Peter Waldner | Chemistry | Best Research Article Award

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Assist. Prof. Dr. Peter Waldner | Chemistry | Best Research Article Award

University of Leoben | Austria

Assist. Prof. Dr. Peter Waldner is an established researcher in geochemistry and materials thermodynamics, with a strong focus on phase equilibria, Gibbs energy modeling, and high-temperature mineral systems. His scholarly output comprises 32 research documents, which have received 636 citations from 501 citing publications, resulting in an h-index of 12, indicating consistent academic influence. His work centers on the Cu–Fe–S system, addressing solid and liquid solution behavior through advanced thermodynamic modeling techniques. Notable contributions include Gibbs energy modeling of high-temperature bornite and intermediate solid solutions, enabling accurate calculation of phase equilibria at elevated temperatures. Published in leading journals such as Chemical Geology and Journal of Phase Equilibria and Diffusion, his research provides critical insights into mineral stability, metallurgical processes, and geochemical systems. Overall, his work significantly advances the understanding of thermodynamic properties governing complex sulfide systems and their applications in Earth and materials sciences.

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Top Publications

Mohammad Afikuzzaman | Mathematics | Best Faculty Award

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Dr. Mohammad Afikuzzaman | Mathematics | Best Faculty Award

Adelaide University | Australia

Dr. Mohammad Afikuzzaman’s research profile reflects a strong and sustained contribution to applied mathematical modeling and computational simulations, with particular emphasis on fluid mechanics, magnetohydrodynamics, nanofluids, heat and mass transfer, and multicomponent alloy diffusion. The scholarly output includes 18 indexed documents with 318 citations and an h-index of 11, alongside broader visibility on Google Scholar reporting 431 total citations and an h-index of 12 (August 2025). The body of work comprises 22 peer-reviewed journal articles, 7 international conference presentations (oral and poster), and 4 book chapters/books, with an additional 6 manuscripts currently under review. Research contributions demonstrate methodological rigor, advanced numerical and theoretical modeling, and practical relevance, supported by extensive collaboration with industry, government, and academic partners to promote innovation and interdisciplinary engagement. Publications appear in high-impact journals such as Scripta Materialia, Journal of Phase Equilibria and Diffusion, Nanoscale Advances, Journal of Molecular Liquids, and Arabian Journal for Science and Engineering, highlighting both depth and breadth of scientific influence.

Citation Metrics (Scopus)

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318

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Featured Publications

Yang Li | Engineering | Research Excellence Award

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Dr. Yang Li | Engineering | Research Excellence Award

Qilu Medical University | China

Dr. Yang Li is an active researcher in advanced manufacturing and biomedical engineering, with a strong focus on high-temperature additive manufacturing, micromachining, and the mechanical behavior of advanced materials. The research portfolio comprises 28 scholarly documents, which have collectively received 338 citations, reflecting steady academic influence, and an h-index of 11, indicating consistent research quality and impact. Key contributions include pioneering studies on surface-modified CF/PEEK and PEEK composite structures fabricated via high-temperature air-assisted 3D printing for potential implant applications, published in leading journals such as Materials & Design and the Journal of the Mechanical Behavior of Biomedical Materials. Additional influential work addresses micromilling of Ti-6Al-4V alloys, focusing on high-aspect-ratio thin walls, dimensional accuracy, and online compensation systems, contributing to precision manufacturing science. Overall, the research output demonstrates a strong integration of materials science, mechanical performance analysis, and advanced manufacturing technologies, with growing relevance in biomedical and high-precision engineering applications.

