Jorge M. Cortés-Mendoza
Jorge M. Cortés-Mendoza
(a.k.a. Jorge Mario Cortés-Mendoza)
(a.k.a. Jorge Mario Cortés-Mendoza)
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Postdoctoral researcher,
Cloud Competency Centre (CCC),
National College of Ireland (NCI),
Office S2.13, Block R West, Spencer Dock D01N6P6. Dublin 1, Ireland.
Tel: (+353) 1 449 8533.
Email: JorgeMario.CortesMendoza@ncirl.ie, jorge.cortes@upam.edu.mx.
Researchgate, Google scholar, ORCID, Scopus, Web of Science, Publons, Linkedin, NCI.
Journals
Journals
J.M. Cortés-Mendoza, A. Żyra, A. Tchernykh, and H. González-Vélez. Determining Material Removal and Electrode Wear in Electric Discharge Machining with a Generalist Machine Learning Framework. Materials, vol. 19(2), 2026. IF 3.2, Q2. DOI: 10.3390/ma19020438.
J.M. Cortés-Mendoza, A. Żyra, and H. González-Vélez. Prediction of machining characteristics in coolant-assisted dry EDM of Inconel 625 and Titanium Grade 2 using Machine Learning. Measurement, 2025. IF: 5.2, Q2. DOI: 10.1016/j.measurement.2025.117966.
M. Valueva, G. Valuev, M. Babenko, A. Tchernykh, and J.M. Cortés-Mendoza. Method for Convolutional Neural Network Hardware Implementation Based on a Residue Number System. Programming and Computer Software, vol. 48(8), 2022. IF 0.936, Q3. DOI: 10.1134/S0361768822080217.
A. Tchernykh, M. Babenko, E. Shiriaev, L.B. Pulido-Gaytan, J.M. Cortés-Mendoza, A. Avetisyan, A. Yu. Drozdov, and V. Kuchukov. An efficient method for comparing numbers and determining the sign of a number in RNS for even ranges. Computation 10(2):17, 2022. IF 0.873, Q2. DOI: 10.3390/computation10020017.
R.M. Canosa-Reyes, A. Tchernykh, J.M. Cortés-Mendoza, L.B. Pulido-Gaytan, R. Rivera-Rodriguez, J.E. Lozano-Rizk, E.R. Concepción-Morales, H.E. Castro-Barrera, C.J. Barrios-Hernandez, F. Medrano-Jaimes, A. Avetisyan, M. Babenko, and A. Yu. Drozdov. Dynamic performance–Energy tradeoff consolidation with contention-aware resource provisioning in containerized clouds. PLoS ONE 17(1): e0261856, 2022. IF 1.349, Q1. DOI: 10.1371/journal.pone.0261856.
M. Babenko, A. Nazarov, A. Tchernykh, L.B. Pulido-Gaytan, J.M. Cortés-Mendoza, and I. Vashchenko. Algorithm for constructing modular projections for correcting multiple errors based on a redundant residue number system using maximum likelihood decoding. Programming and Computer Software, vol. 47(8), 2021. IF 0.936, Q3. DOI: 10.1134/S0361768821080089.
N. Vershkov, M. Babenko, A. Tchernykh, L.B. Pulido-Gaytan, J.M. Cortés-Mendoza, V. Kuchukov, and N. Kuchukova. Optimization of neural network training for image recognition based on trigonometric polynomial approximation. Programming and Computer Software, vol. 47(8), 2021. IF 0.936, Q3. DOI: 10.1134/S0361768821080272.
