P. Picazo-Martínez, C. Barroso-Fernández, A. Calvillo-Fernandez, M. Groshev, C. J. Bernardos, A. de la Oliva, and A. Mourad, “802.11bf Multiband Passive Sensing: Reusing Wi-Fi Signaling for Sensing,” IEEE Internet of Things Journal, vol. 13, no. 6, pp. 10547–10563, 2026, doi: 10.1109/JIOT.2026.3656659. Read More »
A. Zahir, M. Groshev, C. J. Bernardos, and A. de la Oliva, “Blockchain-Driven Federation for Distributed Edge Systems: Design and Experimental Validation,” IEEE Network, early access, pp. 1–9, 2026, doi: 10.1109/MNET.2026.3668864. Read More »
H. Grosjean et al., “Structure–Activity Relationships Can Be Directly Extracted From High-Throughput Crystallographic Evaluation of Fragment Elaborations in Crude Reaction Mixtures,” Chemical Science, vol. 17, no. 9, pp. 4571–4593, 2026, doi: 10.1039/d5sc04919a. Read More »
J. Segura, R. Sanchez-Garcia, S. Bittrich, Y. Rose, S. K. Burley, and J. M. Duarte, “Multi-Scale Structural Similarity Embedding Search Across Entire Proteomes,” Bioinformatics, vol. 42, no. 3, Art. no. btag058, Feb. 2026, doi: 10.1093/bioinformatics/btag058. Read More »
A. V. Florea, R. Sánchez-García, J. A. Gómez-Pedrero, Á. Sierra, J. Alonso, and J. Vargas, “A Curated Dataset for cryo-EM Map Post-Processing,” Scientific Data, July 2026, doi: 10.1038/s41597-026-07949-y. Read More »
A. Calvillo-Fernandez, M. Groshev, and C. J. Bernardos, “Towards Goal-Oriented Semantic Orchestration for Resource-Aware Robotic Function Offloading,” in Proc. 11th International Conference on Control, Decision and Information Technologies (CoDIT), Split, Croatia, 2025, pp. 2214–2219, doi: 10.1109/CoDIT66093.2025.11321721. Read More »
A. González Bermúdez, M. Farreras, M. Groshev, J. A. Trujillo, I. de la Bandera, and R. Barco, “Graph Neural Networks for Open Radio Access Network Mobility Management: A Link Prediction Approach,” IEEE Vehicular Technology Magazine, vol. 20, no. 4, pp. 66–74, 2025, doi: 10.1109/MVT.2025.3623286. Read More »
R. Sanchez-Garcia et al., “Supervised Deep Learning for Efficient Cryo-EM Image Alignment in Drug Discovery With cryoPARES,” Mar. 2025, doi: 10.1101/2025.03.04.641536. Read More »
A. Mendez-Perez et al., “Unraveling the Power of NAP-CNB’s Machine Learning-Enhanced Tumor Neoantigen Prediction,” eLife, vol. 13, Art. no. RP95010, Mar. 2025, doi: 10.7554/elife.95010. Read More »
Branco, Pedro, et al. “Black-box non-interactive zero knowledge from vector trapdoor hash.” Annual International Conference on the Theory and Applications of Cryptographic Techniques. Cham: Springer Nature Switzerland, 2025. Read More »
Aydeniz, Ayhan Alp, et al. “Safe Entropic Agents under Team Constraints.” Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems. 2025. Read More »
Shah, Pranav NM, Ruben Sanchez-Garcia, and David I. Stuart. “TomoCPT: a generalizable model for 3D particle detection and localization in cryo-electron tomograms.” Biological Crystallography 81.2 (2025). Read More »
Alsaadi, Aymen, et al. “Adaptive Protein Design Protocols and Middleware.” 2025 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 2025. Read More »
Merzky, Andre, et al. “Scalable Runtime Architecture for Data-driven, Hybrid HPC and ML Workflow Applications.” arXiv preprint arXiv:2503.13343 (2025). Read More »
Sorzano, COS, Jimenez A, Mota J, Vilas JV, Maluenda D, Martinez M, Ramirez – Aportela E, et al. ‘Survey of the Analysis of Continuous Conformational Variability of Biological Macromolecules by Electron Microsc opy’. Acta Crystallographica Section F: Structural Biology Communications 75, no. 1 (2019): 19 – 32 Read More »
Groshev, Milan, Luca Zanzi, Carlos Delgado, Xinyu Li, Antonio de la Oliva, and Xavier Costa-Pérez. “Energy-Aware Joint Orchestration of 5G and Robots: Experimental Testbed and Field Validation.” IEEE Transactions on Network and Service Management, 2025, doi:10.1109/TNSM.2025.3555126. Read More »
Calvillo-Fernandez, Adrián, Tome Dimitrovski, Milan Groshev, Ananya Ganesh, Constantine Ayimba, and Antonio de la Oliva. “Attention to Virtualization: Making Network Digital Twins Aware of Network Slicing.” IEEE Network, vol. 39, no. 3, May 2025, pp. 134–139, doi:10.1109/MNET.2025.3552137. Read More »
Ferla, Matteo P., et al. “Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology.” Journal of Cheminformatics 17.1 (2025): 4. Read More »
