Mostafa Jalalnezhad | Mobile Robot | Best Researcher Award

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Dr. Mostafa Jalalnezhad | Mobile Robot | Best Researcher Award

Kharazmi University | Iran

Dr. Mostafa Jalalnezhad is a dedicated researcher in Mechanical Engineering with a specialization in Control and Vibration, focusing particularly on robotics and mechatronics systems. His research interests encompass robotics, mobile robotics, nonlinear control, and robust adaptive control, reflecting a deep engagement with advanced control methodologies and intelligent systems design. He has contributed to the study and development of dynamic control mechanisms aimed at enhancing the precision, stability, and adaptability of robotic systems in complex environments. As a researcher at Kharazmi University, he actively participates in projects that integrate theoretical and experimental approaches to address challenges in automation and control engineering. His expertise extends to the modeling and simulation of robotic systems, adaptive algorithms for uncertain environments, and the design of control strategies to improve system performance under nonlinear and time-varying conditions. Through his academic and research activities, Dr. Jalalnezhad demonstrates a strong commitment to advancing innovations in mechatronic applications and fostering the integration of control theory with practical robotic solutions, contributing meaningfully to the progress of intelligent mechanical systems and modern automation technologies.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Jalalnezhad, M. (2025, December). Neural network-based intelligent path tracking for nonlinear predictive control in wheeled robots. Journal of the Brazilian Society of Mechanical Sciences and Engineering.

Jalalnezhad, M., Sayed, B. T., Alotaibi, Y., Al-Mohair, H. K., Kareem, A. K., Adel, A. A., Khaddour, R. H., Sharma, M. K., Alanssari, A. I., & Attabi, K. A. L. (2025, December). Real-time vision-based obstacle avoidance for mobile robots using lightweight monocular depth estimation and behavior-driven control. Journal of the Brazilian Society of Mechanical Sciences and Engineering.

Jalalnezhad, M., Sharma, M. K., Mansouri, S., Velmurugan, S., Askar, S., Alawsi, T., Alawadi, A., & Abbas, A. H. (2025, November). [RETRACTED] Learning model predictive controller for wheeled mobile robot with less time delay. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.

Jalalnezhad, M. (2025, October). Design of intelligent control systems for damping vibrations of composite sheets using piezoelectricity as a sensor and actuator under various disturbance conditions. Journal of the Brazilian Society of Mechanical Sciences and Engineering.

Jalalnezhad, M., Kareem, A. K., Chammam, A., & Al Attabi, K. A. (2025, October). Intelligent vibration control of composite and FGM plates using piezoelectric actuators and optimized sliding mode-based controllers. Journal of Vibration Engineering & Technologies.

Fariba Shokoohi | Construction Engineering | Best Researcher Award

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Ms. Fariba Shokoohi | Construction Engineering | Best Researcher Award

SR.C Islamic Azad University, Tehran | Iran

Ms. Fariba Shokoohi is an accomplished civil engineer and researcher specializing in Construction Engineering and Management, with extensive expertise in sustainable development, lean construction, and project management systems. Her professional experience spans engineering design, supervision, project management, and strategic planning in large-scale infrastructure and building projects. She has held senior positions in several engineering and construction firms, contributing to the design and management of complex urban development, industrial, and institutional projects. Her research integrates Fuzzy Multi Criteria Decision-Making models (DEMATEL, AHP, ANP) with Building Information Modeling (BIM) tools such as DesignBuilder and Revit to optimize sustainability performance and operational efficiency in the construction sector. Dr. Shokoohi’s scholarly work focuses on the intersection of lean thinking, environmental sustainability, and project performance evaluation, leading to publications in international journals and conferences. She is skilled in applying PMBOK standards, SERVQUAL and Kano models, and quality management systems including ISO and SAPCO standards. In addition to her technical expertise, she actively contributes to the engineering community as a Senior Member of the Tehran Construction Engineering Organization and member of professional bodies such as the Iran Concrete Research Center (METEB) and the Iranian Society of Civil Engineers (ISCE). Her ongoing doctoral research explores innovative frameworks for integrating sustainability and lean principles into construction project management, aiming to enhance industry practices and policy frameworks.