 

Citation Metrics (Scopus)

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Featured Publications

Yizhao Li | Engineering | Research Excellence Award

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Ms. Yizhao Li | Engineering | Research Excellence Award

Shanghai University | China

Yizhao Li is a researcher specializing in biomechanics, biomedical instrumentation, and implant-related mechanics, with a research portfolio spanning orthopaedic implants, biofidelic physical models, and advanced sensing technologies. The research work focuses on in vitro wear testing of ankle prostheses, energy harvesting sensor packages for knee implants, knee joint contact mechanics related to meniscus root tears, and cadaver-based experimental validation of implant performance and durability. Earlier research contributions include the development of biofidelic instrumented headforms for head injury biomechanics, miniature optical fiber sensors for rapid intracranial pressure measurement, and image-based analysis of fuel–air explosive cloud growth. The research demonstrates strong integration of experimental mechanics, structural design, simulation, sensing, and measurement, with applications in injury biomechanics, orthopaedic engineering, and safety device evaluation. The scholarly output comprises peer-reviewed journal articles published in leading journals such as Journal of Biomechanics, Annals of Biomedical Engineering, Journal of Mechanical Behavior of Biomedical Materials, Journal of Biomechanical Engineering, and IEEE Transactions on Instrumentation and Measurement, along with multiple international conference publications. According to Google Scholar metrics, the research has received 84 citations, with an h-index of 5 and an i10-index of 3, reflecting growing impact and consistent contributions to biomechanics, biomedical engineering, and measurement science.

 

Citation Metrics (Google Scholar)

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Featured Publications

Offline and online measurement of the geometries of train wheelsets: A review.
– IEEE Transactions on Instrumentation and Measurement, 2022

 

Donglin Zu | Physics and Astronomy | Research Excellence Award

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Prof. Donglin Zu | Physics and Astronomy | Research Excellence Award

Peking University | China

Prof. Donglin Zu is a distinguished physicist whose career spans pioneering contributions to electromagnetics, nuclear magnetic resonance (NMR), magnetic resonance imaging (MRI), and, more recently, photon structure theory. His early work involved teaching electromagnetics and developing an independent NMR magnetometer, along with solving key control challenges in high-voltage electrostatic accelerators. His international research experience includes studying RF superconducting cavities at Cornell University, followed by leading a major project on the practical design of niobium cavities. Over two decades, he made significant advances in MRI engineering, contributing to wavelet-based medical image fusion, high-resolution NMR spectral reconstruction, shim coil design, permanent-magnet MRI optimization, and low-noise preamplifier development. He authored influential textbooks on electrodynamics and MRI, widely adopted in advanced training and research. His extensive publication record encompasses innovations in superconducting magnets, ferromagnetic shimming, pulse sequence optimization, image contrast mechanisms, and magnet design methodologies. As a long-term consultant to MRI industries, he helped translate theoretical principles into practical imaging technologies. In recent years, his research has shifted toward foundational physics, producing breakthrough models on single-photon structures, standing-wave photon behavior in constrained spaces, and multi-photon composite systems, marking a new phase of theoretical advancement with impactful emerging publications.

Profile : Orcid

Featured Publications

Zu, D. (2025). Standing wave photon structures in constraint spaces. Photonics.

Zu, D. (2025). Standing wave photon structures in constraint spaces [Preprint].

Zu, D. (2025). Single photon structure model and multi-photon composite monomer. Optics Express.

Zu, D. (2016). Electrodynamics (Rev. ed.). Tsinghua University Press.

Zu, D. (2015). Nuclear magnetic resonance imager. Science Press.

Zu, D., & Gao, J. (2014). Nuclear magnetic resonance imaging. Peking University Press.

Liu, W., Casanova, F., Blümich, B., & Zu, D. (2012). An efficacious target-field approach to design shim coils for Halbach magnet of mobile NMR sensors. Applied Magnetic Resonance.

Zhao, X., Wen, Z., Huang, F., Lu, S., Wang, X., Hu, S., Zu, D., & Zhou, J. (2011). Saturation power dependence of amide proton transfer image contrasts in human brain tumors and strokes at 3 T. Magnetic Resonance in Medicine.

Cao, X., Zu, D., Zhao, X., Fan, Y., & Gao, J. (2011). The design of a low-noise preamplifier for MRI. Science China Technological Sciences.

