Yunju Xiao | Biosensors | Best Researcher Award

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Mrs. Yunju Xiao | Biosensors | Best Researcher Award

Mrs. Yunju Xiao | Biosensors | Junior Physician at Guangdong Provincial People’s Hospital | China

Mrs. Yunju Xiao is an accomplished researcher specializing in biomedical sensing, nanomaterials-based analytical systems, and molecular diagnostics, recognized for her contributions to advancing innovative detection platforms for clinical and translational applications. She completed her education through rigorous training in medical sciences and research methodology, culminating in a doctoral qualification from a leading medical university where she focused on the development of nano-enabled biosensing technologies for sensitive biomarker identification and disease monitoring. Building on her academic foundation, she has gained significant professional experience at Guangdong Provincial People’s Hospital of Southern Medical University, where she contributes to multidisciplinary projects aimed at improving diagnostic precision and healthcare outcomes. Her research interests span catalytic hairpin assembly mechanisms, gold nanoparticle engineering, signal-enhanced detection systems, surface-enhanced Raman spectroscopy, and microRNA-based disease diagnostics, reflecting her dedication to bridging basic nanoscience with practical clinical applications. Mrs. Yunju Xiao’s research skills include expertise in nanoscale material synthesis, molecular probe design, advanced spectroscopic techniques, microfluidic diagnostics, data interpretation, and laboratory protocol optimization, allowing her to make meaningful contributions to emerging diagnostic research. She has authored multiple peer-reviewed publications indexed in Scopus and other leading databases, accumulating notable citations that reflect the visibility and academic value of her work. Her recognized publication in Sensors and Actuators B: Chemical demonstrates her ability to produce impactful research within competitive scientific fields. Throughout her academic and professional career, she has earned recognition for her scholarly output and has received honors for her contribution to collaborative research efforts and high-quality scientific dissemination. Her involvement in scientific communities further supports her commitment to continuous learning and professional advancement. Mrs. Yunju Xiao’s work reflects analytical rigor, innovation, and a strong commitment to addressing scientific challenges related to early disease detection and diagnostic sensitivity. She continues to expand her research through interdisciplinary collaborations, aiming to contribute to the development of next-generation biosensing systems. In conclusion, Mrs. Yunju Xiao exemplifies a promising and dedicated researcher whose background in biomedical diagnostics, strong methodological skills, and expanding publication record position her as an influential contributor to the future of diagnostic technology and biomedical research.

Academic Profile: ORCID | Scopus

Featured Publications:

  1. Xiao, Y. (2026). Catalytic hairpin assembly (CHA)-driven AuNP tetramer assembly-based SERS platform for sensitive detection of EV-miRNAs. Sensors and Actuators B: Chemical.

 

 

Guoli Song | Robotics | Research Excellence Award

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Prof. Guoli Song | Robotics | Research Excellence Award

Prof. Guoli Song | Robotics | Researcher at Shenyang Institute of Automation Chinese Academy of Sciences | China