Profile: Google Scholar

Featured Publication

Shokoohi, F., & Ravanshadnia, M. (2024). Evaluating the impact of green roofs on reducing carbon emissions and improving environmental sustainability in the construction industry (Case study of a building in Tehran using Design Builder software). In Proceedings of the 8th International Conference on Civil Engineering, Architecture and Sustainable Green City.

Shokoohi, F. (2023). Application of the focus group method in the extended fuzzy DEMET technique (Integrating effective factors in lean and sustainable construction). Statistical Thought, 27(2), 105–120.

Rabieifar, H., Shokoohi, F., & Ashtiani, Z. (2020). The use of bacteria in concrete repair and its effect on the properties of self-healing concrete (Review). In Proceedings of the 23rd Annual National Conference on Concrete and Earthquakes. Concrete Research Center (CRC), 15.

Farokhzadeh, F., & Shokoohi, F. (2020). Integrating lean thinking and sustainable development in the field of health, safety and environment (HSE) management in the construction. Research in Defense Maintenance Engineering, 3(2), 58–74.

Fatma Elsayed | Cancer Resistance | Best Researcher Award

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Ms. Fatma Elsayed | Cancer Resistance | Best Researcher Award

National Research Centre | Egypt

Ms. Fatma Elsayed is a young researcher in the field of biochemistry and molecular biology, currently engaged in advanced studies and research focused on the therapeutic potential of natural and nano-formulated compounds in mitigating drug-induced toxicity and cancer progression. Her work primarily investigates molecular mechanisms underlying oxidative stress, inflammation, and signal transduction pathways in disease models. As a research assistant at the National Research Center in Egypt, she has gained extensive expertise in nanomaterial imaging using Transmission Electron Microscopy (TEM), molecular biology techniques such as RNA extraction, PCR, and ELISA, and analytical instrumentation including HPLC and mass spectrophotometry. She has contributed to peer-reviewed publications addressing cardiotoxicity and neurotoxicity induced by chemotherapeutic agents, as well as nanoparticle-based interventions in oncology. Beyond her research, she has practical experience as an oncology and community pharmacist, providing medication management and patient education on safe drug use and antimicrobial resistance. Her academic achievements have been recognized through national awards and a competitive scholarship from the Academy of Scientific Research and Technology. In addition to her scientific pursuits, she has demonstrated leadership in organizing academic conferences and mentoring peers in scientific writing. With a solid foundation in pharmaceutical sciences, molecular pharmacology, and nanotechnology, Ms. Elsayed continues to pursue innovative biomedical research aimed at improving therapeutic efficacy and patient outcomes in cancer and toxicology-related studies.

Profile: Google Scholar

Featured Publication

Elsayed, F. F., Elshenawy, W. M., Khalifa, E. M., Rizq, M. R., & Abdelaziz, R. R. (2022). Ameliorative effect of flavocoxid on cyclophosphamide-induced cardio and neurotoxicity via targeting the GM-CSF/NF-κB signaling pathway. Environmental Science and Pollution Research, 29(46), 69635–69651.

Alexandre Bougdour | Microbiologie | Research Excellence Distinction Award

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Dr. Alexandre Bougdour | Microbiologie | Research Excellence Distinction Award

Charge de Recherche | Institut National De La Sante Et De la Recherche Medicale | France

