HR job title
- Assistant Professor
- Contact Info
- ORCiD
- 0000-0003-3071-9043
Arroyo Relion, Jesus Assistant Professor
Positions
- Assistant Professor, Statistics, College of Arts and Sciences
Research interests: Statistical network analysis, high-dimensional data analysis, machine learning, and applications to neuroimaging.
- Overview
- Publications
- Teaching
- Background
- Contact
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Overview
Publications
selected publications
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academic article
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Li, Z., Arroyo, J., Pantazis, K., & Lyzinski, V.
(2023).
Clustered Graph Matching for Label Recovery and Graph Classification. IEEE Transactions on Network Science and Engineering.
10(6), 3384-3395.
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Li, A., Perry, R., Huynh, C., Tomita, T. M., Mehta, R., Arroyo, J., ... Vogelstein, J.
(2023).
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks. SIAM Journal on Mathematics of Data Science.
5(1), 77-96.
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Chung, J., Varjavand, B., Arroyo-Relion, J., Alyakin, A., Agterberg, J., Tang, M., Priebe, C. E., & Vogelstein, J. T.
(2022).
Valid two-sample graph testing via optimal transport Procrustes and multiscale graph correlation with applications in connectomics. 11(1),
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Gasca, N. C., Reyes-Garza, J., Lozano-Esparza, S., Orozco-Del Pino, P., Olivas-Martinez, A., Ulloa-Prez, E., Garbuno-Inigo, A., & Arroyo, J.
(2022).
Effect of Mexico's vaccination program on Covid-19 cases, hospitalizations, and deaths among older adults in Mexico City. SALUD PUBLICA DE MEXICO.
64(4, jul-ago), 424-428.
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Arroyo, J., & Levina, E.
(2022).
Overlapping Community Detection in Networks via Sparse Spectral Decomposition. 84(1), 1-35.
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Pantazis, K., Athreya, A., Arroyo, J., Frost, W. N., Hill, E. S., & Lyzinski, V.
(2022).
The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks. JOURNAL OF MACHINE LEARNING RESEARCH.
23, 141.
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Arroyo, J., Sussman, D. L., Priebe, C. E., & Lyzinski, V.
(2021).
Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks. Journal of Computational and Graphical Statistics.
30(4), 1111-1123.
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Arroyo, J., Priebe, C. E., & Lyzinski, V.
(2021).
Graph Matching between Bipartite and Unipartite Networks: to Collapse, or not to Collapse, that is the Question. IEEE Transactions on Network Science and Engineering.
8(4), 3019-3033.
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Wang, S., Arroyo, J., Vogelstein, J. T., & Priebe, C. E.
(2021).
Joint Embedding of Graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence.
43(4), 1324-1336.
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Chung, J., Bridgeford, E., Arroyo, J., Pedigo, B. D., Saad-Eldin, A., Gopalakrishnan, V., ... Vogelstein, J. T.
(2021).
Statistical Connectomics. Annual Review of Statistics and Its Application.
8(1), 463-492.
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Arroyo, J., Athreya, A., Cape, J., Chen, G., Priebe, C. E., & Vogelstein, J. T.
(2021).
Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace. JOURNAL OF MACHINE LEARNING RESEARCH.
22(141), 1-49.
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Nenning, K., Xu, T., Schwartz, E., Arroyo, J., Woehrer, A., Franco, A. R., ... Langs, G.
(2020).
Joint embedding: A scalable alignment to compare individuals in a connectivity space. NEUROIMAGE.
222, 117232-117232.
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Arroyo Relin, J. D., Kessler, D., Levina, E., & Taylor, S. F.
(2019).
NETWORK CLASSIFICATION WITH APPLICATIONS TO BRAIN CONNECTOMICS. Annals of Applied Statistics.
13(3), 1648-1677.
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Li, Z., Arroyo, J., Pantazis, K., & Lyzinski, V.
(2023).
Clustered Graph Matching for Label Recovery and Graph Classification. IEEE Transactions on Network Science and Engineering.
10(6), 3384-3395.
-
conference paper
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Arroyo, J., & Hou, E.
(2016).
Efficient Distributed Estimation of Inverse Covariance Matrices. 1-5.
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Arroyo, J., & Hou, E.
(2016).
Efficient Distributed Estimation of Inverse Covariance Matrices. 1-5.
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institutional repository document
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Agterberg, J., Lubberts, Z., & Arroyo, J.
(2022).
Joint Spectral Clustering in Multilayer Degree-Corrected Stochastic Blockmodels
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Li, Z., Arroyo, J., Pantazis, K., & Lyzinski, V.