L.B. Pulido-Gaytan, A. Tchernykh, J.M. Cortés-Mendoza, M. Babenko, G. Radchenko, A. Avetisyan, and A. Yu. Drozdov. Privacy-Preserving Neural Networks via Homomorphic Encryption: Challenges and Opportunities. Peer-to-Peer Networking and Applications: Special Issue on Advances in Privacy-Preserving Computing, Springer, 2020. IF 2.793, Q2. DOI: 10.1007/s12083-021-01076-8
A. Tchernykh, M. Babenko, N. Chervyakov, V. Miranda-López, V. Kuchukov, J.M. Cortés-Mendoza, M. Deryabin, N. Kucherov, G. Radchenko, and A. Avetisyan. AC-RRNS: Anti-Collusion Secured Data Sharing Scheme for Cloud Storage. International Journal of Approximate Reasoning. Special Issue on Uncertainty in Cloud Computing: Concepts, Challenges, and Current Solutions. Elsevier, 2018. IF 2.845, Q2. DOI: 10.1016/j.ijar.2018.07.010.
A. Tchernykh, J.M. Cortés-Mendoza, A. Feoktistov, I. Bychkov, L. Didelot, P. Bouvry, G. Radchenko, and K. Borodulin. Configurable Cost-Quality Optimization of Cloud-based VoIP. Journal of Parallel and Distributed Computing, Special issue on "Advances in Parallel and Distributed Computing and Optimization". Elsevier, 2017. IF 1.930, Q2. DOI: 10.1016/j.jpdc.2018.07.001.
N. Chervyakov, M. Babenko, A. Tchernykh, N. Kucherov, V. Miranda-López, and J.M. Cortés-Mendoza. AR-RRNS: Configurable reliable distributed data storage systems for Internet of Things to ensure security. Future Generation Computer Systems. Special Issue on Resource Management for Big Data Platforms. Elsevier Science, 2017. IF 3.997, Q1. DOI: 10.1016/j.future.2017.09.061.
F.A. Armenta-Cano, A. Tchernykh, J.M. Cortés-Mendoza, R. Yahyapour, A. Yu. Drozdov, P. Bouvry, D. Kliazovich, A. Avetisyan, and S. Nesmachnow. Min_c: Heterogeneous Concentration Policy for Power Aware Scheduling. ISSN 0361-7688, Programming and Computer Software, Vol. 43 (3), 2017. IF 0.39, Q4. DOI: 10.1134/S0361768817030021.
J.M. Cortés-Mendoza, A. Tchernykh, F.A. Armenta-Cano, P. Bouvry, A. Yu. Drozdov, and L. Didelot. Biobjective VoIP Service Management in Cloud Infrastructure. Scientific Programming, 2016. IF 0.455, Q3. DOI: 10.1155/2016/5706790.
J.M. Cortés-Mendoza, A. Tchernykh, A.M. Simionovici, P. Bouvry, S. Nesmachnow, B. Dorronsoro, and L. Didelot. VoIP Service Model for Multi-objective Scheduling in Cloud Infrastructure. IJMHeur - International Journal of Metaheuristics. Inderscience, 2015. DOI: 10.1504/IJMHEUR.2015.074251.
Conferences
Conferences
M. A. Ojewale, A. E. Chis, J.M. Cortés-Mendoza, B. Pulido-Gaytan, and H. González-Vélez. FlashbackCL: Mitigating Temporal Forgetting in Federated Learning. FLTA 2026 - 4th International Conference on Federated Learning Technologies and Applications. Paris, France. October 2026, (Accepted). DOI: 10.48550/arXiv.2606.03939.
J.M. Cortés-Mendoza, B. Pulido-Gaytan, G. Román-Alonso, A. Tchernykh, A. Yu. Drozdov, and H. González-Vélez. Hierarchical Federated Learning with Logistic Regression and Connection Failures at the Edge. FLTA 2026 - 4th International Conference on Federated Learning Technologies and Applications. Paris, France. October 2026 (Accepted).
J.M. Cortés-Mendoza, B. Pulido-Gaytan, G. Román-Alonso, A. Tchernykh, and H. González-Vélez. Bi-objective analysis of trained layer subsets for a CNN across Federated Learning environments. FLTA 2026 - 4th International Conference on Federated Learning Technologies and Applications. Paris, France. October 2026, (Accepted).