Dr. Alexandre Bougdour is a senior research scientist at the Institut National de la Santé et de la Recherche Médicale (INSERM) within the Institut for Advanced Biosciences in Grenoble, where he leads work in the Host-Pathogen Interactions & Immunity to Infection team. His research focuses on molecular and cellular mechanisms underlying host-pathogen interactions, particularly in parasitic diseases caused by Toxoplasma gondii and Plasmodium falciparum. He has made significant contributions to understanding how these parasites manipulate host signaling pathways, gene expression, and immune responses through effector proteins and epigenetic regulation. His work has uncovered novel targets for antiparasitic therapy, including the identification of spliceosome kinases and proteases as druggable components. He has co-authored highly cited papers in top tier journals such as Nature Microbiology, Science Translational Medicine, Cell Host & Microbe, EMBO Molecular Medicine, and Journal of Experimental Medicine. Dr. Bougdour’s achievements include awards from the National Institutes of Health and the Philippe Foundation, and his research has led to patents on antiparasitic peptides and innovative drug repurposing strategies. As principal investigator of major national research grants, he has established himself as a leader in infection biology and translational research. Beyond his scientific achievements, he contributes as a mentor, thesis examiner, and scientific advisor for biotech initiatives such as ApiMed Discovery, reflecting his commitment to bridging academic research and biomedical innovation.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Bougdour, A., Robert, M. G., Swale, C., Pachano, B., Dépéry, L., Bellini, V., Dard, C., Cannella, D., Corrao, C., Belmudes, L., Couté, Y., et al. (2025). Uncovering biomarkers for chronic toxoplasmosis detection highlights alternative pathways shaping parasite dormancy. EMBO Molecular Medicine.

Bougdour, A., Pachano, B., Farhat, D. C., Shahinas, M., von Velsen, J., Corrao, C., Belmudes, L., de Bock, P. J., Mas, C., Couté, Y., Bowler, M. W., et al. (2025). An ISWI-related chromatin remodeller regulates stage-specific gene expression in Toxoplasma gondii. Nature Microbiology.

Bougdour, A., Antunes, A. V., Shahinas, M., Swale, C., Farhat, D. C., Ramakrishnan, C., Bruley, C., Cannella, D., Robert, M. G., Corrao, C., Couté, Y., et al. (2023). In vitro production of cat-restricted Toxoplasma pre-sexual stages. Nature.

Yogavel, M., Bougdour, A., Mishra, S., Malhotra, N., Chhibber-Goel, J., Bellini, V., Harlos, K., Laleu, B., Hakimi, M. A., & Sharma, A. (2023). Targeting prolyl-tRNA synthetase via a series of ATP-mimetics to accelerate drug discovery against toxoplasmosis. PLoS Pathogens.

Ten Hoeve, A. L., Braun, L., Rodriguez, M. E., Olivera, G. C., Bougdour, A., Belmudes, L., Couté, Y., Saeij, J. P. J., Hakimi, M. A., & Barragan, A. (2022). The Toxoplasma effector GRA28 promotes parasite dissemination by inducing dendritic cell-like migratory properties in infected macrophages. Cell Host & Microbe.

Nadia Shamshad | Wireless Networks | Best Researcher Award

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Ms. Nadia Shamshad | Wireless Networks | Best Researcher Award

Dalian University of Technoogy | China

Dr. Nadia S. Shamshad is a Software Engineer and Scholar in Software Engineering at Dalian University of Technology, China, with a strong research background in machine learning, reinforcement learning, deep learning, and multi-agent systems. Her work primarily focuses on adaptive control, localization, and optimization in dynamic and underwater sensor network environments, leveraging intelligent algorithms for precision and energy efficiency. She has contributed to several high-impact journals, including Scientific Reports, IEEE Access, and the IEEE Internet of Things Journal, where her research explores neural network-based localization, routing resilience, and machine learning-driven network adaptation. Her technical expertise spans Python, C++, MATLAB, NS 3, and network simulation, complemented by experience in both teaching and applied research. In academia, she has guided students in machine learning and cybersecurity applications, fostering critical thinking and innovation. Her professional experience also includes network administration and IT systems management, emphasizing performance optimization and cybersecurity. Dr. Shamshad’s research aims to bridge theoretical advancements and real world applications, contributing to intelligent, sustainable, and energy aware communication systems. She has received multiple academic honors, including prestigious scholarships and social service awards, and continues to advance interdisciplinary research at the intersection of artificial intelligence, wireless communication, and underwater sensing technologies.