M. Groshev, C. Guimarães, and A. de la Oliva, “Robotics Digital Twin for 6G,” in Digital Twins for 6G: Fundamental Theory, Technology and Applications, H. Ahmadi, T. Q. Duong, A. Nag, V. Sharma, B. Canberk, and O. A. Dobre, Eds. London, U.K.: Institution of Engineering and Technology, 2024, ch. 10, pp. 269–303, doi: 10.1049/PBTE109E_ch10. Read More »
P. González, M. Angoustures, A. Zahir, S. Barzegar, M. Ruiz, M. Groshev, V. Lefebvre, and L. Velasco, “Deployment of Genuine Multi-Agent Pipelines for Near-Real-Time Control of 6G Network Services,” in Proc. 24th International Conference on Transparent Optical Networks (ICTON), Bari, Italy, 2024, pp. 1–4, doi: 10.1109/ICTON62926.2024.10647825. Read More »
P. González, A. Zahir, C. Grasselli, A. Muñiz, M. Groshev, S. Barzegar, F. Callegati, D. Careglio, M. Ruiz, and L. Velasco, “Deployment of Secure Machine Learning Pipelines for Near-Real-Time Control of 6G Network Services,” in Optical Fiber Communication Conference (OFC) 2024, Technical Digest Series, San Diego, CA, USA: Optica Publishing Group, 2024, paper M3Z.8, doi: 10.1364/OFC.2024.M3Z.8. Read More »
A. Zahir, M. Groshev, K. Antevski, C. J. Bernardos, C. Ayimba, and A. de la Oliva, “Performance Evaluation of Private and Public Blockchains for Multi-Cloud Service Federation,” in Proc. 25th International Conference on Distributed Computing and Networking (ICDCN ’24), Chennai, India, 2024, pp. 217–221, doi: 10.1145/3631461.3631559. Read More »
P. Picazo-Martínez, C. Barroso-Fernández, J. Martín-Pérez, M. Groshev, and A. de la Oliva, “IEEE 802.11az Indoor Positioning with mmWave,” IEEE Communications Magazine, vol. 62, no. 10, pp. 126–131, 2024, doi: 10.1109/MCOM.001.2300454. Read More »
Gerritz, Evan, Luciano Dyballa, and Steven W. Zucker. “Zero-shot generalization across architectures for visual classification.” arXiv preprint arXiv:2402.14095 (2024). Read More »
S. Wills et al., “Expanding the Scope of a Catalogue Search to Bioisosteric Fragment Merges Using a Graph Database Approach,” Aug. 2024, doi: 10.1101/2024.08.02.606367. Read More »
R. Sanchez-Garcia, M. Saur, J. Vargas, C. Poelking, and C. M. Deane, “CESPED: A Benchmark for Supervised Particle Pose Estimation in cryo-EM,” Physical Review Research, vol. 6, no. 2, Art. no. 023245, June 2024, doi: 10.1103/physrevresearch.6.023245. Read More »
Marzari, Luca, et al. “Enumerating safe regions in deep neural networks with provable probabilistic guarantees.” Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 38. No. 19. 2024. Read More »
Aydeniz, Ayhan Alp, et al. “Entropy Seeking Constrained Multiagent Reinforcement Learning.” Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. 2024. Read More »
Sanchez-Garcia, Ruben, et al. “Cryo-EM map anisotropy can be attenuated by map post-processing and a new method for its estimation.” International Journal of Molecular Sciences 25.7 (2024): 3959. Read More »
Sanchez-Garcia, Ruben, et al. “CESPED: A benchmark for supervised particle pose estimation in cryo-EM.” Physical Review Research 6.2 (2024): 023245. Read More »
Dyballa, Luciano, et al. “Population encoding of stimulus features along the visual hierarchy.” Proceedings of the National Academy of Sciences 121.4 (2024): e2317773121. Read More »
Prohaska, Vera, and Eduardo Castelló Ferrer. “Spice: Smart projection interface for cooking enhancement.” arXiv preprint arXiv:2412.03551 (2024). Read More »
Dyballa, L., et al. (2024). Learning dynamic representations of the functional connectome in neurobiological networks. In International Conference on Learning Representations (Vol. 2024, pp. 36957-36972). Read More »
K. Gillani, J. Martín-Pérez, M. Groshev, A. de la Oliva, and R. Gazda, “Don’t Let Me Down! Offloading Robot VFs Up to the Cloud,” in Proc. IEEE 9th International Conference on Network Softwarization (NetSoft), Madrid, Spain, 2023, pp. 232–236, doi: 10.1109/NetSoft57336.2023.10175499. Read More »
P. Picazo, M. Groshev, A. Blanco, C. Fiandrino, A. de la Oliva, and J. Widmer, “waveSLAM: Empowering Accurate Indoor Mapping Using Off-the-Shelf Millimeter-Wave Self-Sensing,” in Proc. IEEE 98th Vehicular Technology Conference (VTC2023-Fall), Hong Kong, 2023, pp. 1–7, doi: 10.1109/VTC2023-Fall60731.2023.10333840. Read More »
E. Fernández-Giménez et al., “A New Algorithm for Particle Weighted Subtraction to Decrease Signals From Unwanted Components in Single Particle Analysis,” Journal of Structural Biology, vol. 215, no. 4, p. 108024, Dec. 2023, doi: 10.1016/j.jsb.2023.108024. Read More »