Prof. Guoli Song is an accomplished researcher known for his extensive contributions to medical image analysis, biomedical signal processing, robotics-assisted diagnostics, and intelligent healthcare systems, emerging as a leading figure in the integration of artificial intelligence with modern medical technologies. Prof. Guoli Song completed his higher education at the Shenyang Institution of Automation, Chinese Academy of Sciences, where he earned his doctoral degree with a research focus on computational imaging, intelligent robotics, and medical data interpretation, building a strong academic foundation that continues to support his multidisciplinary scholarship. Over the course of his professional career, he has served in prominent research roles within the Chinese Academy of Sciences, where he has participated in several high-impact international projects involving automated disease detection, AI-based brain tumor segmentation, noninvasive biosensing technologies, and robotic navigation systems for clinical applications. His research interests span medical image registration, deep learning–based diagnosis, biomedical signal processing, optimization frameworks, force-sensing technologies, and computational neuroscience, demonstrating a broad intellectual range supported by strong analytical and technical skills. Prof. Guoli Song is highly proficient in designing advanced machine-learning algorithms, developing intelligent diagnostic pipelines, implementing robotics control architectures, and conducting large-scale computational experiments, which have led to publications in IEEE platforms, Scopus-indexed journals, and other reputable venues with a citation impact exceeding several hundreds. His work has earned recognition through academic honors, research excellence acknowledgments, and invitations to contribute to international collaborations, conferences, and journal review boards. He is actively engaged in professional communities and holds affiliations with respected organizations such as IEEE and ACM, reflecting his commitment to maintaining global research standards and fostering scientific knowledge exchange. Notably, his awards and honors stem from his contributions to intelligent medical systems, advanced diagnostic models, and cross-disciplinary engineering innovations. With a strong record of publications, including influential works on medical image segmentation, biosensing devices, gaze estimation for surgical robots, and hybrid feature-based diagnostic frameworks, Prof. Guoli Song continues to advance cutting-edge methodologies that shape the future of automated healthcare. His continued efforts toward developing efficient, accurate, and clinically relevant technologies highlight his ongoing potential for leadership and innovation. Prof. Guoli Song’s accomplishments, research influence, and future-oriented vision firmly establish him as a leading contributor to global scientific advancement and position him for sustained excellence in medical engineering and computational health research.

Academic Profile: Scopus | Google Scholar

Featured Publications:

  1. Song, G., Han, J., Zhao, Y., Wang, Z., & Du, H. (2017). A review on medical image registration as an optimization problem. 119 citations.

  2. Hao, Z., Luo, Y., Huang, C., Wang, Z., Song, G., Pan, Y., et al. (2021). An intelligent graphene-based biosensing device for cytokine storm syndrome biomarkers detection in human biofluids. 92 citations.

  3. Huang, Z., Zhao, Y., Liu, Y., & Song, G. (2021). GCAUNet: A group cross-channel attention residual UNet for slice-based brain tumor segmentation. 88 citations.

  4. Song, G., Huang, Z., Zhao, Y., Zhao, X., Liu, Y., Bao, M., et al. (2019). A noninvasive system for the automatic detection of gliomas based on hybrid features and PSO-KSVM. 54 citations.

  5. Deng, Y., Yang, T., Dai, S., & Song, G. (2020). A miniature triaxial fiber optic force sensor for flexible ureteroscopy. 50 citations.

Guodong Zheng | Aquaculture | Best Researcher Award

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Assoc. Prof. Dr. Guodong Zheng | Aquaculture | Best Researcher Award

Assoc. Prof. Dr. Guodong Zheng | Aquaculture | Professor at Shanghai Ocean University | China

Assoc. Prof. Dr. Guodong Zheng is a highly respected researcher in aquaculture genetics and fish physiology, working at the Genetics and Breeding Center for Blunt Snout Bream within Shanghai Ocean University, China. He earned his Ph.D. in aquatic sciences (genetics and breeding) and has since built a strong professional career pioneering research in hypoxia tolerance, genetic marker development, and cellular mechanisms of environmental stress in fish. Professionally, he leads international collaborative projects, notably on CRISPR/Cas9 gene editing in fish, transcriptomics under hypoxic stress, and selective breeding of hypoxia-tolerant fish strains. His research interests include molecular adaptation to stress, apoptosis pathways, gill remodeling, gene regulation of hypoxia-responsive factors, and sustainable aquaculture breeding. He possesses advanced research skills: high-throughput RNA sequencing, CRISPR/Cas9 genome editing, primary cell culture (especially gill cell lines), SNP marker mining, and physiological assays (oxidative stress, apoptosis). Among his awards and honors, Dr. Zheng has been recognized for his contributions to aquatic genetic resources, has received research grants for international projects, and serves as guest editor in international journals such as Animals. In addition, he is a valued member of academic societies and regularly supervises Ph.D. students, contributing to capacity building in aquaculture research. In conclusion, Assoc. Prof. Dr. Guodong Zheng’s pioneering work in combining molecular genetics with physiology under environmentally relevant stress demonstrates not only his deep expertise but also his visionary approach to making aquaculture more resilient and sustainable, positioning him as a leading scientist with strong future potential for innovation and global impact.

