, E., & Braga-Neto, U. M.
(2017).
Bayesian Top Scoring Pairs for Feature Selection. 387-391.
-
Xie, S., Imani, M., Dougherty, E. R., & Braga-Neto, U. M.
(2017).
Nonstationary Linear Discriminant Analysis. Conference record / Asilomar Conference on Signals, Systems & Computers. Asilomar Conference on Signals, Systems & Computers.
161-165.
-
Imani, .., & Braga-Neto, U. M.
(2017).
Optimal Finite-Horizon Sensor Selection for Boolean Kalman Filter. 1481-1485.
-
Arslan, E., & Braga-Neto, U. M.
(2017).
A Bayesian Approach to Top-Scoring Pairs Classification. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing / sponsored by the Institute of Electrical and Electronics Engineers Signal Processing Society. ICASSP (Conference).
871-875.
-
McClenny, L. D., Imani, .., & Braga-Neto, U. M.
(2017).
Boolean Kalman Filter with Correlated Observation Noise. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing / sponsored by the Institute of Electrical and Electronics Engineers Signal Processing Society. ICASSP (Conference).
866-870.
-
Karbalayghareh, A., Braga-Neto, U., & Dougherty, E. R.
(2017).
CLASSIFICATION OF GAUSSIAN TRAJECTORIES WITH MISSING DATA IN BOOLEAN GENE REGULATORY NETWORKS. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing / sponsored by the Institute of Electrical and Electronics Engineers Signal Processing Society. ICASSP (Conference).
1078-1082.
-
Karbalayghareh, A., Braga-Neto, U., & Dougherty, E. R.
(2017).
Intrinsically Bayesian Robust Classifier for Single-Cell Gene Expression Time Series in Gene Regulatory Networks. 766-767.
-
Imani, M., & Braga-Neto, U.
(2017).
Multiple Model Adaptive Controller for Partially-Observed Boolean Dynamical Systems. Proceedings of the ... American Control Conference. American Control Conference.
1103-1108.
-
Imani, M., & Braga-Neto, U.
(2016).
Point-Based Value Iteration for Partially-Observed Boolean Dynamical Systems with Finite Observation Space. Proceedings of the ... IEEE Conference on Decision & Control / IEEE Control Systems Society. IEEE Conference on Decision & Control.
4208-4213.
-
Imani, M., & Braga-Neto, U.
(2016).
State-Feedback Control of Partially-Observed Boolean Dynamical Systems Using RNA-Seq Time Series Data. Proceedings of the ... American Control Conference. American Control Conference.
227-232.
-
Imani, M., & Braga-Neto, U.
(2015).
Optimal Gene Regulatory Network Inference using the Boolean Kalman Filter and Multiple Model Adaptive Estimation. Conference record / Asilomar Conference on Signals, Systems & Computers. Asilomar Conference on Signals, Systems & Computers.
423-427.
-
Imani, M., & Braga-Neto, U.
(2015).
Optimal State Estimation for Boolean Dynamical Systems using a Boolean Kalman Smoother. 972-976.
-
Jiang, X., & Braga-Neto, U.
(2014).
A Naive-Bayes Approach to Bolstered Error Estimation in High-Dimensional Spaces. 1398-1401.
-
Bahadorinejad, A., & Braga-Neto, U.
(2014).
Optimal Fault Detection in Stochastic Boolean Regulatory Networks. 1386-1389.
-
Braga-Neto, U.
(2013).
PARTICLE FILTERING APPROACH TO STATE ESTIMATION IN BOOLEAN DYNAMICAL SYSTEMS. 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP).
81-84.
-
Zollanvari, A., Braga-Neto, U. M., & Dougherty, E. R.
(2013).
Effect of Mixing Probabilities on the Bias of Cross-Validation Under Separate Sampling. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
98-99.
-
Atashpaz-Gargari, E., Braga-Neto, U. M., & Dougherty, E. R.
(2013).
Improved Branch-and-Bound Algorithm for U-Curve Optimization. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
100-101.
-
Chen, T., & Braga-Neto, U.
(2013).
Optimal Bayesian MMSE Estimation of the Coefficient of Determination for Discrete Prediction. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
66-69.
-
Chen, T., & Braga-Neto, U.
(2012).
A Statistical Test for Intrinsically Multivariate Predictive Genes. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
151-154.
-
Braga-Neto, U.
(2012).
JOINT STATE AND PARAMETER ESTIMATION FOR BOOLEAN DYNAMICAL SYSTEMS. 704-707.
-
Chen, T., & Braga-Neto, U.
(2011).
Sample-based estimators for the instrinsically multivariate prediction score. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
139-142.
-
Afra, S., & Braga-Neto, U.
(2011).
Studying the possibility of peaking phenomenon in linear support vector machines with non-separable data. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
218-221.
-
Zhang, Z., Sun, Y., Braga-Neto, U., Dougherty, E., & Zhang, J.
(2011).
A parallel programming framework with Markovian messaging for LC-MS peptide detection. 1057-1059.
-
Chen, T., & Braga-Neto, U.