Wills, Stephanie, et al. “Fragment merging using a graph database samples different catalogue space than similarity search.” Journal of Chemical Information and Modeling 63.11 (2023): 3423-3437. Read More »
Baldoni, Gabriele, Luca Cominardi, Milan Groshev, Antonio de la Oliva, and Antonio Corsaro. “Managing the Far-Edge: Are Today’s Centralized Solutions a Good Fit?” IEEE Consumer Electronics Magazine, vol. 12, no. 3, May 2023, pp. 51–61, doi:10.1109/MCE.2021.3082503. Read More »
Dyballa, Luciano, and Steven W. Zucker. “IAN: Iterated Adaptive Neighborhoods for manifold learning and dimensionality estimation.” Neural Computation 35.3 (2023): 453-524. Read More »
Groshev, Milan, et al. “Edge robotics: Are we ready? An experimental evaluation of current vision and future directions.” Digital Communications and Networks 9.1 (2023): 166-174. Read More »
M. Groshev, J. Sacido, and J. Martín-Pérez, “Demo: FoReCo – A Forecast-Based Recovery Mechanism for Real-Time Remote Control of Robotic Manipulators,” in Proc. SIGCOMM ’22 Poster and Demo Sessions, Amsterdam, Netherlands, 2022, pp. 7–9, doi: 10.1145/3546037.3546047. Read More »
F. Mungari, M. Groshev, and C. F. Chiasserini, “Resource Requirements of an Edge-based Digital Twin Service: An Experimental Study,” Virtual Reality & Intelligent Hardware, vol. 4, no. 6, pp. 506–520, 2022, doi: 10.1016/j.vrih.2022.05.005. Read More »
M. Groshev, J. Martín-Pérez, C. Guimarães, A. de la Oliva, and C. J. Bernardos, “FoReCo: A Forecast-Based Recovery Mechanism for Real-Time Remote Control of Robotic Manipulators,” IEEE Transactions on Network and Service Management, vol. 19, no. 3, pp. 2573–2586, 2022, doi: 10.1109/TNSM.2022.3173436. Read More »
R. Sanchez-Garcia, Macias, J.R, Sorzano, C.O.S, Carazo, J.M, and J. Segura, “BIPSPI+: Mining Type-Specific Datasets of Protein Complexes to Improve Protein Binding Site Prediction,” Computation Resources for Molecular Biology, vol. 434, no. 11, p. 167556, June 2022, doi: 10.1016/j.jmb.2022.167556. Read More »
C. O. S. Sorzano et al., “On Bias, Variance, Overfitting, Gold Standard and Consensus in Single-Particle Analysis by Cryo-Electron Microscopy,” Acta Crystallographica Section D Structural Biology, vol. 78, no. 4, pp. 410–423, Mar. 2022, doi: 10.1107/s2059798322001978. Read More »
Martín-Pérez, Jorge, Fabrizio Malandrino, Carla-Fabiana Chiasserini, Milan Groshev, and Carlos J. Bernardos. “KPI Guarantees in Network Slicing.” IEEE/ACM Transactions on Networking, vol. 30, no. 2, Apr. 2022, pp. 655–668, doi:10.1109/TNET.2021.3120318. Read More »
Zuccotto, M., Piccinelli, M., Castellini, A., Marchesini, E., & Farinelli, A. (2022). Learning state-variable relationships in POMCP: A framework for mobile robots. Frontiers in Robotics and Al, 9, 2296-9144. Read More »
Groshev, Milan, Carlos Guimarães, Jorge Martín-Pérez, and Antonio de la Oliva. “Toward Intelligent Cyber-Physical Systems: Digital Twin Meets Artificial Intelligence.” IEEE Communications Magazine, vol. 59, no. 8, Aug. 2021, pp. 14–20, doi:10.1109/MCOM.001.2001237. Read More »
Sanchez-Garcia, Ruben, et al. “DeepEMhancer: a deep learning solution for cryo-EM volume post-processing.” Communications biology 4.1 (2021): 874. Read More »
Costa, Bruno, et al. “Randomized oblivious transfer for secure multiparty computation in the quantum setting.” Entropy 23.8 (2021): 1001. Read More »
Groshev, Milan, Carlos Guimarães, Antonio de la Oliva, and Robert Gazda. “Dissecting the Impact of Information and Communication Technologies on Digital Twins as a Service.” IEEE Access, vol. 9, 2021, pp. 102862–102876, doi:10.1109/ACCESS.2021.3098109. Read More »
Sanchez – Garcia R, Segura J, Maluenda D, Sorzano COS, and Carazo JM. ‘MicrographCleaner: A Python Package for Cryo – EM Micrograph Cleaning Using Deep Learning’. Journal of Structural Biology 210, no. 3 (2020): 10749 8. Read More »
Segura J, Sanchez – Garcia R, Sorzano COS, and Carazo JM. ‘3DBIONOTES v3.0: Crossing Molecular and Structural Biology Data with Genomic Variations’. Bioinformatics 35, no. 18 (2019): 3512 – 13. Read More »
Sorzano, COS, Jimenez A, Mota J, Vilas JV, Maluenda D, Martinez M, Ramirez – Aportela E, et al. ‘Survey of the Analysis of Continuous Conformational Variability of Biological Macromolecules by Electron Microsc opy’. Acta Crystallographica Section F: Structural Biology Communications 75, no. 1 (2019): 19 – 32 Read More »