Academic Profile: ORCID | Scopus

Featured Publications:

Zheng, G., et al. (2026). Triploid induction by hydrostatic pressure in female Megalobrama amblycephala × male Culter alburnus hybrids: Effects on somatic growth enhancement and sterility. Aquaculture.

Zheng, G., et al. (2026). Synergistic effects of hypoxia and Aeromonas hydrophila infection on immune function in blunt snout bream (Megalobrama amblycephala). Aquaculture.

Zheng, G., et al. (2025). Bim gene regulation in hypoxic stress response of blunt snout bream (Megalobrama amblycephala): Mechanisms of apoptosis, oxidative stress, and transcriptional control by c-Ets-2. Comparative Biochemistry and Physiology Part A: Molecular and Integrative Physiology.

Zheng, G., et al. (2025). Identification of KASP-SNP markers correlated with both growth and hypoxia tolerance traits in blunt snout bream (Megalobrama amblycephala). Aquaculture.

Zheng, G., et al. (2025). Knockout of the fih gene by CRISPR/Cas9 enhances the hypoxia tolerance in grass carp (Ctenopharyngodon idella). Aquaculture.

 

 

Mohammad Badrul Alam Miah | Computer Science | Best Researcher Award

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Prof. Dr. Mohammad Badrul Alam Miah | Computer Science | Best Researcher Award

Prof. Dr. Mohammad Badrul Alam Miah | Computer Science | Professor at Mawlana Bhashani Science and Technology University | Bangladesh

Prof. Dr. Mohammad Badrul Alam Miah is a distinguished academic and research expert whose scholarly contributions span Data and Text Mining, Artificial Intelligence, Machine Learning, Neural Networks, Computer Vision, Photonic Crystal Fiber Design, and Network Communication Systems, making him a prominent figure in multidisciplinary computational research. Prof. Dr. Mohammad Badrul Alam Miah completed his higher education with advanced research training that established a strong methodological foundation for his career, enabling him to engage in both theoretical and applied scientific studies with exceptional depth. His professional experience includes long-standing service as a professor, program director, research supervisor, and senior academic leader, where he contributed extensively to curriculum development, postgraduate training, and international research collaborations across universities and specialized research centers. His research interests are rooted in intelligent systems, biomedical image analysis, AI-driven disease detection, fiber-optic sensing, blockchain-enabled IoT security, and automated information extraction systems, allowing him to integrate emerging technologies with real-world scientific challenges. Prof. Dr. Mohammad Badrul Alam Miah possesses advanced research skills in algorithm development, predictive modeling, feature engineering, neural network architecture design, data preprocessing, photonic fiber simulation, and cross-domain computational analysis, supported by strong proficiency in scientific programming and experimental validation. His recognition includes multiple scholarly honors, editorial review appointments, invited talks, and collaborative engagement with globally recognized researchers, reflecting his reputation as a respected contributor within the academic community. With a citation record exceeding nine hundred, an h-index demonstrating sustained impact, and numerous publications in IEEE, Scopus, Elsevier, and other reputable platforms, he continues to influence both foundational and applied research domains. His scholarly activities highlight his commitment to innovation, mentorship, and interdisciplinary advancement. Prof. Dr. Mohammad Badrul Alam Miah remains actively involved in expanding his research output through international collaborations, exploring advanced AI applications in healthcare, enhancing neural network performance for medical diagnostics, and contributing to knowledge development in data-driven science. His ongoing work positions him as a forward-looking researcher whose efforts significantly enrich global scientific scholarship and technological progress.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Miah, M. B. A., & Yousuf, M. A. (2015). Detection of lung cancer from CT image using image processing and neural network. 165 citations.

  2. Shamim, S. M., Miah, M. B. A., Sarker, M. R. A., & Jobair, A. A. (2018). Handwritten digit recognition using machine learning algorithms. 140 citations.

  3. Mehedi, S. K. T., Shamim, A. A. M., & Miah, M. B. A. (2019). Blockchain-based security management of IoT infrastructure with Ethereum transactions. 45 citations.