Profiles: Scopus | Google Scholar

Featured Publications

Shamshad, N., Sarwr, D., Almogren, A., Saleem, K., Munawar, A., Rehman, A. U., et al. (2024). Enhancing brain tumor classification by a comprehensive study on transfer learning techniques and model efficiency using MRI datasets. IEEE Access, 63, 1.

Ahmad, I., Liu, Y., Javeed, D., Shamshad, N., Sarwr, D., & Ahmad, S. (2020). A review of artificial intelligence techniques for selection & evaluation. IOP Conference Series: Materials Science and Engineering, 853(1), 012055.

Shamshad, N., Wang, L., Saleem, K., Sarwr, D., Bharany, S., Almogren, A., et al. (2025). Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks. Scientific Reports, 15(1), 2182.

Shamshad, N., Wang, L., Sarwr, D., & Mohsan, S. A. H. (2025). Deeploc: A CNN-LSTM framework for NLOS-aware localization in underwater sensor networks. The Journal of Supercomputing, 81(16), 1–24.

Shamshad, N. D. S. (2020). A review of traffic flow prediction based on machine learning approaches. International Journal of Scientific & Engineering Research, 11(3), 5.

Ruiwen Wu | Aquatic Zoology | Best Researcher Award

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Dr. Ruiwen Wu | Aquatic Zoology | Best Researcher Award

Associate Professor | Shanxi Normal University | China

Dr. Ruiwen Wu is a researcher at Shanxi Normal University whose work centers on the taxonomy, phylogeny, biodiversity, and conservation of freshwater mussels and other bivalves. Her research integrates morphological, molecular, and phylogenomic approaches to uncover hidden diversity, describe new species, and refine the systematic classification of Unionidae and related taxa. She has significantly contributed to understanding the evolutionary relationships and biogeography of endemic Chinese freshwater mussels, advancing knowledge on their genetic diversity, population structure, and ecological adaptations. Her publications in high impact journals such as Invertebrate Systematics, ZooKeys, Zoologica Scripta, Freshwater Biology, and BMC Genomics demonstrate her expertise in combining integrative taxonomy with conservation biology. Dr. Wu’s studies have also addressed broader ecological issues, including biodiversity loss due to habitat alteration and dam construction. Her research outputs include detailed phylogenetic reconstructions, mitochondrial genome analyses, and biogeographic assessments that inform species conservation strategies and contribute to global freshwater biodiversity studies. As an active reviewer for several international journals, she supports the advancement of rigorous scientific scholarship in evolutionary biology and aquatic ecology. Through her extensive body of work, Dr. Wu has established herself as a leading figure in freshwater mollusk systematics, contributing valuable insights into species diversity, evolutionary history, and conservation priorities within aquatic ecosystems.

Profile: Scopus

Featured Publications

Wu, R., (2025). Diversity, phylogeny and distribution of the subtribe Cristariina (Bivalvia: Unionidae: Unioninae) from China, with description of a new genus and species. Invertebrate Systematics.

Wu, R., (2025). Underestimated diversity: A new species of the genus Cuneopsis (Bivalvia, Unionidae, Unioninae) from Henan, China. Zoosystematics and Evolution.

Wu, R., (2025). Revisiting the genus Nodularia (Bivalvia, Unionidae): Mitochondrial phylogenomics and the description of a new species. Zoosystematics and Evolution.

Wu, R., (2025). Corrigendum to: Cryptic species, mitochondrial phylogenomics and historical biogeography in the endemic genus Schistodesmus (Bivalvia, Unionidae) from China.