Tang, X., Zu, D., Wang, T., & Han, B. (2010). An optimizing design method for a compact iron-shielded superconducting magnet for use in MRI. Superconductor Science and Technology.

Tang, X., Li-Ming, H., & Zu, D.-L. (2010). Active ferromagnetic shimming of the permanent magnet for magnetic resonance imaging scanner. Chinese Physics B.

Zhao, X., Chen, M., Zhang, C., Hu, S., & Zu, D. (2010). Experimental evaluation of dual acceptance window weighting function for right coronary MR angiography at 3.0 T. Magnetic Resonance Imaging.

Zu, D., Liming, H., Xueming, C., & Xin, T. (2010). Analysis on background magnetic field to generate eddy current by pulsed gradient of permanent-magnet MRI. Science China Series E.

Verónica Córdoba | Chemical Engineering | Best Researcher Award

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Prof. Dr. Verónica Córdoba | Chemical Engineering | Best Researcher Award

Universidad Nacional del Centro de la Provincia de Buenos Aires | Argentina

Prof. Dr. Verónica Córdoba is a researcher whose work focuses on bioenergy, anaerobic digestion, biomethane modelling, and environmental sustainability, with a research portfolio that has earned 381 citations, an h-index of 8, and 8 i10-index publications, reflecting a steadily growing scholarly impact. She has contributed extensively to understanding methane production dynamics from diverse biomass sources, including swine wastewater, cheese whey, macroalgae, third-generation biomass, and agricultural residues. Her publications span high-impact journals with studies on mixture design for anaerobic co-digestion, neural-network-based prediction of biomethane production, thermal behavior of biofuel feedstocks, activated carbon production from biomass waste, and long-term methane emission modelling from waste treatment processes. Her involvement in R&D Project 03/E208 (2023–2025) focuses on the valorization of lignocellulosic residues for low-emission energy scenarios, underscoring her commitment to circular bioeconomy strategies. She also contributes to academic development through the supervision of doctoral fellows working on methane modeling and biomass conversion systems. Additional works include analyses of greenhouse gas emissions in waste management, kinetics of methane generation, renewable fuel drying behavior, and theoretical–practical assessments of electricity generation from biogas. Across more than a decade of scientific output, she has advanced sustainable energy research through rigorous modelling, experimental analysis, and interdisciplinary collaboration.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Córdoba, V., & Ottolina, G. (2025). Anaerobic co-digestion of swine wastewater, cheese whey and organic waste: Performance optimization through mixture design. Biomass.

Córdoba, V., Bavio, M., & Acosta, G. (2024). Biomethane production modelling from third-generation biomass. Renewable Energy.

Córdoba, V. E., Mussi, J., De Paula, M., & Acosta, G. G. (2023). Prediction of biomethane production of cheese whey by using artificial neural networks. IEEE Latin America Transactions.

Córdoba, V., Manzur, A., & Santalla, E. (2023). Thermal behaviour and emission characteristics of Arundo donax L. as potential biofuel. BioEnergy Research.

Jerez, F., Ramos, P. B., Córdoba, V. E., Ponce, M. F., Acosta, G. G., & Bavio, M. A. (2023). Yerba mate: From waste to activated carbon for supercapacitors. Journal of Environmental Management.

Córdoba, V. E., & Santalla, E. M. (2022). Estimation of long-term methane emissions from mechanical-biological treatment waste through biomethane potential test. Environmental Technology.

Córdoba, V., Manzur, A., & Santalla, E. (2022). Drying kinetics and mathematical modelling of Arundo donax L. canes, a potential renewable fuel. Research in Agricultural Engineering.

Ibarlucía, D. G., Santalla, E. M., & Córdoba, V. E. (2021). Evaluation of biomethane potential and kinetics modelling of green macroalgae from the South Atlantic Sea: Codium sp. and Ulva sp. Environmental Chemistry.