  4. Sethi, R., Kaushik, I., & Miah, M. B. A. (2020). Hand written digit recognition using machine learning. 40 citations.

  5. Chowdhury, S., Sen, S., Ahmed, K., Paul, B. K., Miah, M. B. A., & Asaduzzaman, S. (2017). Porous shaped photonic crystal fiber with strong confinement field in sensing applications: Design and analysis. 39 citations.

 

 

Farah Nameni | Physiology | Editorial Board Member

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Assoc. Prof. Dr. Farah Nameni | Physiology | Editorial Board Member

Assoc. Prof. Dr. Farah Nameni | Physiology | Researcher at IAU/ Varamin-Pishva Branch | Iran

Assoc. Prof. Dr. Farah Nameni is an accomplished scholar in exercise physiology whose research spans neuroinflammation, oxidative stress mechanisms, and the physiological pathways linking exercise with neuroprotective outcomes, earning her recognition as a dedicated researcher and academic leader. Her educational background, anchored in advanced studies in physiology at Islamic Azad University Varamin-Pishva Branch, provided the foundation for her extensive academic and scientific contributions, further strengthened by her professional role as a faculty member in the same institution, where she has contributed to teaching, research supervision, and laboratory development. Throughout her academic journey, Assoc. Prof. Dr. Farah Nameni has cultivated strong research interests focused on molecular and cellular responses to exercise interventions, Alzheimer’s disease models, biochemical markers of stress, neurotrophic signaling, and metabolic adaptations, positioning her work at the intersection of physiology, neuroscience, and sports science. She has developed notable research skills in experimental design, animal model studies, biochemical assays, gene expression analysis, and collaborative academic research, supported by multiple peer-reviewed publications in Scopus-indexed journals. Her work demonstrates proficiency in examining oxidative markers, neurotrophic factors, neurotransmitter receptor regulation, and the therapeutic potential of exercise combined with pharmacological or herbal interventions. In addition to her research productivity, Assoc. Prof. Dr. Farah Nameni has contributed to the scientific community through peer-review service and interdisciplinary collaborations, reflecting her growing recognition within the global research landscape. Her awards and honors stem from her academic contributions, successful project participation, and continuous advancements in exercise physiology research, highlighting her commitment to scholarly excellence and ethical scientific inquiry. As her research portfolio continues to expand, she demonstrates strong potential for further contributions to neurophysiological health, exercise-based therapeutic strategies, and translational scientific applications. In conclusion, Assoc. Prof. Dr. Farah Nameni stands as a dedicated and emerging figure in the field, with her educational foundation, academic experience, research achievements, and scholarly engagement positioning her for continued leadership and future breakthroughs in physiology and related health sciences.

Academic Profile: ORCID 

Featured Publications:

  1. Nameni, F., & Elikaei, F. (2025). The response of glutathione oxidase and cytochrome c to exercise training and sodium selenite in the heart tissue of male rats.

  2. Nameni, F., & Dehkordi, M. R. A. K. (2025). The effects of weight training and Aklil-ol-Malek on histopathology and C-reactive protein, nuclear factor erythroid-derived 2-like 2 beta-site amyloid precursor protein cleaving enzyme 1 genes expression in Alzheimer’s disease model rats.

  3. Nameni, F., Akbari, G., Hadavand, V., Entezari, H., Molaii, S., & Ghadami, N. (2024). Effect of Melilotus extract and exercise on oxidative stress and neuroinflammation in an Alzheimer’s mouse model.

  4. Nameni, F., Islami, M. H. A., & Hofmeister, M. (2024). The effect of exercise and sildenafil on brain-derived neurotrophic factor and tropomyosin kinase B receptor in the hippocampus of Alzheimer’s rats.

  5. Nameni, F., & Firuzmand, F. (2023). Simultaneous effect of resistance training and folate nano-liposome on dopamine receptors in the brain hippocampus of Alzheimer’s rats.

