Publications#

This page contains selected publications in the fields of Smart Cities, Neuroscience, and High-Performance Computing.

For a full list of publication, check my Lattes curriculum and Google Scholar page.

Neuroscience

  • Directed functional and structural connectivity in a large-scale model for the mouse cortex.

    • Nunes, RV.; Reyes, MB; Mejias, JF; de Camargo, Raphael Y.

    • Network Neuroscience, v. 1, p. 1-16, 2021 (JCR 4.625)

  • A model for the peak-interval task based on neural oscillation-delimited states.

    • Varella, Thiago T; Reyes, Marcelo B; Caetano, Marcelo S; de Camargo, Raphael Y

    • Behavioural Processes, v. 168, p. 103941, 2019.

  • Dissociating the sequential dependency of subjective temporal order from subjective simultaneity.

    • Recio, Renan S; Cravo, André M; de Camargo, Raphael Y; Van Wassenhove, Virginie

    • PLoS One, v. 14, p. e0223184, 2019.

  • Approaching subjective interval timing with a non-Gaussian perspective.

    • Aquino, TG; de Camargo, RY; Reyes, MB.

    • Journal of Mathematical Psychology, v. 84, p. 13-19, 2018. (JCR 1.377)

  • Heteroassociative storage of hippocampal pattern sequences in the CA3 subregion.

    • de Camargo, RY; Recio, RS; Reyes, MB.

    • PeerJ, v. 6, p. E4203, 2018. (JCR 2.177)

  • A common representation of time across visual and auditory modalities.

    • Barne, Louise C; Sato, João R; de Camargo, Raphael Y; Claessens, Peter ME; Caetano, Marcelo S; Cravo, André M

    • Neuropsychologia, v. 119, p. 223-232, 2018.

  • Dynamic representation of time in brain states.

    • Bueno, FD; Morita VC, de Camargo, RY; Reyes, MB; Caetano, MS; Cravo, A.

    • Scientific Reports, v. 7, p. 46053, 2017. (JCR 4.379)

Smart Cities and Health

  • Predicting Dengue Outbreaks with Explainable Machine Learning

    • Aleixo, Robson; Kon, Fabio; Rocha, Rudi; Camargo, Marcela Santos; de Camargo, Raphael Y.

    • 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid) - Workshop AI4Health, 2022, Taormina, Italy.

  • Cravo, A; De Azevedo, G; Azarias, C; Barne, L; Bueno, F; de Camargo, RY; Morita, V; Sirius, E; Recio, R; Silvestrin, M; de Azevedo Neto, R.

    • Time experience during social distancing: A longitudinal study during the first months of COVID-19 pandemic in Brazil.

    • Science Advances, v. 8, p. 1, 2022.

  • Efficient Prediction of Region-wide Traffic States in Public Bus Networks using LSTMs.

    • Amaris, M; Morais, M.; de Camargo, RY.

    • 24th IEEE International Conference on Intelligent Transportation - ITSC, 2021, Indianápolis, EUA. p. 1-6

  • Morais, Mayuri; Camargo, Raphael Y.

    • A Framework for Scalable Data Analysis and Model Aggregation for Public Bus Systems.

    • III Workshop de Computação Urbana (CoUrb), 2019.

High-Performance Computing

  • Improving the performance of batch schedulers using online job runtime classification

    • Zirigui, Salah; de Camargo, Raphael Y.; Legrand, Arnaud; Trystam, Denis.

    • Journal of Parallel and Distributed Computing, v. 164, p. 83-95, 2022.

  • Evaluating Execution Time Predictions on GPU Kernels Using an Analytical Model and Machine Learning Techniques

    • Amaris, Marcos; de Camargo, Raphael; Cordeiro, Daniel; Goldman, Alfredo; Trystam, Denis

    • Journal of Parallel and Distributed Computing, v. 1, p. 1, 2022.

  • One Can Only Gain by Replacing EASY Backfilling: A Simple Scheduling Policies Case Study

    • Carastan-Santos, Danilo; de Camargo, Raphael Y.; Trystam, Dennis; Zrigui, Salah

    • 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2019, Larnaca. 2019. Best paper award

  • Real-Time Scheduling Policy Selection from Queue and Machine States

    • Sant’Ana, Luis ; Carastan-Santos, Danilo; Codeiro, Daniel; de Camargo, Raphael

    • 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2019, Larnaca, Cyprus.

  • Sant’Ana, Luis; Cordeiro, Daniel; de Camargo, Raphael Y.

    • PLB-HAC: Dynamic Load-Balancing for Heterogeneous Accelerator Clusters.

