Assoc. Prof. Dr. M. Abdul | Research Excellence Award

Assoc. Prof. Dr. M. Abdul | Research Excellence Award

Quanzhou University of Information Engineering | China

Muhammad Abdul is a researcher specializing in boson sampling, machine learning, ultracold atoms, high-resolution imaging systems, quantum technology involving surface acoustic waves, quantum phase transitions, nonlinear dynamical systems, and the invention of new materials. He earned his PhD from the University of Science and Technology of China, Hefei, where he worked on ultracold atoms in optical lattices, nonlinear optics, photonic devices, quantum networks, and boson sampling. He previously completed an M.Phil in Electronics at Quaid-i-Azam University. His professional experience includes serving as a Researcher at the University of Electronic Science and Technology of China; Assistant Professor at Sichuan University; Research Associate at Quaid-i-Azam University; Visiting Faculty at the Federal Urdu University; Lecturer at St. Mary College and the Punjab Group of Colleges; and High School Science Teacher at Down High School Mailsi. His research activities span mathematical modeling of nonlinear systems, materials development, and improvements in medication, supported in part by funding for developing a general dynamical model. He has contributed extensively to peer review across major journals and continues to advance interdisciplinary science across China, the United States, and the United Kingdom through research, teaching, and collaboration.

Profile : Orcid

Featured Publications

Abdul, M., Ko, C., Ismail, M. A., Ben Khalifa, S., Alsaif, N. A. M., Chebaane, S., Akbar, J., & Allakhverdiev, S. I. (2026). Development of rare earth metal-supported manganese selenide (MnSe₂-Nd₂O₃) heterostructure enabling robust hydrogen evolution reaction. Fuel. https://doi.org/10.1016/j.fuel.2025.136948

Abdul, M., Zhang, M., Ma, T., Alotaibi, N. H., Mohammad, S., & Luo, Y.-S. (2025). Facile synthesis of Co₃Te₄–Fe₃C for efficient overall water-splitting in an alkaline medium. Nanoscale Advances. https://doi.org/10.1039/D4NA00930D

Abdul, M., Kuo, C.-T., Ismail, M. A., Ben Khalifa, S., Alsaif, N. A. M., Chebaane, S., Shareef, M., & Shehzadi, A. (2025). Facile synthesis of novel WO₃·H₂O@Al-MOF nanocomposite for enhanced electrocatalytic hydrogen and oxygen evolution. Electrochimica Acta. https://doi.org/10.1016/j.electacta.2025.147714

Sardar, S., Nazeer, S., Naeem, F., Ben Khalifa, S., Chebaane, S., Saidani, T., Ismail, M. A., & Abdul, M. (2025). Se-decorated TiC/TiO₂ nanocomposite for overall water-splitting in alkaline medium. Fuel. https://doi.org/10.1016/j.fuel.2025.135672

Abdul, M., Ko, C., Tang, X., Ben Khalifa, S., Alsaif, N. A. M., Chebaane, S., & Akbar, J. (2025). S-scheme MnO₂–MnS₂@C heterostructure for environmental and biological applications. Ceramics International. https://doi.org/10.1016/j.ceramint.2025.09.284

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

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