Jimenez A, Jonic S, Majtner T, Oton J, Vilas JV, Maluenda D, Mota J, et al. ‘Validation of Electron Microscopy Initial Models via Small Angle X – Ray Scattering Cur ves’. Bioinformatics 35, no. 14 (2019): 2427 – 33. Read More »
Sanchez – Garcia R, Sorzano COS., Carazo J M., & Segura, J (2019). BIPSPI: a method for the predicti on of partner – specific protein – protein interfaces. Bioinformatics , 35 , no. 3 (2019): 470 – 477. Read More »
Sanchez-Garcia, Ruben, et al. “BIPSPI: a method for the prediction of partner-specific protein–protein interfaces.” Bioinformatics 35.3 (2019): 470-477. Read More »
Sorzano COS, Vargas J, Vilas JL, Jimenez – Moreno A, Mot a J, Majtner T, Maluenda D, et al. ‘Swarm Optimization as a Consensus Technique for Electron Microscopy Initial Volume’. Appl. Anal. Optim 2 (2018): 299 – 313. Read More »
Sanchez – Garcia R, Segura J, Maluenda D, Carazo JM, and Sorzano COS. ‘Deep Consensus, a Deep Learning – Based Approach for Particle Pruning in Cryo – Electron Microscopy’. IUCrJ 5, no. 6 (2018): 854 – 65. Read More »
Bertram, J., Dyballa, L., Keller, T. A., Kinger, S., & Zucker, S. W. (2026). Decoding Alignment without Encoding Alignment: A critique of similarity analysis in neuroscience. arXiv:2605.05907. Read More »
Kinger, S., Dyballa, L., & Zucker, S. W. (2026). Bracketing Uncertainty in Clustering Under the Manifold Hypothesis. arXiv:2609.17892. Read More »
Kinger, S., Bertram, J., Dyballa, L., Keller, T. A., & Zucker, S. W. (2026) Reading Positional Coupling in Transformers with Diffusion Scores. In Advances in Neural Information Processing Systems, vol. 39 Read More »
H. Grosjean et al., “Structure–Activity Relationships Can Be Directly Extracted From High-Throughput Crystallographic Evaluation of Fragment Elaborations in Crude Reaction Mixtures,” Chemical Science, vol. 17, no. 9, pp. 4571–4593, 2026, doi: 10.1039/d5sc04919a. Read More »
J. Segura, R. Sanchez-Garcia, S. Bittrich, Y. Rose, S. K. Burley, and J. M. Duarte, “Multi-Scale Structural Similarity Embedding Search Across Entire Proteomes,” Bioinformatics, vol. 42, no. 3, Art. no. btag058, Feb. 2026, doi: 10.1093/bioinformatics/btag058. Read More »
A. V. Florea, R. Sánchez-García, J. A. Gómez-Pedrero, Á. Sierra, J. Alonso, and J. Vargas, “A Curated Dataset for cryo-EM Map Post-Processing,” Scientific Data, July 2026, doi: 10.1038/s41597-026-07949-y. Read More »
Bertram, J., Dyballa, L., Keller, T. A., Kinger, S., & Zucker, S. W. (2025). Manifolds and Modules: How Function Develops in a Neural Foundation Model. arXiv:2512.07869. Read More »
R. Sanchez-Garcia et al., “Supervised Deep Learning for Efficient Cryo-EM Image Alignment in Drug Discovery With cryoPARES,” Mar. 2025, doi: 10.1101/2025.03.04.641536. Read More »
A. Mendez-Perez et al., “Unraveling the Power of NAP-CNB’s Machine Learning-Enhanced Tumor Neoantigen Prediction,” eLife, vol. 13, Art. no. RP95010, Mar. 2025, doi: 10.7554/elife.95010. Read More »
Aydeniz, Ayhan Alp, et al. “Safe Entropic Agents under Team Constraints.” Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems. 2025. Read More »
Shah, Pranav NM, Ruben Sanchez-Garcia, and David I. Stuart. “TomoCPT: a generalizable model for 3D particle detection and localization in cryo-electron tomograms.” Biological Crystallography 81.2 (2025). Read More »
Merzky, Andre, et al. “Scalable Runtime Architecture for Data-driven, Hybrid HPC and ML Workflow Applications.” arXiv preprint arXiv:2503.13343 (2025). Read More »
Lin, Y., Kopp, R. E., Reedy, A., Turilli, M., Jha, S., and Ashe, E. L.: PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data, Geosci. Model Dev., 18, 2609–2637, https://doi.org/10.5194/gmd-18-2609-2025, 2025. Read More »
Dyballa, L., Gerritz, E., & Zucker, S. W. (2024). A separability-based approach to quantifying generalization: which layer is best?. arXiv:2405.01524. Read More »
Gerritz, Evan, Luciano Dyballa, and Steven W. Zucker. “Zero-shot generalization across architectures for visual classification.” arXiv preprint arXiv:2402.14095 (2024). Read More »
S. Wills et al., “Expanding the Scope of a Catalogue Search to Bioisosteric Fragment Merges Using a Graph Database Approach,” Aug. 2024, doi: 10.1101/2024.08.02.606367. Read More »
R. Sanchez-Garcia, M. Saur, J. Vargas, C. Poelking, and C. M. Deane, “CESPED: A Benchmark for Supervised Particle Pose Estimation in cryo-EM,” Physical Review Research, vol. 6, no. 2, Art. no. 023245, June 2024, doi: 10.1103/physrevresearch.6.023245. Read More »