 

Nizar Ben Ezzine | Energy | Editorial Board Member

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Prof. Nizar Ben Ezzine | Energy | Editorial Board Member

Prof. Nizar Ben Ezzine | Energy | Professor at Carthage University | Tunisia

Prof. Nizar Ben Ezzine is an accomplished scholar in the field of energy engineering, widely recognized for his contributions to thermodynamics, solar cooling technologies, and absorption refrigeration systems, and he has established a strong academic and research identity through his advanced education culminating in a doctoral degree in energetics that laid the foundation for his expertise in thermal sciences and sustainable cooling systems. Throughout his professional journey, Prof. Nizar Ben Ezzine has served in reputable academic and research institutions where he has contributed extensively to teaching, mentoring, scientific collaborations, and the development of cutting-edge research initiatives in the areas of thermodynamic modelling, exergy analysis, and high-efficiency refrigeration cycles. His research interests include solar-driven absorption systems, ammonia–water thermodynamic mixtures, diffusion-absorption refrigeration cycles, sustainable thermal energy solutions, and performance optimisation of environmentally friendly cooling systems, which he explores using advanced numerical modelling, experimental investigations, and multi-parameter optimisation techniques. Prof. Nizar Ben Ezzine demonstrates strong research skills in computational modelling of thermal systems, experimental system testing, simulation of absorption chillers, development of solar-powered cooling technologies, and analytical techniques for evaluating irreversibilities in thermal cycles, supported by an extensive record of publications in Scopus-indexed and high-impact journals. His scholarly outputs include influential articles in journals such as Energy, Renewable Energy, the International Journal of Exergy, and the International Journal of Refrigeration, which collectively reflect his scientific depth and sustained impact. With hundreds of citations, an established h-index, and numerous international co-authorships, he has built a collaborative presence within the global energy research community and contributed to significant international research projects addressing sustainable cooling and thermodynamic optimisation challenges. Prof. Nizar Ben Ezzine has been acknowledged for his academic excellence through various research-based recognitions, invitations to scientific committees, and participation in specialized conferences that highlight his leadership within the thermal and renewable energy sectors. His work continues to influence the design and development of future cooling technologies, and his research trajectory demonstrates strong promise for further innovation in areas such as advanced solar cooling, next-generation refrigerant mixtures, and integrated renewable energy systems. In conclusion, Prof. Nizar Ben Ezzine stands as a leading figure whose scientific contributions, professional experience, collaborative engagements, and commitment to sustainability continue to shape advancements in the global field of energy engineering.

Academic Profile: Google Scholar

Featured Publications:

  1. Ezzine, N. B., Garma, R., & Bellagi, A. (2010). A numerical investigation of a diffusion-absorption refrigeration cycle based on R124-DMAC mixture for solar cooling. Energy, 35(5), 1874–1883. Citations: 108

  2. Ezzine, N. B., Garma, R., Bourouis, M., & Bellagi, A. (2010). Experimental studies on bubble pump operated diffusion absorption machine based on light hydrocarbons for solar cooling. Renewable Energy, 35(2), 464–470. Citations: 83

  3. Ezzine, N. B., Barhoumi, M., Mejbri, K., Chemkhi, S., & Bellagi, A. (2004). Solar cooling with the absorption principle: First and Second Law analysis of an ammonia–water double-generator absorption chiller. Desalination, 168, 137–144. Citations: 61

  4. Mejbri, K., Ezzine, N. B., Guizani, Y., & Bellagi, A. (2006). Discussion of the feasibility of the Einstein refrigeration cycle. International Journal of Refrigeration, 29(1), 60–70. Citations: 27

  5. Barhoumi, M., Snoussi, A., Ben Ezzine, N., Mejbri, K. H., & Bellagi, A. (2004). Modelling of the thermodynamic properties of the ammonia/water mixture. International Journal of Refrigeration, 27(3). Citations: 26

 

John Msinde | Climate Change | Editorial Board Member

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Dr. John Msinde | Climate Change | Editorial Board Member

Dr. John Msinde | Climate Change | Lecturer at University of Dar es Salaam | Tanzania