Peijiang Zhang | Automatic Drive | Best Researcher Award

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Dr. Peijiang Zhang | Automatic Drive | Best Researcher Award

School of Information, Chang’an University | China

Dr. Peijiang Zhang is a researcher specializing in human machine collaboration, bio inspired visual perception, 3D vision, precision measurement, and multi sensor information fusion. His research bridges the fields of computer vision, cognitive neuroscience, and artificial intelligence, focusing on developing biologically inspired perception models that emulate the cognitive and visual mechanisms of the human brain. Through his work, he has advanced methodologies for image quality assessment, defect detection in mechanical manufacturing, and visual modeling inspired by human visual cognition. His studies extend to 3D LiDAR based SLAM algorithms and integrated vehicle infrastructure cooperative perception systems, contributing to intelligent transportation and autonomous systems. Dr. Zhang’s current research aims to enhance human machine collaborative perception by integrating AI and brain computer interface technologies to improve system adaptability, real time decision making, and cooperative sensing performance. His scientific contributions have been recognized through publications in high impact journals and conferences, including research on cognitive load classification using spiking neural networks and cross-modal brain activity analysis. His work is directed toward advancing intelligent, adaptive, and cooperative perception systems for autonomous vehicles and smart transportation infrastructures, contributing to the next generation of bio inspired artificial intelligence and human-centered machine collaboration.

Profile: Orcid

Featured Publications

Zhang, P., Cheng, T., Jiang, Y., Zou, X., & Chen, X. (2025). fNIRS SpikeNet: A spiking neural network framework for cognitive load classification in cooperative learning environments. IEEE Transactions on Computational Social Systems.

Zou, X., Liu, X., Wang, K., Cheng, T., & Zhang, P. (2025, November 4). Cognitive load in novice UAV pilots: A preliminary fNIRS investigation. International Journal of Human–Computer Interaction.

Zou, X., Zhang, P., Cheng, T., & Fan, J. (2024, November 15). Effects of hazard perception training on driving behavior: An fNIRS-based assessment. In Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Human-Computer Interaction and Robotics (AIHCIR). IEEE.

Zhang, P., & Zou, X. (2024, November 15). Integrated approach for cross-modal brain activity classification through manual feature extraction. In Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Human-Computer Interaction and Robotics (AIHCIR). IEEE.

Dan Li | Computer Vision | Best Researcher Award

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Dr. Dan Li | Computer Vision | Best Researcher Award

Lecturer | University of Shanghai for Science and Technology | China

Dr. Dan Li is a Lecturer at the University of Shanghai for Science and Technology, specializing in decision theory, artificial intelligence management, and efficiency analysis. Her research integrates data driven decision making methods with emerging AI technologies to address complex management and operational challenges. She has contributed to advancements in efficiency measurement, intelligent systems, and optimization through funded research projects supported by national and provincial foundations. Dr. Li’s publications appear in leading journals such as Knowledge-Based Systems, Advanced Engineering Informatics, Omega, Journal of the Operational Research Society, and Journal of Cleaner Production, where she explores topics including AI based object detection, data envelopment analysis, and performance evaluation of industrial and service systems. Her work bridges theoretical modeling with practical applications in sectors such as finance, education, and sustainability. In addition to her research, she actively contributes to the academic community as a reviewer for high-impact international journals and engages in interdisciplinary collaborations focusing on the integration of artificial intelligence into management science. Through her innovative approaches and international research engagements, Dr. Li continues to advance the fields of decision science and AI-driven management solutions.

Profiles: Scopus | Orcid

Featured Publications

Tang, J., Li, D., Yang, J., Chen, J., & Yuan, R. (2025). Leveraging large visual models for enhanced object detection: An improved SAM-YOLOv5 model. Knowledge-Based Systems, 114757.

Yang, J., Emrouznejad, A., & Li, D. (2024, October 25). An improved game cross-efficiency approach with dual-role factors for measuring the efficiency of Chinese “985 project” universities. Journal of the Operational Research Society.

Chen, C.-M., & Li, D. (2024, July). Weighing in on the average weights: Measuring corporate social performance (CSP) score using DEA. Omega, 103072.

Yang, J., Li, D., & Li, Y. (2024, January). A generalized data envelopment analysis approach for fixed cost allocation with preference information. Omega, 102948.

Yang, J., & Li, D. (2022, June 9). Finding the single efficient unit in data envelopment analysis with flexible measures. Journal of the Operational Research Society.