Aydeniz, Ayhan Alp, et al. “Entropy Seeking Constrained Multiagent Reinforcement Learning.” Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. 2024. Read More »
Alsaadi, Aymen, Shantenu Jha, and Matteo Turilli. “Hydra: Brokering Cloud and HPC Resources to Support the Execution of Heterogeneous Workloads at Scale.” Proceedings of the 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures. 2024. Read More »
Sanchez-Garcia, Ruben, et al. “CESPED: A benchmark for supervised particle pose estimation in cryo-EM.” Physical Review Research 6.2 (2024): 023245. Read More »
Dyballa, Luciano, et al. “Population encoding of stimulus features along the visual hierarchy.” Proceedings of the National Academy of Sciences 121.4 (2024): e2317773121. Read More »
Dyballa, L., et al. (2024). Learning dynamic representations of the functional connectome in neurobiological networks. In International Conference on Learning Representations (Vol. 2024, pp. 36957-36972). Read More »
E. Fernández-Giménez et al., “A New Algorithm for Particle Weighted Subtraction to Decrease Signals From Unwanted Components in Single Particle Analysis,” Journal of Structural Biology, vol. 215, no. 4, p. 108024, Dec. 2023, doi: 10.1016/j.jsb.2023.108024. Read More »
Dyballa, Luciano, and Steven W. Zucker. “IAN: Iterated Adaptive Neighborhoods for manifold learning and dimensionality estimation.” Neural Computation 35.3 (2023): 453-524. Read More »
Groshev, Milan, et al. “Edge robotics: Are we ready? An experimental evaluation of current vision and future directions.” Digital Communications and Networks 9.1 (2023): 166-174. Read More »
P. Picazo-Martínez, C. Barroso-Fernández, A. Calvillo-Fernandez, M. Groshev, C. J. Bernardos, A. de la Oliva, and A. Mourad, “802.11bf Multiband Passive Sensing: Reusing Wi-Fi Signaling for Sensing,” IEEE Internet of Things Journal, vol. 13, no. 6, pp. 10547–10563, 2026, doi: 10.1109/JIOT.2026.3656659. Read More »
A. Zahir, M. Groshev, C. J. Bernardos, and A. de la Oliva, “Blockchain-Driven Federation for Distributed Edge Systems: Design and Experimental Validation,” IEEE Network, early access, pp. 1–9, 2026, doi: 10.1109/MNET.2026.3668864. Read More »
Aydeniz, Ayhan Alp, et al. “Safe Entropic Agents under Team Constraints.” Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems. 2025. Read More »
de la Jara, Javier Jimenez, et al. “HADAD: Hexagonal A-Star with Differential Algorithm Designed for weather routing.” Ocean Engineering 319 (2025): 120050. Read More »
Groshev, Milan, Luca Zanzi, Carlos Delgado, Xinyu Li, Antonio de la Oliva, and Xavier Costa-Pérez. “Energy-Aware Joint Orchestration of 5G and Robots: Experimental Testbed and Field Validation.” IEEE Transactions on Network and Service Management, 2025, doi:10.1109/TNSM.2025.3555126. Read More »
Calvillo-Fernandez, Adrián, Tome Dimitrovski, Milan Groshev, Ananya Ganesh, Constantine Ayimba, and Antonio de la Oliva. “Attention to Virtualization: Making Network Digital Twins Aware of Network Slicing.” IEEE Network, vol. 39, no. 3, May 2025, pp. 134–139, doi:10.1109/MNET.2025.3552137. Read More »
M. Groshev, C. Guimarães, and A. de la Oliva, “Robotics Digital Twin for 6G,” in Digital Twins for 6G: Fundamental Theory, Technology and Applications, H. Ahmadi, T. Q. Duong, A. Nag, V. Sharma, B. Canberk, and O. A. Dobre, Eds. London, U.K.: Institution of Engineering and Technology, 2024, ch. 10, pp. 269–303, doi: 10.1049/PBTE109E_ch10. Read More »
Branco, Pedro, et al. “Roted: Random oblivious transfer for embedded devices.” IACR Transactions on Cryptographic Hardware and Embedded Systems (2021): 215-238. Read More »
K. Gillani, J. Martín-Pérez, M. Groshev, A. de la Oliva, and R. Gazda, “Don’t Let Me Down! Offloading Robot VFs Up to the Cloud,” in Proc. IEEE 9th International Conference on Network Softwarization (NetSoft), Madrid, Spain, 2023, pp. 232–236, doi: 10.1109/NetSoft57336.2023.10175499. Read More »
P. Picazo, M. Groshev, A. Blanco, C. Fiandrino, A. de la Oliva, and J. Widmer, “waveSLAM: Empowering Accurate Indoor Mapping Using Off-the-Shelf Millimeter-Wave Self-Sensing,” in Proc. IEEE 98th Vehicular Technology Conference (VTC2023-Fall), Hong Kong, 2023, pp. 1–7, doi: 10.1109/VTC2023-Fall60731.2023.10333840. Read More »
Coretti-Sanchez, N., et al. “Urban Mobility Swarms: Towards a Decentralized Autonomous Bicycle-Sharing System.” 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2023. Read More »