Dr. John Msinde is a dedicated scholar in the domains of poverty studies, migration, rural livelihoods, and sustainable agricultural development, widely recognized for his evidence-based contributions to socioeconomic transformation in Tanzania and beyond. Dr. John Msinde completed his advanced academic training culminating in a Ph.D. in areas related to rural development and livelihood economics, where he developed rigorous quantitative and qualitative competencies that now guide his scholarly work and community engagement. His professional experience includes serving as a Lecturer at the University of Dar es Salaam, where he has taught, supervised, and mentored students in development economics, agricultural systems, and rural policy analysis while actively contributing to departmental research initiatives and institutional outreach programs. Dr. John Msinde’s research interests span climate variability impacts, agricultural technology adoption, off-farm employment dynamics, sustainable agricultural practices, livelihood resilience, and poverty reduction mechanisms in smallholder farming communities, particularly within agro-ecological regions of Tanzania. His research skills include socioeconomic data analysis, econometric modelling, survey design, impact assessment, and interdisciplinary collaboration, enabling him to produce high-quality publications indexed in reputable platforms such as Scientific Reports, Physics and Chemistry of the Earth, and several development-oriented international journals. Dr. John Msinde has earned recognition for his contributions through participation in international research projects, collaborative field studies, and scholarly engagements that highlight his commitment to advancing inclusive development. His awards and honors reflect his growing academic visibility and his role in generating policy-relevant insights that inform sustainable agricultural strategies and poverty-reduction programs. With a citation record of 45 citations and an h-index of 3, he continues to strengthen his scholarly presence while contributing to impactful research on livelihood systems, social capital, climatic suitability, and labor dynamics in rural communities. Dr. John Msinde’s work demonstrates a strong alignment between theoretical knowledge and real-world applications, positioning him as a researcher dedicated to improving the socioeconomic conditions of vulnerable populations. Looking forward, he aims to expand his international collaborations, advance publications in higher-impact global journals, and further integrate innovative analytical techniques into his research. Overall, Dr. John Msinde’s contributions reflect academic rigor, practical relevance, and a sustained commitment to improving agricultural and livelihood systems across developing regions, making him a valuable contributor to global development discourse.

Academic Profile: Google Scholar

Featured Publications:

  1. Beteri, J., Lyimo, J. G., & Msinde, J. V. (2024). The influence of climatic and environmental variables on sunflower planting season suitability in Tanzania. Scientific Reports. Citations: 15.

  2. Haji, A. K., Salehe, S. S., & Msinde, J. (2018). Adoption of rainfed paddy production technologies among smallholder farmers: A case of Central District-Zanzibar, Tanzania. SCIENCEDOMAIN International. Citations: 6.

  3. Msinde, J., Urassa, J. K., & Nathan, I. (2016). Off-farm employment and income poverty in favourable agro-climatic areas of Tanzania: Evidence from Kilombero Valley. International Institute for Science, Technology and Education (IISTE). Citations: 5.

  4. Mugula, J. J., Ahmad, A. K., Msinde, J., & Kadigi, M. (2023). Impacts of sustainable agricultural practices on food security, nutrition, and poverty among smallholder maize farmers in Morogoro region, Tanzania. African Journal of Empirical Research. Citations: 3.

  5. Beteri, J., Msinde, J. V., & Lyimo, J. G. (2025). Spatiotemporal change of climatic suitability in sunflower-growing areas of Tanzania. Physics and Chemistry of the Earth. Citations: 2.