    • 25th International Conference on Parallel and Distributed Computing, 2019, Göttingen. LNCS: Euro-Par 2019: Parallel Processing, 2019. p. 197-209.

  • A hybrid CPU-GPU-MIC algorithm for minimal hitting set enumeration.

    • Carastan-Santos, Danilo; Martins Jr., David; Song, Siang W. ; Rozante, Luiz; de Camargo, Raphael Y.

    • Concurrency and Computation: Practice and Experience, v. 1, p. e5087, 2018.

  • Obtaining dynamic scheduling policies with simulation and machine learning

    • Carastan-Santos D.; de Camargo, Raphael Y.

    • International Conference for High Performance Computing, Networking, Storage and Analysis (SC-Supercomputing), 2017, Denver. Nominated for best paper award

  • Finding exact hitting set solutions for systems biology applications using heterogeneous GPU clusters

    • Carastan-Santos, D; de Camargo, RY; Martins, DC; Song, SW. ; Rozante, LCS

    • Future Generation Computer Systems, v. 67, p. 418-429, 2016. (JCR 7.187)

  • A comparison of GPU execution time prediction using machine learning and analytical modeling. 2016

    • Amaris, MA; de Camargo, RY; Dyab, M; Goldman, Alfredo; Trystam, D.

    • IEEE 15th International Symposium on Network Computing and Applications (NCA), 2016. p. 326.

  • PLB-HeC: A Profile-Based Load-Balancing Algorithm for Heterogeneous CPU-GPU Clusters.

    • Sant’Ana, L; Cordeiro, D; de Camargo, RY.

    • IEEE International Conference on Cluster Computing (CLUSTER), 2015, Chicago. p. 96-105.

  • A Simple BSP-based Model to Predict Execution Time in GPU Applications.

    • Amaris, MA; Cordeiro, D; Goldman, Alfredo; de Camargo, RY.

    • 2015 IEEE 22nd International Conference on High Performance Computing (HiPC), 2015, p. 285-294.

  • Borelli, FF; de Camargo, RY; Martins Jr., D. C.; Rozante, Luiz .

    • Gene regulatory networks inference using a multi-GPU exhaustive search algorithm.

    • BMC Bioinformatics, v. 14, p. S5, 2013.

  • Gene regulatory networks inference using a multi-GPU exhaustive search algorithm.

    • Borelli, F. F.; de Camargo, Raphael Y.; Martins Jr., D. C.; Rozante, Luiz.

    • BMC Bioinformatics, v. 14, p. S5, 2013. (JCR 2.448)

  • A multi-GPU algorithm for large-scale neuronal networks.

    • de Camargo, Raphael Y.; Rozante, Luiz; Song, Siang W.

    • Concurrency and Computation: Practice and Experience, v. 23, p. 556-572, 2011.

  • A Multi-GPU Algorithm for Communication in Neuronal Network Simulations.

    • de Camargo, Raphael Y.

    • 18th IEEE Annual International Conference on High Performance Computing (HiPC 2011), 2011, Bangalore

  • A multi-GPU algorithm for large-scale neuronal networks.

    • de Camargo, Raphael Y.; Rozante, Luiz ; Song, Siang W. .

    • Concurrency and Computation: Practice and Experience, v. 23, p. 556-572, 2011.

  • Application execution management on the InteGrade opportunistic grid middleware.

    • da Silva e Silva, Francisco José; Kon, Fabio; Goldman, Alfredo; Finger, Marcelo; de Camargo, Raphael Y.; Filho, Fernando Castor; Costa, Fábio M.

    • Journal of Parallel and Distributed Computing (Print), p. 573-583, 2010.

  • Reliable management of checkpointing and application data in opportunistic grids.

    • Camargo, Raphael Y.; Castor, Fernando ; Kon, Fabio .

    • Journal of the Brazilian Computer Society (Impresso), v. 16, p. 1, 2010.

  • Exploiting A Generic Approach To Construct Component-Based Systems Software In Linux Environments

    • Ueyama, Jó; Madeira, Edmundo R. M.; Taiani, Francois; Camargo, Raphael Y.; Grace, Paul; Coulson, Geoff

    • International Journal of Software Engineering and Knowledge Engineering, v. 20, p. 843, 2010.

  • Checkpointing BSP parallel applications on the InteGrade Grid middleware.

    • de Camargo, Raphael Y.; Goldchleger, Andrei; Kon, Fabio; Goldman, Alfredo.

    • Concurrency and Computation, v. 18, p. 567-579, 2006.

  • Strategies for Checkpoint Storage on Opportunistic Grids.

    • de Camargo, Raphael Y.; Kon, F. ; Cerqueira, R.

    • IEEE Distributed Systems Online, v. 7, p. 1-1, 2006.