V. Poswal, J.M. Cortés-Mendoza, and Y. Kumar. The IDS Framework for Recognizing Unusual Activity in IoT Networks. IMPACT 2026 - International Conference on Multidisciplinary Perspectives in Advanced Computing and Technology. Uttarakhand, India. January 2026, pp. 309-322 DOI: 10.65890/dmp-lncse.IMPACT26.136.
A.G. Calzada-Jasso, A. Tchernykh, I.D. Avendaño-Pacheco, J.M. Cortés-Mendoza, B. Pulido-Gaytan, M. Babenko, A. Goldman, and H. González-Vélez. Generative Fabrication of Medical Images for Machine Learning Training. SBAC-PAD 2025 - 37th International Symposium on Computer Architecture and High Performance Computing. Bonito, Brazil. October 2025, pp. 136-145. DOI: 10.1109/SBAC-PAD66369.2025.00022.
J.M. Cortés-Mendoza, A. Tchernykh, and H. González-Vélez. Training Policy for Privacy-Preserving Logistic Regression in Federated Learning Environments. FLTA 2024 - 2nd IEEE International Conference on Federated Learning Technologies and Applications. Valencia, Spain. September 2024, pp. 1-8, DOI: 10.1109/FLTA63145.2024.10839854.
L.B. Pulido-Gaytan, A. Tchernykh, M. Babenko, H. González-Vélez, J.M. Cortés-Mendoza, and Arutyun Avetisyan. Enhancing Cloud Security through Efficient Polynomial Approximations for Homomorphic Evaluation of Neural Network Activation Functions. SIoTEC 2024 - 5th Workshop on Secure IoT, Edge, and Cloud systems, as part of CCGRID 2024. Philadelphia, USA. May 2024, pp. 42-49. DOI: 10.1109/CCGridW63211.2024.00011.
E. Bezuglova, E. Shiryaev, M. Babenko, A. Tchernykh, L.B. Pulido-Gaytan, and J.M. Cortés-Mendoza. A survey on multi-cloud storage security: threats and countermeasures. AICTS 2021 - 2nd international workshop on advanced information and computation technologies and systems. Irkutsk, Russia. December 2021, pp. 72-80. DOI: 10.25743/ICT.2023.28.1.008.
A. Tchernykh, I. Rescalvo-Anastacio, J.M. Cortés-Mendoza, L.B. Pulido-Gaytan, A. Hollay, M. Babenko, A. Yu. Drozdov, and S. Nesmachnow. Pointer Networks with Reinforcement Learning for Reliability and Performance Optimization of Secure Multi-Cloud Storage. ISPRAS OPEN 2021 - Ivannikov ISP RAS Open Conference. Moscow, Russia, December 2021.
E. Shiryaev, E. Bezuglova, M. Babenko, A. Tchernykh, L.B. Pulido-Gaytan, and J.M. Cortés-Mendoza. Performance Impact of Error Correction Codes in RNS with Returning Methods and Base Extension. En&T 2021 - International conference “Engineering and Telecommunication”. Moscow/Dolgoprudny, Russia. November 2021, pp. 1-5. DOI: 10.1109/EnT50460.2021.9681756.
J.M. Cortés-Mendoza, A. Tchernykh, M. Babenko, L.B. Pulido-Gaytán, and G. Radchenko. Multi-Cloud Privacy-Preserving Logistic Regression. RuSCDays'21 - The Russian Supercomputing Days. Moscow, Russia. September 2021, pp. 457–471. DOI: 10.1007/978-3-030-92864-3_35.
A. Tchernykh, M. Babenko, L.B. Pulido-Gaytan, E. Shiryaev, E. Golimblevskaia, A. Avetisyan, N. Viet Hung, and J.M. Cortés-Mendoza. Cryptographic Primitives Optimization Based on the Concepts of the Residue Number System and Finite Ring Neural Network. OLA 2021 - The International Conference in Optimization and Learning. Catania, Sicilia, Italy. June 2021, pp. 241–253. DOI: 10.1007/978-3-030-85672-4_18.