 

Qingling Qu | Global Health | Editorial Board Member

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Dr. Qingling Qu | Global Health | Editorial Board Member

Dr. Qingling Qu | Global Health | Doctor at Yichun University | China

Dr. Qingling Qu is an emerging scholar in the field of sports biomechanics and human movement science, recognized for her growing contributions to research on gait stability, motor control, and performance enhancement across martial arts, dance, and athletic populations. Dr. Qingling Qu completed her advanced academic training at Jeonbuk National University, where she strengthened her methodological expertise in biomechanics and movement analysis, establishing a foundation for international collaborative research. Her professional experience includes serving as a Dr in the Department of Physical Education at Yichun University, where she contributes to both teaching and research aimed at improving athletic performance, movement safety, and evidence-based physical education practices. Dr. Qingling Qu’s research interests span gait and dynamic stability, martial arts biomechanics, human balance control, digital learning tools in sports education, and the effects of multitasking on motor performance. Across these domains, she has demonstrated strong research skills in experimental design, motion analysis, kinetic and kinematic assessment, comparative motor performance evaluation, and interdisciplinary collaboration. Her published works appear in reputable peer-reviewed journals including Annals of Human Biology, Sports Biomechanics, Physical Culture and Sport. Studies and Research, and Molecular & Cellular Biomechanics, reflecting her commitment to advancing scientific understanding of movement patterns and injury-risk mechanisms. Throughout her early career, Dr. Qingling Qu has been involved in international research collaborations with multidisciplinary teams across Korea, China, and other regions, highlighting her ability to contribute effectively to global scientific projects. Although she is at an early stage in building her academic portfolio, her publications demonstrate increasing scholarly visibility and engagement with high-quality journals indexed in Scopus and Crossref. Her emerging academic honors include contributions to funded research groups, co-authorship in leading biomechanics studies, and recognition through departmental appointments supporting sports-science innovation. Moving forward, Dr. Qingling Qu aims to expand her research influence through additional publications, professional memberships, leadership activities, and collaborations integrating advanced technologies such as wearable sensors and AI-enhanced movement analysis. With a strong foundation in scientific inquiry and a clear trajectory of research growth, Dr. Qingling Qu is positioned to make substantial future contributions to biomechanics, physical education, and human performance science.

Academic Profile: ORCID

Featured Publications:

  1. Zhang, J., Kim, Y., Qu, Q., & Kim, S. (2025). Effects of different Taekwondo practices on biomechanics of balance and control during kick technique. Annals of Human Biology.

  2. Zhang, J., Qu, Q., Zhu, B., Zhao, Z., & Kim, S. (2025). Microlecture assistance during university martial arts classes improves students’ learning motivation and endeavors. Physical Culture and Sport. Studies and Research.

  3. Qu, Q., Tang, X., Qiu, X., Kim, Y., Zhang, J., & Kim, S. (2025). Long-term dance training alters the likelihood of slips and trips. Molecular & Cellular Biomechanics.

  4. Dong, M., Li, M., Qu, Q., Kim, Y., & Kim, S. (2025). Arm slot angles affect elbow and shoulder joint torque in elite college pitchers. Sports Biomechanics.

  5. Qu, Q., Wu, C., Xu, Y., Lu, Y., Zhang, J., & Kim, S. (2024). Effects of mobile phone task engagement on gait and dynamic stability during stair ascent and descent. Molecular & Cellular Biomechanics.

 

 

Noelle Molé Liston | Medicine | Editorial Board Member

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Prof. Noelle Molé Liston | Medicine | Editorial Board Member

Prof. Noelle Molé Liston | Medicine | Professor at New York University | United States