Castelló Ferrer, E., Berman, I., Kapitonov, A., Manaenko, V., Chernyaev, M., & Tarasov, P. (2023). “Gaka-chu: a self-employed autonomous robot artist”. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 11583-11589. Read More »
Ferrer, Eduardo Castelló. “If blockchain is the solution, robot security is the problem.” Frontiers in Blockchain 6 (2023): 1181820. Read More »
Groshev, Milan, et al. “Edge robotics: Are we ready? An experimental evaluation of current vision and future directions.” Digital Communications and Networks 9.1 (2023): 166-174. Read More »
M. Groshev, J. Sacido, and J. Martín-Pérez, “Demo: FoReCo – A Forecast-Based Recovery Mechanism for Real-Time Remote Control of Robotic Manipulators,” in Proc. SIGCOMM ’22 Poster and Demo Sessions, Amsterdam, Netherlands, 2022, pp. 7–9, doi: 10.1145/3546037.3546047. Read More »
F. Mungari, M. Groshev, and C. F. Chiasserini, “Resource Requirements of an Edge-based Digital Twin Service: An Experimental Study,” Virtual Reality & Intelligent Hardware, vol. 4, no. 6, pp. 506–520, 2022, doi: 10.1016/j.vrih.2022.05.005. Read More »
M. Groshev, J. Martín-Pérez, C. Guimarães, A. de la Oliva, and C. J. Bernardos, “FoReCo: A Forecast-Based Recovery Mechanism for Real-Time Remote Control of Robotic Manipulators,” IEEE Transactions on Network and Service Management, vol. 19, no. 3, pp. 2573–2586, 2022, doi: 10.1109/TNSM.2022.3173436. Read More »
Castelló Ferrer, E., Jiménez, E., Lopez-Presa, J. L., & Martín-Rueda, J. (2022). “Following Leaders in Byzantine Multi-Robot Systems by Using Blockchain Technology”. IEEE Transactions on Robotics. Read More »
Martín-Pérez, Jorge, Fabrizio Malandrino, Carla-Fabiana Chiasserini, Milan Groshev, and Carlos J. Bernardos. “KPI Guarantees in Network Slicing.” IEEE/ACM Transactions on Networking, vol. 30, no. 2, Apr. 2022, pp. 655–668, doi:10.1109/TNET.2021.3120318. Read More »
Groshev, Milan, Carlos Guimarães, Jorge Martín-Pérez, and Antonio de la Oliva. “Toward Intelligent Cyber-Physical Systems: Digital Twin Meets Artificial Intelligence.” IEEE Communications Magazine, vol. 59, no. 8, Aug. 2021, pp. 14–20, doi:10.1109/MCOM.001.2001237. Read More »
Castelló Ferrer, E., Hardjono, T., Pentland, A. S., & Dorigo, M. (2021). “Secure and secret cooperation in robotic swarms”. Science Robotics, 4(29), eaaw3739. Read More »
Branco, Pedro. “A post-quantum UC-commitment scheme in the global random oracle model from code-based assumptions.” Cryptology ePrint Archive (2019). Read More »
Branco, P., Mateus, P., Salema, C., Souto, A. Using Low – Density Parity – Check codes to improve the McEliece cryptosystem. Information Sciences, Volume 510, 2020, Pages 243 – 255, ISSN 0020 – 0 255 Read More »
Jimenez A, Jonic S, Majtner T, Oton J, Vilas JV, Maluenda D, Mota J, et al. ‘Validation of Electron Microscopy Initial Models via Small Angle X – Ray Scattering Cur ves’. Bioinformatics 35, no. 14 (2019): 2427 – 33. Read More »
Castelló Ferrer, Eduardo. “The blockchain: a new framework for robotic swarm systems.” Proceedings of the Future Technologies Conference (FTC) 2018: Volume 2. Springer International Publishing, 2019. Read More »
Strobel, Volker, Eduardo Castelló Ferrer, and Marco Dorigo. “Managing byzantine robots via blockchain technology in a swarm robotics collective decision making scenario.” (2018). Read More »
Sorzano COS, Vargas J, Vilas JL, Jimenez – Moreno A, Mot a J, Majtner T, Maluenda D, et al. ‘Swarm Optimization as a Consensus Technique for Electron Microscopy Initial Volume’. Appl. Anal. Optim 2 (2018): 299 – 313. Read More »
Branco P., Lai R.W.F., Maitra M., Malavolta G., Rahimi A., Woo I.K.Y. (2025) “Traitor Tracing Without Trusted Authority from Registered Functional Encryption.” In Advances in Cryptology – ASIACRYPT 2024, LNCS 15486, Springer, Singapore. Read More »
Branco, Pedro, et al. “Black-box non-interactive zero knowledge from vector trapdoor hash.” Annual International Conference on the Theory and Applications of Cryptographic Techniques. Cham: Springer Nature Switzerland, 2025. Read More »
Calvillo-Fernandez, Adrián, Tome Dimitrovski, Milan Groshev, Ananya Ganesh, Constantine Ayimba, and Antonio de la Oliva. “Attention to Virtualization: Making Network Digital Twins Aware of Network Slicing.” IEEE Network, vol. 39, no. 3, May 2025, pp. 134–139, doi:10.1109/MNET.2025.3552137. Read More »