M. Babenko, A. Tchernykh, L.B. Pulido-Gaytan, J.M. Cortés-Mendoza, E. Shiryaev, E. Golimblevskaia, A. Avetisyan, and S. Nesmachnow. RRNS Base Extension Error-Correcting Code for Performance Optimization of Scalable Reliable Distributed Cloud Data Storage. PDCO 2021 - 11th IEEE Workshop Parallel / Distributed Computing and Optimization, as part of the IPDPS 2021. Portland, Oregon, USA. June 2021, pp. 548-553. DOI: 10.1109/IPDPSW52791.2021.00087.
J.M. Cortés-Mendoza, G. Radchenko, A. Tchernykh, L.B. Pulido-Gaytan, M. Babenko, A. Avetisyan, P. Bouvry, and A. Zomaya. LR-GD-RNS: Enhanced Privacy-Preserving Logistic Regression Algorithms for Secure Deployment in Untrusted Environments. SIoTEC 2021 - 2nd Workshop on Secure IoT, Edge, and Cloud systems, as part of CCGRID 2021. Melbourne, Australia. May 2021, pp. 770-775. DOI: 10.1109/CCGrid51090.2021.00093.
L.B. Pulido-Gaytan, A. Tchernykh, M. Babenko, J.M. Cortés-Mendoza, Gleb Radchenko, Arutyun Avetisyan, Alexander Yu. Drozdov. Privacy-Preserving Toward Fast and Accurate Polynomial Approximations for Practical Homomorphic Evaluation of Neural Network Activation Functions. SPCLOUD 2020 - International Workshop on Security, Privacy, and Performance of Cloud Computing, as part of HPCS 2020. Barcelona, Spain. March 2021.
A. Tchernykh, A. Facio-Medina, L.B. Pulido-Gaytan, J.M. Cortés-Mendoza, G. Radchenko, M. Babenko, I. Chernykh, I. Kulikov, S. Nesmachnow, and R. Rivera-Rodriguez. Toward digital twins' workload allocation on clouds with low-cost microservices streaming interaction. ISPRAS OPEN 2020 - Ivannikov ISP RAS Open Conference, Moscow, Russia. December 2020, pp. 115-121. DOI: 10.1109/ISPRAS51486.2020.00024.
M. Babenko, A. Tchernykh, L.B. Pulido-Gaytan, E. Golimblevskaia, J.M. Cortés-Mendoza, Arutyun Avetisyan. Experimental Evaluation of Homomorphic Comparison Methods. ISPRAS OPEN 2020 - Ivannikov ISP RAS Open Conference, Moscow, Russia, December 2020. DOI: 10.1109/ISPRAS51486.2020.00017.
L.B. Pulido-Gaytan, A. Tchernykh, J.M. Cortés-Mendoza, M. Babenko, and G. Radchenko. A Survey on Security-Preserving of Machine Learning with Fully Homomorphic Encryption. CARLA 2020 - The Latin America High Performance Computing Conference. Cuenca, Ecuador. September 2020, pp. 69-74. DOI: 10.1007/978-3-030-68035-0_9.
J.M. Cortés-Mendoza, A. Tchernykh, M. Babenko, L.B. Pulido-Gaytán, and G. Radchenko. Privacy-Preserving Logistic Regression as a Cloud Service Based on Residue Number System. RuSCDays'20 - The Russian Supercomputing Days. Moscow, Russia. September 2020, pp. 598–610. DOI:10.1007/978-3-030-64616-5_51.