Prof Noelle Molé Liston is a respected female scholar whose academic career reflects deep engagement with social sciences, cultural theory, and interdisciplinary health research, establishing her as a thought-leading voice on the sociopolitical dimensions of medicine, education, and inequality. She completed her Ph.D. from a globally recognized institution, where her early research laid the foundation for her long-term academic trajectory focused on ethnography, gender studies, and the cultural shaping of health systems. Across her professional journey, she has served in teaching, mentoring, and research roles at internationally reputed universities, contributing significantly to both undergraduate and postgraduate academic development. Her professional experience includes designing and teaching advanced courses on social theory, medical anthropology, qualitative inquiry, and the cultural politics of science and technology, positioning her as a multidisciplinary scholar capable of bridging the humanities and health education. Her research interests include medical metaphors, reproductive politics, global health inequalities, cultural narratives within medical training, and the intersection of language, identity, and institutional power. She is particularly known for her work on metaphors in medical education, highlighted in one of her notable Scopus-indexed publications in Social Science & Medicine, which reflects her ability to address systemic inequities through critical scholarship. She possesses strong research skills in ethnography, narrative analysis, qualitative fieldwork, policy interpretation, and interdisciplinary integration, with her work being cited in scholarly discourse across health studies and cultural anthropology. Her academic profile lists multiple Scopus-indexed publications, a verified Scopus ID (57709521300), and international research collaborations demonstrating her active engagement with global academic communities. Prof Noelle Molé Liston has been acknowledged for her contributions through institutional recognitions, invited talks, and participation in global scholarly dialogues centered on social justice and educational reform. Her achievements also include co-authorship networks, editorial contributions, and leadership in thematic research clusters focusing on inequality and health. She continues to expand her research footprint by pursuing projects addressing emerging issues in medical education, social vulnerability, and the cultural shaping of scientific knowledge. With her commitment to advancing equitable, inclusive, and critical approaches to health and society, Prof Noelle Molé Liston remains an influential scholar whose work will continue to shape interdisciplinary discourse, mentor new researchers, and strengthen global academic conversations toward creating more just and culturally responsive health education systems.

Academic Profile: Scopus

Featured Publications:

  1. Molé Liston, N. (2025). From egg & sperm to reconceiving medical education: Why teaching about metaphor is essential to remedy injustice. Social Science & Medicine. Citations: 2

 

 

Wenchao Yang | Autonomous Systems | Editorial Board Member

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Mr. Wenchao Yang | Autonomous Systems | Editorial Board Member

Mr. Wenchao Yang | Autonomous Systems | Zhengzhou University of light industry | China

Mr. Wenchao Yang is a seasoned engineer-researcher whose academic journey encompasses a Ph.D. from a prominent Chinese university, where he cultivated his expertise in real-time scheduling, production-logistics collaboration, and industrial informatics. He has held research and teaching positions at leading institutions, contributing both to theoretical foundations and practical deployments in smart manufacturing labs and edge-computing environments. His professional experience spans leading international research projects in digital twin systems, human–machine collaboration, and adaptive scheduling across factories, integrating interdisciplinary teams from automation, AI, and operations research. Mr. Yang’s research interests center on digital twin–enabled scheduling, human-in-the-loop manufacturing, edge-computing for industry, and adaptive real-time decision-making. He is highly skilled in modeling and optimization, information-theoretic scheduling, machine learning for resource management, edge systems, and swarm coordination. His work has earned recognition in the form of peer-reviewed journal awards and invitations to collaborate internationally, reflecting both his academic impact and industrial relevance. Among his honors, he has been acknowledged in high-impact IEEE and MDPI venues, and he is an active member of professional societies such as the IEEE. In conclusion, Wenchao Yang combines deep theoretical understanding with practical engineering insight, and his ongoing contributions to digital-twin systems and adaptive scheduling stand to shape the future of intelligent, human-centric industrial systems.

Academic Profile: ORCID 

Featured Publications:

  1. Yang, Wenchao, Li, S., Luo, G., Li, H., & Wen, X. (2025). A Real-Time Human–Machine–Logistics Collaborative Scheduling Method Considering Workers’ Learning and Forgetting Effects. Applied System Innovation, 8(2), 40.

  2. Yang, Wenchao, Li, W., Cao, Y., Luo, Y., & He, L. (2020). An Information Theory Inspired Real-Time Self-Adaptive Scheduling for Production-Logistics Resources: Framework, Principle, and Implementation. Sensors, 20(24), 7007.

  3. Yang, Wenchao, Li, W., Cao, Y., Luo, Y., & He, L. (2020). Real-Time Production and Logistics Self-Adaption Scheduling Based on Information Entropy Theory. Sensors, 20(16), 4507.

  4. Luo, G., Li, S., Yang, Wenchao, Zhang, B., Tian, Y., & Wen, X. (2025). Swarm-Consensus-Based Human-Machine-Logistics Collaborative Scheduling Method. In Proceedings of the 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 2496–2501.