Publications

  • A. Salimi-Badr, “A data-driven implicit deep adaptive neuro-fuzzy inference system capable of manifold learning for function approximation.” Applied Soft Computing (2024): 111458.
  • A. Salimi-Badr, “UNFIS: A Novel Neuro-Fuzzy Inference System with Unstructured Fuzzy Rules.” Neurocomputing (2024): 127437.
  • M. H. Nasiri, S. H. M. Zonouzi and A. Salimi-Badr, “Enhancing Decisions of Goalkeeper and Kicker Players in the RoboCup 2D Simulation League through Behavioral Cloning,” 2024 20th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP), Babol, Iran, Islamic Republic of, 2024, pp. 1-6, doi: 10.1109/AISP61396.2024.10475295.
  • A. Rashnu, and A. Salimi-Badr. “Integrative Deep Learning Framework for Parkinson’s Disease Early Detection using Gait Cycle Data Measured by Wearable Sensors: A CNN-GRU-GNN Approach.” arXiv preprint arXiv:2404.15335 (2024).
  • A. Abdi, and A. Salimi-Badr, “ENF-S: An Evolutionary-Neuro-Fuzzy Multi-Objective Task Scheduler for Heterogeneous Multi-core Processors,” IEEE Transactions on Sustainable Computing, 2023. ( arXiv preprint is available at arXiv:2203:14717).
  • A. Parvizi and A. Salimi-Badr, “Generating Hand-Written Symbols With Trajectory Planning Using A Robotic Arm,” 2023 13th International Conference on Computer and Knowledge Engineering (ICCKE), Mashhad, Iran, Islamic Republic of, 2023, pp. 335-339, doi: 10.1109/ICCKE60553.2023.10326253.
  • M. Saadatinia, and A. Salimi-Badr. “An Explainable Deep Learning-Based Method For Schizophrenia Diagnosis Using Generative Data-Augmentation.” arXiv preprint arXiv:2310.16867 (2023).
  • A. Salimi-Badr, M. Hashemi, H. Saffari, “A type-2 neuro-fuzzy system with a novel learning method for Parkinson’s disease diagnosis,” Applied Intelligence, vol. 53, 2023.
  • A. Salimi-Badr, and M. Hashemi. “Early Parkinson’s Disease Diagnosis Based on Sequence Analysis,” Journal of Innovations in Computer Science and Engineering (JICSE), vol. 1, no. 1, pp. 1-10, 2023.
  • A. Salimi-Badr, “UNFIS: A Novel Neuro-Fuzzy Inference System with Unstructured Fuzzy Rules for Classification,” arXiv preprint, arXiv:2211.00599
  • A. Salimi-Badr, M.M. Ebadzadeh, ” A Novel Self-Organizing Fuzzy Neural Network to Learn and Mimic Habitual Sequential Tasks ,” IEEE Transactions on Cybernetics, vol. 52, pp. 323 – 332, 2022.
  • A. Salimi-Badr, “IT2CFNN: An Interval Type-2 Correlation-Aware Fuzzy Neural Network to Construct Non-Separable Fuzzy Rules with Uncertain and Adaptive Shapes for Nonlinear Function Approximation,”  Applied Soft Computing, vol. 115, pp. 108258, 2022..
  • A. Salimi-Badr, M.M. Ebadzadeh, “A Novel Learning Algorithm Based on Computing the Rules’ Desired Outputs of a TSK Fuzzy Neural Network with Non-Separable Fuzzy Rules,” Neurocomputing, vol. 470, pp. 139-153, 2022.
  • M. Vazirpanah, S. -H. Attarzadeh-Niaki, and A. Salimi-Badr, “ROS-Based Co-Simulation for Formal Cyber-Physical Robotic System Design,” 2022 27th International Computer Conference, Computer Society of Iran (CSICC), 2022, pp. 1-5, doi:10.1109/CSICC55295.2022.9780500.
  • N. Mahdian, S.H. Attarzadeh-Niaki, A. Salimi-Badr, A Systematic Embedded Software Design Flow for Robotic Applications. In 2021 11th International Conference on Computer and Knowledge Engineering (ICCKE ) 2021 Oct. 28-29. IEEE.
  • A. Salimi-Badr, M. Hashemi, A Neural-Based Approach to Aid Early Parkinson’s Disease Diagnosis. In 2020 11th International Conference on Information and Knowledge Technology (IKT) 2020 Dec 22 (pp. 23-25). IEEE.
  • C. Darlot, A. Salimi-Badr, M. Asadi-Eydivand, Z. Ghorrati, M.M. Ebadzadeh, “A computational system-level model of oculomotor pathways accounting for the representation of eye biomechanics in the cerebellar vermis,” IEEE Access, vol. 8, pp. 110859 – 110879, 2020.
  • M.M. Ebadzadeh, A. Salimi-Badr, “IC-FNN: A novel fuzzy neural network with interpretable, intuitive and correlated-contours fuzzy rules for function approximation,” IEEE Transactions on Fuzzy Systems, vol. 26, no. 3, pp. 1288-1302, 2018.
  • A. Salimi-Badr, M.M. Ebadzadeh, and C. Darlot, “A system-level mathematical model of Basal Ganglia motor-circuit for kinematic planning of arm movements,” Computers in Biology and Medicine, vol. 92, pp. 78-89, 2018.
  • A. Salimi-Badr, M.M. Ebadzadeh, and C. Darlot, “Fuzzy neuronal model of motor control inspired by cerebellar pathways to online and gradually learn inverse biomechanical functions in presence of delay,” Biological Cybernetics, vol. 111, pp. 421-438, 2017.
  • A. Salimi-Badr, M.M. Ebadzadeh, and C. Darlot, “A possible correlation between basal ganglia motor function and the inverse kinematics calculation,” Journal of Computational Neuroscience, vol. 43, pp. 295-318, 2017.
  • M. M. Ebadzadeh, A. Salimi-Badr, “CFNN: Correlated fuzzy neural network,” Neurocomputing, vol. 148, no. 1, pp. 430-444, 2015.
  • M. M. Homayounpour, A. Salimi-Badr, “Phrase Chunking in Persian Texts,” Signal and Data Processing, vol. 10, pp. 69-86, 2013.

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