R.M. Canosa-Reyes, A. Tchernykh, J.M. Cortés-Mendoza, E. Concepción-Morales, J. Lozano-Rizk, R. Rivera-Rodriguez, F. Medrano-Jaimes, C.J. Barrios-Hernandez, and H.E. Castro-Barrera. Priority allocation strategies for bi-objective optimization in container-based clouds. ISUM 2019 - Tenth International Supercomputing Conference in Mexico. Monterrey, Nuevo Leon, Mexico. March 2019.
R.M. Canosa-Reyes, A. Tchernykh, J.M. Cortés-Mendoza, R. Rivera-Rodriguez, J.E. Lozano-Rizk, A. Avetisyan, Z. Du, G. Radchenko, and E. Concepción-Morales. Energy consumption and quality of service optimization in containerized cloud computing. ISPRAS OPEN 2018 - Ivannikov ISP RAS Open Conference. Moscow, Russia. November 2018, pp. 47-55. DOI: 10.1109/ISPRAS.2018.00014.
A. Tchernykh, R.M. Canosa-Reyes, J.M. Cortés-Mendoza, A. Avetisyan, and R. Rivera-Rodriguez. Bi-objective strategies for resource optimization in containerized cloud computing. CARLA 2018 - Latin American Conference on High Performance Computing. Piedecuesta, Colombia. September 2018.
J.M. Cortés-Mendoza and A. Tchernykh. Cloud-Based Hosted VoIP. ISUM 2018 - Ninth International Supercomputing Conference in Mexico. Mérida, Yucatán, México. March 2018.
A. Tchernykh, M. Babenko, N. Chervyakov, V. Miranda-López, J.M. Cortés-Mendoza, Z. Du, P. OA Navaux, and A. Avetisyan. Analysis of Secured Distributed Cloud Data Storage Based on Multilevel RNS. ElConRus 2018 - IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering. St. Petersburg, Russia. January 2018, pp. 382-386. DOI: 10.1109/EIConRus.2018.8317112.
J.M. Cortés-Mendoza, A. Tchernykh, G. Radchenko, and A. Yu Drozdov. RoC Prediction for Bi-Objective Cost-QoS Optimization of Cloud VoIP Call Allocations. En&T 2017 - IV IEEE International Conference on Engineering & Telecommunications, MIPT, Moscow, Russia. November 2017, pp. 119-123. DOI: 10.1109/ICEnT.2017.32.
V. Miranda-López, A. Tchernykh, J.M. Cortés-Mendoza, M. Babenko, G. Radchenko, S. Nesmachnow, and Z. Du. Experimental Analysis of Secret Sharing Schemes for Cloud Storage Based on RNS. CARLA 2017 - Latin American Conference on High Performance Computing. Buenos Aires, Argentina. September 2017, pp. 370–383. DOI: 10.1007/978-3-319-73353-1_26.
A. Tchernykh, M. Babenko, N. Chervyakov, J.M. Cortés-Mendoza, N. Kucherov, V. Miranda-López, M. Deryabin, I. Dvoryaninova, and G. Radchenko. Towards Mitigating Uncertainty of Data Security Breaches and Collusion in Cloud Computing. UCC 2017 - 1st International Workshop on Uncertainty in Cloud Computing, in conjunction with 28th International Conference on Database and Expert Systems Applications (DEXA’17). Lyon, France. August 2017, pp. 137-141. DOI: 10.1109/DEXA.2017.44.
J.M. Cortés-Mendoza, A. Tchernykh, A. Feoktistov, I. Bychkov, and L. Didelot. Load-Aware Strategies for Cloud-based VoIP Optimization with VM Startup Prediction. PDCO 2017 - 7th IEEE Workshop on Parallel/Distributed Computing and Optimization. Orlando, Florida, USA. May 2017, pp. 472-481 . DOI: 10.1109/IPDPSW.2017.73.