(2011).
Maximum Likelihood Estimation of the Binary Coefficient of Determination. Conference record / Asilomar Conference on Signals, Systems & Computers. Asilomar Conference on Signals, Systems & Computers.
1012-1016.
-
Sun, Y., Ulisses, B., & Dougherty, E. R.
(2011).
Modeling and systematic analysis of LC-MS proteomics pipeline. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
112-116.
-
Atashpaz-Gargari, E., Braga-Neto, U. M., & Dougherty, E. R.
(2011).
Multiple Reaction Monitoring: Modeling and Systematic Analysis. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
105-107.
-
Braga-Neto, U.
(2011).
Optimal State Estimation for Boolean Dynamical Systems. Conference record / Asilomar Conference on Signals, Systems & Computers. Asilomar Conference on Signals, Systems & Computers.
1050-1054.
-
Atashpaz-Gargari, E., Sima, C., Braga-Neto, U. M., & Dougherty, E. R.
(2011).
Relationship between the accuracy of classifier error estimation and distribution complexity. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
147-149.
-
Chen, T., & Braga-Neto, U.
(2010).
APPROXIMATE EXPRESSIONS FOR THE VARIANCES OF NON-RANDOMIZED ERROR ESTIMATORS AND COD ESTIMATORS FOR THE DISCRETE HISTOGRAM RULE. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
1-4.
-
Zollanvari, A., Braga-Neto, U. M., & Dougherty, E. R.
(2010).
RMS BOUNDS AND SAMPLE SIZE CONSIDERATIONS FOR ERROR ESTIMATION IN LINEAR DISCRIMINANT ANALYSIS. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
1-4.
-
Vu, T. T., Braga-Neto, U. M., & Dougherty, E. R.
(2009).
BAGGING DEGRADES THE PERFORMANCE OF LINEAR DISCRIMINANT CLASSIFIERS. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
78-79.
-
Sima, C., Vu, T., Braga-Neto, U. M., & Dougherty, E. R.
(2009).
BOLSTERED ERROR ESTIMATOR WITH FEATURE SELECTION. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
17-+.
-
Zollanvari, A., Braga-Neto, M. M., & Dougherty, E. R.
(2009).
SAMPLE SIZE CALCULATION FROM SPECIFIED RMS OF THE RESUBSTITUTION ERROR FOR LINEAR CLASSIFIERS. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
76-77.
-
Braga-Neto, U.
(2008).
An asymptotically-exact expression for the variance of classification error for the discrete histogram rule. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
107-109.
-
Martins-D, C. J., Braga-Neto, U., Bittner, M. L., & Dougherty, E. R.
(2008).
Network properties of intrinsically multivariate predictive genes. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
9-+.
-
Vu, T. T., Braga-Neto, U., & Dougherty, E. R.
(2008).
Preliminary study on bolstered error estimation in high-dimensional spaces. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics.
110-111.
-
Braga-Neto, U.
(2005).
Grayscale level multiconnectivity. 129-138.
-
Braga-Neto, U.
(2005).
Small-sample error estimation: mythology versus mathematics. Proceedings of SPIE.
59160v-59160v-11-11.
-
Han, X., Xu, C., Braga-Neto, U., & Prince, J. L.
(2001).
Graph-based topology correction for brain cortex segmentation. Lecture Notes in Artificial Intelligence.
395-401.
-
Braga-Neto, U. M., & Goutsias, J. I.
(1998).
Detecting mines and minelike objects in highly cluttered multispectral aerial images by means of mathematical morphology. Proceedings of SPIE.
987-999.
-
Davi, C., & Braga-Neto, U.
(2021).
A SEMI-SUPERVISED GENERATIVE ADVERSARIAL NETWORK FOR PREDICTION OF GENETIC DISEASE OUTCOMES. IEEE International Workshop on Machine Learning for Signal Processing : [proceedings]. IEEE International Workshop on Machine Learning for Signal Processing.
1-6.
-
institutional repository document
-
Braga-Neto, U.
(2022).
Characteristics-Informed Neural Networks for Forward and Inverse Hyperbolic Problems
-
Yadav, P. K., Thomasson, J. A., Hardin, R. G., Searcy, S. W., Braga-Neto, U., Popescu, S. C., ... White, E. L.
(2022).
Plastic Contaminant Detection in Aerial Imagery of Cotton Fields with Deep Learning
-
Chen, X., Jeffery, D. J., Zhong, M., McClenny, L., Braga-Neto, U., & Wang, L.
(2022).
Using Physics Informed Neural Networks for Supernova Radiative Transfer Simulation
-
Yadav, P. K., Thomasson, J. A., Hardin, R., Searcy, S. W., Braga-Neto, U., Popescu, S. C., ... Wang, T.
(2022).
Detecting Volunteer Cotton Plants in a Corn Field with Deep Learning on UAV Remote-Sensing Imagery
-
Ghane, P., & Braga-Neto, U.
(2021).
Generalized Resubstitution for Classification Error Estimation
-
Tan, Y., III, D. C., Ndeffo-Mbah, M., & Braga-Neto, U.