Córdoba, V., Fernández, M., & Santalla, E. (2018). The effect of substrate/inoculum ratio on the kinetics of methane production in swine wastewater anaerobic digestion. Environmental Science and Pollution Research.

Blanco, G., Santalla, E., Córdoba, V., & Levy, A. (2017). Generación de electricidad a partir de biogás capturado de residuos sólidos urbanos: Un análisis teórico-práctico. Report.

Blanco, G., Córdoba, V., Baldi, R., Fernández, M., & Santalla, E. (2016). Outcomes of the Clean Development Mechanism in Argentina. American Journal of Climate Change.

Córdoba, V., Colavolpe, M. B., Fernández, M., Santalla, E., & Albertó, E. (2016). Potential methane production of spent sawdust used in the cultivation of Gymnopilus pampeanus. Journal of Environmental Chemical Engineering.

Córdoba, V., Fernández, M., & Santalla, E. (2016). The effect of different inoculums on anaerobic digestion of swine wastewater. Journal of Environmental Chemical Engineering.

Santalla, E., Córdoba, V., & Blanco, G. (2013). Greenhouse gas emissions from the waste sector in Argentina in business-as-usual and mitigation scenarios. Journal Article.

Yendouhamtchié Nadiedjoa | Agricultural and Biological Sciences | Best Researcher Award

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Dr. Yendouhamtchié Nadiedjoa | Agricultural and Biological Sciences | Best Researcher Award

Shandong Agricultural University | Togo

Dr. Yendouhamtchié Nadiedjoa is a dedicated researcher in animal sciences, focusing on sustainable nutrition strategies that enhance poultry productivity while reducing dependence on conventional feed resources. His work centers on developing ecological, cost-effective, and long-term sustainable alternatives that do not compete with human food systems, thereby supporting both food security and environmental protection. His research interests include poultry science and physiology, stress responses in birds, energy metabolism, efficient production systems, and nutritional regulation aimed at improving overall animal health. He conducts research through international academic collaborations, contributing to advancements in non-grain feed resource utilization and environmentally sound agricultural practices. A key contribution of his scholarly work is the investigation of maggot oil derived from the Black Soldier Fly (Hermetia illucens) as an innovative feed component in poultry production. In a 2025 study published in Animals, he examined the effects of in ovo injection timing and dosing of maggot oil on hatching success, growth performance, and biochemical parameters in broiler chicks. This research provided valuable insights into the potential of insect-based oils to enhance early-life development and support sustainable poultry nutrition. His contributions continue to promote healthier, more efficient, and environmentally responsible poultry production systems.

Profile : Orcid

Featured Publication

Nadiedjoa, Y., Wang, X., Attivi, K., Okai, M. A., Xin, Q., Mijiyawa, A., Maa Maa, C. T., Zhao, J., Jiao, H., Agboka, K., et al. (2025). The effect of in ovo injection time and dose of maggot oil from Hermetia illucens on hatching rate, growth performance, and biochemical parameters of broiler chicks. Animals, 15(21), 3115.

Zhang Zhenqian | Neuroscience | Best Researcher Award

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Mr. Zhang Zhenqian | Neuroscience | Best Researcher Award

University of Toyama | Japan

Mr. Zhang Zhenqian is a dedicated researcher whose work bridges artificial intelligence, machine learning, and meteorology, with an emphasis on developing advanced neural network models for predictive analytics. His recent publication, “RD2: Reconstructing the Residual Sequence via Under Decomposing and Dendritic Learning for Generalized Time Series Predictions,” featured in Neurocomputing (October 2025), showcases his innovative approach to enhancing time series forecasting accuracy through the integration of dendritic learning mechanisms and residual sequence reconstruction. Collaborating with Houtian He, Zhenyu Lei, Zihang Zhang, and Shangce Gao, Mr. Zhang contributes to advancing the computational intelligence field by addressing challenges in dynamic data modeling and predictive reliability. His research explores the intersection of data-driven modeling and environmental systems, offering valuable insights for improving real-world forecasting, particularly in meteorological and environmental applications. With a growing scholarly presence and contributions recognized through peer-reviewed international publications, Mr. Zhang exemplifies a new generation of researchers committed to interdisciplinary innovation. His work not only strengthens the theoretical foundations of artificial intelligence but also demonstrates its transformative potential in understanding and managing complex natural and engineered systems.