Marzari, Luca, et al. “Enumerating safe regions in deep neural networks with provable probabilistic guarantees.” Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 38. No. 19. 2024. Read More »
Branco, Pedro, Nico Döttling, and Akshayaram Srinivasan. “Two-Round Maliciously-Secure Oblivious Transfer with Optimal Rate.” Annual International Conference on the Theory and Applications of Cryptographic Techniques. Cham: Springer Nature Switzerland, 2024. Read More »
Yokelson, Dewi, et al. “Enabling performance observability for heterogeneous hpc workflows with SOMA.” Proceedings of the 53rd International Conference on Parallel Processing. 2024. Read More »
Alsaadi, Aymen, Shantenu Jha, and Matteo Turilli. “Hydra: Brokering Cloud and HPC Resources to Support the Execution of Heterogeneous Workloads at Scale.” Proceedings of the 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures. 2024. Read More »
Branco P., Döttling N., Lysyanskaya A., Handschuh H. (2023) “A Framework for Statistically Sender-Private OT with Optimal Rate.” In Advances in Cryptology – CRYPTO 2023, LNCS 14081, Springer, Cham. Tags: Security & Privacy, Scientific Computing Read More »
Martín-Pérez, Jorge, Fabrizio Malandrino, Carla-Fabiana Chiasserini, Milan Groshev, and Carlos J. Bernardos. “KPI Guarantees in Network Slicing.” IEEE/ACM Transactions on Networking, vol. 30, no. 2, Apr. 2022, pp. 655–668, doi:10.1109/TNET.2021.3120318. Read More »
Costa, Bruno, Pedro Branco, Manuel Goulão, Mariano Lemus, and Paulo Mateus. “Randomized Oblivious Transfer for Secure Multiparty Computation in the Quantum Setting.” Entropy, vol. 23, no. 8, 2021, p. 1001. Read More »
H. Grosjean et al., “Structure–Activity Relationships Can Be Directly Extracted From High-Throughput Crystallographic Evaluation of Fragment Elaborations in Crude Reaction Mixtures,” Chemical Science, vol. 17, no. 9, pp. 4571–4593, 2026, doi: 10.1039/d5sc04919a. Read More »
J. Segura, R. Sanchez-Garcia, S. Bittrich, Y. Rose, S. K. Burley, and J. M. Duarte, “Multi-Scale Structural Similarity Embedding Search Across Entire Proteomes,” Bioinformatics, vol. 42, no. 3, Art. no. btag058, Feb. 2026, doi: 10.1093/bioinformatics/btag058. Read More »
A. V. Florea, R. Sánchez-García, J. A. Gómez-Pedrero, Á. Sierra, J. Alonso, and J. Vargas, “A Curated Dataset for cryo-EM Map Post-Processing,” Scientific Data, July 2026, doi: 10.1038/s41597-026-07949-y. Read More »
Krausch, N., Doff-Sotta, M., Cannon, M., Neubauer, P., & Bournazou, M.N.C. (2025). Deep learning adaptive model predictive control of fed-batch cultivations, Computers & Chemical Engineering, Vol. 203. Read More »
Doff-Sotta, M., Cannon, M., & Bacic, M. (2025). Data-driven robust model predictive control of tiltwing vertical take-off and landing aircraft. Journal of Guidance, Control and Dynamics, 48(1), 203-211 Read More »
R. Sanchez-Garcia et al., “Supervised Deep Learning for Efficient Cryo-EM Image Alignment in Drug Discovery With cryoPARES,” Mar. 2025, doi: 10.1101/2025.03.04.641536. Read More »
A. Mendez-Perez et al., “Unraveling the Power of NAP-CNB’s Machine Learning-Enhanced Tumor Neoantigen Prediction,” eLife, vol. 13, Art. no. RP95010, Mar. 2025, doi: 10.7554/elife.95010. Read More »
Branco, Pedro, et al. “Black-box non-interactive zero knowledge from vector trapdoor hash.” Annual International Conference on the Theory and Applications of Cryptographic Techniques. Cham: Springer Nature Switzerland, 2025. Read More »
Shah, Pranav NM, Ruben Sanchez-Garcia, and David I. Stuart. “TomoCPT: a generalizable model for 3D particle detection and localization in cryo-electron tomograms.” Biological Crystallography 81.2 (2025). Read More »
Alsaadi, Aymen, et al. “Adaptive Protein Design Protocols and Middleware.” 2025 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 2025. Read More »
Merzky, Andre, et al. “Scalable Runtime Architecture for Data-driven, Hybrid HPC and ML Workflow Applications.” arXiv preprint arXiv:2503.13343 (2025). Read More »
de la Jara, Javier Jimenez, et al. “HADAD: Hexagonal A-Star with Differential Algorithm Designed for weather routing.” Ocean Engineering 319 (2025): 120050. Read More »
Groshev, Milan, Luca Zanzi, Carlos Delgado, Xinyu Li, Antonio de la Oliva, and Xavier Costa-Pérez. “Energy-Aware Joint Orchestration of 5G and Robots: Experimental Testbed and Field Validation.” IEEE Transactions on Network and Service Management, 2025, doi:10.1109/TNSM.2025.3555126. Read More »