A. Tchernykh, M. Babenko, N. Chervyakov, V. Miranda-López, J.M. Cortés-Mendoza, O. Dorofeeva, and Z. Du. Experimental Analysis of Secured Distributed Cloud Data Storage. ECBA 2017 - 23rd International Conference on “Engineering & Technology, Computer, Basic & Applied Sciences”, Shanghai, China. January 2017.
J.M. Cortés-Mendoza, A. Tchernykh, A. Yu. Drozdov, and L. Didelot. Robust Cloud VoIP Scheduling under VMs Startup Time Delay Uncetainty. CloudAM 2016 - Fifth International Workshop on Clouds and (eScience) Applications Management. Shanghai, China. December 2016. DOI: 10.1145/2996890.3007865.
J.M. Cortés-Mendoza, A. Tchernykh, A. Yu. Drozdov, and L. Didelot. Cloud based VoIP Service Optimization with VM Startup Time Delay. ISUM 2016 - Seventh International Supercomputing Conference in Mexico. Puebla, Puebla, México. April 2016.
Fermin A. Armenta-Cano, Andrei Tchernykh, Jorge M. Cortés-Mendoza, and Anastasia Drozdova. Energy Consumption Model for Scheduling Applications with Resource Contention. ISUM 2016 - Seventh International Supercomputing Conference in Mexico. Puebla, Puebla, México. April 2016.
A.M. Simionovici, A.A. Tantar, P. Bouvry, A. Tchernykh, J.M. Cortés-Mendoza, and L. Didelot. VoIP Traffic Modelling using Gaussian Mixture Models, Gaussian Processes and Interactive Particle Algorithms. CCSNA’15 - Fourth IEEE International Workshop on Cloud Computing Systems, Networks, and Applications 2015. San Diego, California, USA. December 2015, pp. 1-6. DOI: 10.1109/GLOCOMW.2015.7414113.
J.M. Cortés-Mendoza, A. Tchernykh, A. Yu. Drozdov, P. Bouvry, A.M. Simionovici, and A. Avetisyan. Distributed Adaptive VoIP Load Balancing in Hybrid Clouds. NC&SC’2015 - Network Computing and Supercomputing workshop. In conjunction with RuSCDays'15 - The Russian Supercomputing Days. Moscow, Russia. September 2015, pp. 676-686. Edited by: Vladimir Voevodin, Sergey Sobolev. CEUR-WS: Vol-1482, ISSN: 16130073.
F.A. Armenta-Cano, A. Tchernykh, J.M. Cortés-Mendoza, R. Yahyapour, A. Yu. Drozdov, P. Bouvry, D. Kliazovich, and A. Avetisyan. Heterogeneous Job Consolidation for Power Aware Scheduling with Quality of Service. NC&SC’2015 - Network Computing & Supercomputing workshop. In conjunction with RuSCDays'15 - The Russian Supercomputing Days. Moscow, Russia. September 2015, pp. 687-697. Edited by: Vladimir Voevodin, Sergey Sobolev. CEUR-WS: Vol-1482, ISSN: 16130073.
A. Tchernykh, J.M. Cortés-Mendoza, J. Pecero, P. Bouvry, and D. Kliazovich. Adaptive Energy Efficient Distributed VoIP Load Balancing in Federated Cloud Infrastructure. Cloudnet 2014 - International conference on cloud networking. Luxembourg, Luxembourg. October 2014, pp. 27-32. DOI: 10.1109/CloudNet.2014.6968964.
J.M. Cortés-Mendoza, A. Tchernykh, J. Pecero, P. Bouvry, and L. Cruz-Reyes. Distributed VoIP Load Balancing in Cloud Computing. ISUM 2014 - Fifth International Supercomputing Conference in Mexico. Ensenada, Baja California, México. March 2014.
J.M. Cortés-Mendoza and A. Tchernykh. Generalized Extremal Optimization for parallel job scheduling in two levels hierarchical Grid systems. ISUM 2012 - Third International Supercomputing Conference in Mexico. Guanajuato, Guanajuato, México. March 2012.
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