Assoc. Prof. Dr. Ateke Goshvarpour | Best Researcher Award

Imam Reza International University | Iran

Ateke Goshvarpour is a distinguished researcher at Imam Reza International University, renowned for her extensive contributions to biomedical signal processing, emotion recognition, and neurophysiological data analysis. With an impressive h-index of 20, over 1,093 citations, and 70 research publications, her work has significantly advanced the integration of computational intelligence and physiological signal modeling. She has co-authored several influential studies on electroencephalography (EEG), electrocardiography (ECG), photoplethysmography (PPG), and galvanic skin response (GSR) for emotion and mental disorder recognition. Dr. Goshvarpour earned her higher education in biomedical engineering and has accumulated years of academic and research experience focusing on nonlinear analysis, chaos theory, and machine learning applications in healthcare. Her recent works explore quantum-inspired models, graph-based EEG analysis, and spectral–spatiotemporal fusion for diagnosing schizophrenia and cognitive disorders. She has been recognized for developing innovative feature fusion techniques that enhance accuracy in automated emotion recognition and neurodiagnostic systems. Her publications in high-impact journals such as Cognitive Neurodynamics, Chaos, Solitons & Fractals, and Biomedical Signal Processing and Control underscore her leadership in the field. Through her pioneering research, she continues to shape the future of computational neuroscience and affective computing, bridging the gap between biomedical engineering and mental health diagnostics.

Profiles : Scopus | Google Scholar

Featured Publications

Goshvarpour, A., Abbasi, A., & Goshvarpour, A. (2017). An accurate emotion recognition system using ECG and GSR signals and matching pursuit method. Biomedical Journal, 40(6), 355–368. https://doi.org/10.1016/j.bj.2017.10.001

Goshvarpour, A., & Goshvarpour, A. (2019). EEG spectral powers and source localization in depressing, sad, and fun music videos focusing on gender differences. Cognitive Neurodynamics, 13(2), 161–173. https://doi.org/10.1007/s11571-018-9510-8

Goshvarpour, A., Abbasi, A., & Goshvarpour, A. (2017). Fusion of heart rate variability and pulse rate variability for emotion recognition using lagged Poincaré plots. Australasian Physical & Engineering Sciences in Medicine, 40(3), 617–629. https://doi.org/10.1007/s13246-017-0560-7

Goshvarpour, A., & Goshvarpour, A. (2020). Schizophrenia diagnosis using innovative EEG feature-level fusion schemes. Physical and Engineering Sciences in Medicine, 43(1), 227–238. https://doi.org/10.1007/s13246-019-00853-8

Goshvarpour, A., & Goshvarpour, A. (2018). Poincaré’s section analysis for PPG-based automatic emotion recognition. Chaos, Solitons & Fractals, 114, 400–407. https://doi.org/10.1016/j.chaos.2018.07.009

Prof. Nicolas Lori | Best Researcher Award

University of Azores | Portugal

Dr. Nicolas F. Lori is a distinguished physicist and computer scientist, presently serving as an Assistant Professor at the University of the Azores and a researcher at the Centre Algoritmi, University of Minho, Portugal. He earned a Ph.D. in Physics from Washington University in St. Louis in 2001 and a Ph.D. in Informatics from the University of Minho in 2020. With 44 research papers, over 2,495 citations, and an h-index of 13, his work spans theoretical physics, computer science, and neuroscience. Dr. Lori has made pioneering contributions to diffusion MRI, brain connectivity mapping, and theoretical models bridging physics and computation. His studies have appeared in top-tier journals such as PNAS, Radiology, and Annals of Physics. He has successfully led national research projects totaling over €1.5 million and supervised multiple graduate students. His current research interests include MRI data processing, quantum gravity, artificial intelligence, theoretical neuroscience, and computational modeling. A Fulbright Fellow and former Vice-President of Fulbrighters Portugal, Dr. Lori’s career demonstrates a strong commitment to advancing interdisciplinary research that integrates physics, computation, and cognitive science to understand the complexity of the brain and the universe.

Featured Publications

Lori, N. F., Akbudak, E., Shimony, J. S., Cull, T. S., Snyder, A. Z., Guillory, R. K., … & Conturo, T. E. (2002). Diffusion tensor fiber tracking of human brain connectivity: Acquisition methods, reliability analysis, and biological results. NMR in Biomedicine, 15(7–8), 459–477.

Seehaus, A., Roebroeck, A., Bastiani, M., Fonseca, L., Bratzke, H., Lori, N., … & Galuske, R. (2015). Histological validation of high-resolution DTI in human post mortem tissue. Frontiers in Neuroanatomy, 9, 98.

Sedeno, L., Piguet, O., Abrevaya, S., Desmaras, H., García-Cordero, I., Baez, S., … & Lori, N. F. (2017). Tackling variability: A multicenter study to provide a gold‐standard network approach for frontotemporal dementia. Human Brain Mapping, 38(8), 3804–3822.

Lori, N. F. (2023). Mass creation in superconductors by Physics-cells quantum gravity. Physica C: Superconductivity and Its Applications, 611, 135722.

Lori, N. F. (2025). Darwinian quantum gravity dynamics of small particles. Annals of Physics, 449, 169553.

Lori, N. F. (2025). Varying Newton gravitational “constant” cosmology. Annals of Physics, 451, 170012.