Lin, Y., Kopp, R. E., Reedy, A., Turilli, M., Jha, S., and Ashe, E. L.: PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data, Geosci. Model Dev., 18, 2609–2637, https://doi.org/10.5194/gmd-18-2609-2025, 2025. Read More »
Calvillo-Fernandez, Adrián, Tome Dimitrovski, Milan Groshev, Ananya Ganesh, Constantine Ayimba, and Antonio de la Oliva. “Attention to Virtualization: Making Network Digital Twins Aware of Network Slicing.” IEEE Network, vol. 39, no. 3, May 2025, pp. 134–139, doi:10.1109/MNET.2025.3552137. Read More »
Buerger, J., Cannon, M., & Doff-Sotta, M. (2024). Safe learning in nonlinear model predictive control, In 2024 Proceedings of Machine Learning Research vol 242:603–614. Read More »
S. Wills et al., “Expanding the Scope of a Catalogue Search to Bioisosteric Fragment Merges Using a Graph Database Approach,” Aug. 2024, doi: 10.1101/2024.08.02.606367. Read More »
R. Sanchez-Garcia, M. Saur, J. Vargas, C. Poelking, and C. M. Deane, “CESPED: A Benchmark for Supervised Particle Pose Estimation in cryo-EM,” Physical Review Research, vol. 6, no. 2, Art. no. 023245, June 2024, doi: 10.1103/physrevresearch.6.023245. Read More »
Marzari, Luca, et al. “Enumerating safe regions in deep neural networks with provable probabilistic guarantees.” Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 38. No. 19. 2024. Read More »
Seijo, Francisco, et al. “Contrasting state land and fire use policies condition fire regime seasonality and size in two Central Spain forest landscapes.” Land Use Policy 147 (2024): 107338. Read More »
Branco, Pedro, Nico Döttling, and Akshayaram Srinivasan. “Two-Round Maliciously-Secure Oblivious Transfer with Optimal Rate.” Annual International Conference on the Theory and Applications of Cryptographic Techniques. Cham: Springer Nature Switzerland, 2024. Read More »
Yokelson, Dewi, et al. “Enabling performance observability for heterogeneous hpc workflows with SOMA.” Proceedings of the 53rd International Conference on Parallel Processing. 2024. Read More »
Alsaadi, Aymen, Shantenu Jha, and Matteo Turilli. “Hydra: Brokering Cloud and HPC Resources to Support the Execution of Heterogeneous Workloads at Scale.” Proceedings of the 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures. 2024. Read More »
Sanchez-Garcia, Ruben, et al. “CESPED: A benchmark for supervised particle pose estimation in cryo-EM.” Physical Review Research 6.2 (2024): 023245. Read More »
Prohaska, Vera, and Eduardo Castelló Ferrer. “Spice: Smart projection interface for cooking enhancement.” arXiv preprint arXiv:2412.03551 (2024). Read More »
E. Fernández-Giménez et al., “A New Algorithm for Particle Weighted Subtraction to Decrease Signals From Unwanted Components in Single Particle Analysis,” Journal of Structural Biology, vol. 215, no. 4, p. 108024, Dec. 2023, doi: 10.1016/j.jsb.2023.108024. Read More »
Baldoni, Gabriele, Luca Cominardi, Milan Groshev, Antonio de la Oliva, and Antonio Corsaro. “Managing the Far-Edge: Are Today’s Centralized Solutions a Good Fit?” IEEE Consumer Electronics Magazine, vol. 12, no. 3, May 2023, pp. 51–61, doi:10.1109/MCE.2021.3082503. Read More »
Branco P., Döttling N., Lysyanskaya A., Handschuh H. (2023) “A Framework for Statistically Sender-Private OT with Optimal Rate.” In Advances in Cryptology – CRYPTO 2023, LNCS 14081, Springer, Cham. Tags: Security & Privacy, Scientific Computing Read More »
R. Sanchez-Garcia, Macias, J.R, Sorzano, C.O.S, Carazo, J.M, and J. Segura, “BIPSPI+: Mining Type-Specific Datasets of Protein Complexes to Improve Protein Binding Site Prediction,” Computation Resources for Molecular Biology, vol. 434, no. 11, p. 167556, June 2022, doi: 10.1016/j.jmb.2022.167556. Read More »
C. O. S. Sorzano et al., “On Bias, Variance, Overfitting, Gold Standard and Consensus in Single-Particle Analysis by Cryo-Electron Microscopy,” Acta Crystallographica Section D Structural Biology, vol. 78, no. 4, pp. 410–423, Mar. 2022, doi: 10.1107/s2059798322001978. Read More »
Martín-Pérez, Jorge, Fabrizio Malandrino, Carla-Fabiana Chiasserini, Milan Groshev, and Carlos J. Bernardos. “KPI Guarantees in Network Slicing.” IEEE/ACM Transactions on Networking, vol. 30, no. 2, Apr. 2022, pp. 655–668, doi:10.1109/TNET.2021.3120318. Read More »
Groshev, Milan, Carlos Guimarães, Antonio de la Oliva, and Robert Gazda. “Dissecting the Impact of Information and Communication Technologies on Digital Twins as a Service.” IEEE Access, vol. 9, 2021, pp. 102862–102876, doi:10.1109/ACCESS.2021.3098109. Read More »