(2021).
A stochastic metapopulation state-space approach to modeling and estimating Covid-19 spread
-
McClenny, L. D., Haile, M. A., & Braga-Neto, U. M.
(2021).
TensorDiffEq: Scalable Multi-GPU Forward and Inverse Solvers for Physics Informed Neural Networks
-
Braga-Neto, U.
(2022).
Characteristics-Informed Neural Networks for Forward and Inverse Hyperbolic Problems
Research
principal investigator on
- CIF:Small:Minimum Mean Square Error Estimation and Control of Partially-Observed Boolean Dynamical Systems with Applications in Metagenomics awarded by National Science Foundation - (Arlington, Virginia, United States) 2017 - 2020
- CIF: Small: Optimal Estimation and Network Inference for Boolean Dynamical Systems awarded by National Science Foundation - (Arlington, Virginia, United States) 2013 - 2017
- CAREER: Theory and Application of Small-Sample Error Estimation in Genomic Signal Processing awarded by National Science Foundation - (Arlington, Virginia, United States) 2009 - 2015
investigator on
Teaching
teaching activities
- ECEN214 Elec Circuit Theory Instructor
- ECEN215 Prin Of Electrical Engr Instructor
- ECEN215 Prin Of Electrical Engr: Fra Instructor
- ECEN303 Random Signals & Systems Instructor
- ECEN303 Random Signals&systems-germany Instructor
- ECEN314 Signals And Systems Instructor
- ECEN322 Elec & Magnetic Fields-germ Instructor
- ECEN350 Computer Arch & Design Instructor
- ECEN485 Directed Studies Instructor
- ECEN491 Hnr-research Instructor
- ECEN649 Pattern Recognition Instructor
- ECEN684 Professional Internship Instructor
- ECEN684 Professional Internship Instructor
- ECEN685 Directed Studies Instructor
- ECEN685 Directed Studies:uk/germany Instructor
- ECEN689 Sptp: Mtls Informatics Instructor
- ECEN689 Sptp: Sci Machine Learning Instructor
- ECEN689 Sptp: Scientific Machine Learn Instructor
- ECEN689 Sptp:scientific Machine Learn Instructor
- ECEN691 Research Instructor
- ECEN769 Materials Informatics Instructor
- MSEN660 Materials Informatics Instructor
- MSEN689 Sptp: Mtls Informatics Instructor
Works By Students
chaired theses and dissertations
-
Arslan, Emre (2018-11). A Novel Bayesian Rank-Based Framework for the Classification of High-Dimensional Biological Data.
-
Atashpazgargari, Esmaeil (2014-08). Biomarker Discovery and Validation for Proteomics and Genomics: Modeling And Systematic Analysis.
-
Bahadorinejad, Arghavan (2017-04). Fault Detection and Diagnosis in Gene Regulatory Networks and Optimal Bayesian Classification of Metagenomic Data.
-
Chen, Ting (2013-09). Estimation and Detection of Multivariate Gene Regulatory Relationships.
-
Imani, Mahdi (2019-02). Estimation, Inference and Learning of Partially-Observed Dynamical Systems.
-
Jiang, Xingde (2016-08). Novel Pattern Recognition Approaches to Identification of Gene-Expression Pathways in Banana Cultivars.
-
Koonchanok, Ratanond (2017-12). Computational Tool for Applications of Sparse Canonical Correlation Analysis on Biological Data.
-
Liu, Fan (2018-11). Network Analysis to Reveal Jasmonic Acid Pathway Related Mechanistic Changes for Drought-Tolerant Maize.
-
McClenny, Levi Daniel (2016-08). Optimal State Estimation for Partially Observed Boolean Dynamical Systems in the Presence of Correlated Observation Noise.
-
Nagaraja, Kashyap (2019-04). Bayesian Classification of Proteomics Biomarkers from Selected Reaction Monitoring Data Using an ABC-MCMC Approach.
-
Sun, Youting (2012-07). Model-based Biomarker Detection and Systematic Analysis in Translational Science.
-
Vu, Thang (2012-07). The Bootstrap in Supervised Learning and its Applications in Genomics/Proteomics.
-
Zollanvari, Amin (2012-02). Analytic Study of Performance of Error Estimators for Linear Discriminant Analysis with Applications in Genomics.
Background
education and training
- Ph.D. in Electrical & Computer Engineering, Johns Hopkins University - (Baltimore, Maryland, United States) 2002
- M.S.E. in Electrical & Computer Engineering and Mathematical Sciences, Johns Hopkins University - (Baltimore, Maryland, United States) 1998
- M.S. in Electrical Engineering, State University of Campinas - (Campinas, Brazil) 1994
- B.S. in Electrical Engineering, Federal University of Pernambuco - (Recife, Brazil) 1992
awards and honors
Contact
first name
- Ulisses
has last name
- Braga Neto
mailing address
-
Texas A&M University
Electrical Engineering
3128 TAMU
College Station, TX 77843-3128
USA
Other
In the News
- ulisses@tamu.edu