Muhammad Akram | Bioinformatics | Best Researcher Award

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Dr. Muhammad Akram | Bioinformatics | Best Researcher Award

Assistant Professor | University of Management and Technology | Pakistan

Dr. Muhammad Akram is a biochemist and biotechnology researcher whose work bridges molecular biology, metabolic engineering, and pharmaceutical biotechnology. His research focuses on the metabolic engineering of microbial strains for the sustainable production of natural compounds, therapeutic proteins, and pharmaceuticals. He has made significant contributions to the biosynthesis of secondary metabolites from both natural and heterologous hosts, the bioinformatics visualization of protein ligand interactions, and the development of microbial systems for nanoparticle synthesis and biomedical applications. His expertise also extends to protein engineering, synthetic biology, and cancer genetics, with a strong emphasis on translating laboratory findings into industrial and health-related innovations. Dr. Akram’s research has been published in high impact international journals, covering topics such as engineered Yarrowia lipolytica for plant metabolite production, CRISPR based disease control, and nanobiotechnology. He has actively participated in international scientific conferences and workshops, demonstrating a commitment to advancing interdisciplinary collaboration and applied biosciences. As an academic and mentor, he has supervised numerous postgraduate and undergraduate students in biochemistry and biotechnology, fostering research capacity in emerging areas of synthetic and molecular biosciences. His professional service includes peer reviewing for several international journals and contributing to academic workshops on molecular biology and generative AI in scientific research, reflecting his dedication to both research excellence and modern pedagogical innovation.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Mahboob, A., Akram, M., Rauf, A., Saidmuratova, M., Djabbarov, I., Ali, S. K., Alamri, A. A., Asimov, A., Bahadur, A., Iqbal, S., et al. (2025, November 4). Comprehensive functional and profiling analysis of circular RNAs in type 2 diabetes mellitus: Unveiling novel and biomarker therapeutic targets. Network Modeling Analysis in Health Informatics and Bioinformatics.

Akram, M. (2025, June 29). Bioremediation of textile disperse dyes using white-rot fungi Trametes versicolor. International Journal of Innovations in Science & Technology.

Akram, M. (2025, June 28). Cyanidin-3-glucoside from Litchi: Extraction techniques and bioactivity evaluation. Riphah Journal of Allied Health Sciences.

Akram, M. (2025, May 22). Bioremediation of textile disperse dyes using white-rot fungi Trametes gibbosa. TSF Journal of Biology.

Akram, M. (2024, October 24). Microbiological, heavy metal and antioxidant analysis of some commonly used spices in Pakistani cuisine. Riphah Journal of Allied Health Sciences.

Christine Saleh | Women’s Health | Best Researcher Award

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Ms. Christine Saleh | Women’s Health | Best Researcher Award

Researcher | Western Sydney University | Australia

Ms. Christine Saleh is a Health Science professional with a strong academic foundation in Health Promotion and Women’s Health. Her research background reflects a focused interest in improving public health outcomes through the promotion of healthy lifestyles and preventive health strategies, particularly in relation to children’s health and women’s wellbeing. She has engaged in applied research exploring self-care practices, pelvic pain management, and health behavior interventions, contributing to initiatives that bridge research with community-based health promotion. Professionally, she has extensive experience within the higher education and healthcare sectors, providing administrative, advisory, and research support in academic and clinical settings. Her roles have emphasized effective communication, student engagement, and the coordination of research-related activities, enhancing the operational and research functions of her institutions. She has demonstrated proficiency in managing complex administrative systems, supporting postgraduate research programs, and facilitating health-related projects. Her background in pharmacy assistance has further strengthened her understanding of community health service delivery and patient engagement. Fluent in English and Arabic, she brings a multicultural perspective to her professional and research endeavors. Ms. Saleh’s combined expertise in research, administration, and community health underpins her commitment to advancing evidence-based health promotion and public health initiatives that foster wellbeing across diverse populations.

Profile: Orcid

Featured Publications

Saleh, C., Hawkey, A., & Armour, M. (2025). Perceptions and experiences of menstrual pain among Middle Eastern women living in Australia. Culture, Health & Sexuality. Advance online publication.