(2022).
Clustered Graph Matching for Label Recovery and Graph Classification
-
Gopalakrishnan, V., Chung, J., Bridgeford, E., Pedigo, B. D., Arroyo, J., Upchurch, L., ... Vogelstein, J. T.
(2020).
Discovery of Multi-Level Network Differences Across Populations of Heterogeneous Connectomes
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Arroyo, J., & Levina, E.
(2020).
Overlapping community detection in networks via sparse spectral decomposition
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Chen, G., Arroyo, J., Athreya, A., Cape, J., Vogelstein, J. T., Park, Y., ... Priebe, C. E.
(2020).
Multiple Network Embedding for Anomaly Detection in Time Series of Graphs
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Chung, J., Bridgeford, E., Arroyo, J., Pedigo, B. D., Saad-Eldin, A., Gopalakrishnan, V., ... Vogelstein, J. T.
(2020).
Statistical Connectomics
-
Pantazis, K., Athreya, A., Arroyo, J., Frost, W. N., Hill, E. S., & Lyzinski, V.
(2020).
The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks
-
Li, M., Kessler, D., Arroyo, J., Freytag, S., Bahlo, M., Levina, E., & Yang, J.
(2020).
Guiding and interpreting brain network classification with transcriptional data
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Arroyo, J., Priebe, C. E., & Lyzinski, V.
(2020).
Graph matching between bipartite and unipartite networks: to collapse, or not to collapse, that is the question
-
Arroyo, J., & Levina, E.
(2020).
Simultaneous prediction and community detection for networks with application to neuroimaging
-
Arroyo Relion, J. D.
(2020).
Multiple Network Embedding for Anomaly Detection in Time Series of Graphs
-
Arroyo Relion, J. D.
(2020).
Multiscale Comparative Connectomics
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Arroyo Relion, J. D.
(2020).
Simultaneous prediction and community detection for networks with application to neuroimaging
-
Chung, J., Varjavand, B., Arroyo, J., Alyakin, A., Agterberg, J., Tang, M., Vogelstein, J. T., & Priebe, C. E.
(2019).
Valid Two-Sample Graph Testing via Optimal Transport Procrustes and Multiscale Graph Correlation with Applications in Connectomics
-
Li, A., Perry, R., Huynh, C., Tomita, T. M., Mehta, R., Arroyo, J., ... Vogelstein, J. T.
(2019).
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks
-
Perry, R., Mehta, R., Guo, R., Yezerets, E., Arroyo, J., Powell, M., ... Vogelstein, J. T.
(2019).
Random Forests for Adaptive Nearest Neighbor Estimation of Information-Theoretic Quantities
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Arroyo, J., Athreya, A., Cape, J., Chen, G., Priebe, C. E., & Vogelstein, J. T.
(2019).
Inference for multiple heterogeneous networks with a common invariant subspace
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Xiong, J., Shen, C., Arroyo, J., & Vogelstein, J. T.
(2019).
Graph Independence Testing
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Arroyo, J., Sussman, D. L., Priebe, C. E., & Lyzinski, V.
(2018).
Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks
-
Wang, S., Arroyo, J., Vogelstein, J. T., & Priebe, C. E.
(2017).
Joint Embedding of Graphs
-
Arroyo-Relin, J. D., Kessler, D., Levina, E., & Taylor, S. F.
(2017).
Network classification with applications to brain connectomics
-
Arroyo, J., & Hou, E.
(2016).
Efficient Distributed Estimation of Inverse Covariance Matrices
-
Agterberg, J., Lubberts, Z., & Arroyo, J.
(2022).
Joint Spectral Clustering in Multilayer Degree-Corrected Stochastic Blockmodels
Teaching
teaching activities
- STAT414 Math Statistics I Instructor
- STAT415 Math Statistics Ii Instructor
- STAT685 Directed Studies Instructor
- STAT689 Sptp: Network Data Analysis Instructor
- STAT691 Research Instructor
- STAT695 Frontiers In Stat Research Instructor
Background
education and training
- Ph.D. in Statistics, University of Michigan-Ann Arbor - (Ann Arbor, Michigan, United States) 2018
- B.S. in Computer Engineering, Instituto Tecnologico Autonomo de Mexico - (Mexico City, Mexico) 2013
- B.Sc. in Applied Mathematics, Instituto Tecnologico Autonomo de Mexico - (Mexico City, Mexico) 2013
Contact
first name
- Jesus
has last name
- Arroyo Relion
Other
- jarroyo@tamu.edu