Profile : Orcid

Featured Publication

Zhang, Z., He, H., Lei, Z., Zhang, Z., & Gao, S. (2025). RD2: Reconstructing the residual sequence via under decomposing and dendritic learning for generalized time series predictions. Neurocomputing, 131867.

Diogo Santiago | Computer Science | Best Researcher Award

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Mr. Diogo Santiago | Computer Science | Best Researcher Award

Oracle | Brazil

Mr. Diogo Santiago is a highly accomplished technology professional with extensive experience spanning software engineering, big data, and artificial intelligence. Beginning his career in 2009 as a software engineer developing major e-commerce platforms in Brazil, he transitioned into data engineering and science, mastering technologies like Hadoop, Spark, Hive, and Sqoop for large-scale data processing and migration. Since 2018, he has specialized in data science and AI, contributing to diverse projects in computer vision, anomaly detection, logistics optimization, and generative AI, including GAN and diffusion model applications for virtual try-on systems. As an AI Architect at Oracle for LATAM, he designs advanced AI architectures, supports clients with resource planning, and enhances model deployment efficiency through GPU optimization and large language model serving using vLLM and SGLang. His prior roles at Lambda3, Tivit, and Qintess involved developing ML models, data pipelines, and automation systems using cloud technologies such as GCP, AWS, and OCI. With multiple postgraduate qualifications in Big Data and Machine Learning for Finance, along with a Master’s in Medical Texture Imaging, he exemplifies innovation and leadership in merging AI research with scalable enterprise solutions.

Profile : Orcid

Featured Publication

Adorno, P. L. V., Jasenovski, I. M., Santiago, D. F. D. M., & Bergamasco, L. (2023, May 29). Automatic detection of people with reduced mobility using YOLOv5 and data reduction strategy. Conference paper.

 

Leila Celin Nascimento | Engineering | Women Research Award

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Dr. Leila Celin Nascimento | Engineering | Women Research Award

Instituto Federal do Espirito Santo | Brazil

Dr. Leila Celin Nascimento is a distinguished researcher in Civil and Environmental Engineering, with a Ph.D. in Materials Engineering from Universidade Estadual Norte Fluminense (2024), a Master’s degree in Environmental Engineering from Universidade Federal do Espírito Santo (2002), and a Bachelor’s degree in Civil Engineering from the same institution (2000). She currently serves as a professor in technical and technological education at Instituto Federal do Espírito Santo (IFES – Campus Vitória). Her research expertise spans Civil Engineering, with strong emphasis on Environmental and Materials Engineering, focusing on coating mortars, solid waste management, construction materials, and construction technology. She has contributed to four scholarly publications, with a total of 37 citations and an h-index of 2. Dr. Nascimento has led and participated in research projects evaluating solid waste management infrastructure and analyzing pathological manifestations in buildings, reflecting her applied research impact. In addition to research, she has extensive teaching experience in water resources, environmental planning, geology, water supply, and solid waste, as well as professional development in scientific writing, gamification in education, and hybrid learning methods. Her work demonstrates a commitment to advancing sustainable construction practices, integrating technical education with environmental and materials research, and mentoring students in applied scientific inquiry, making her a significant contributor to the fields of civil and environmental engineering.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Nascimento, L. C., Baptista Junior, G., Xavier, G. C., Azevedo, A. R. G. de, Monteiro, S. N., & Alledi, C. T. D. B. (2025). Performance of wood bottom ash as a replacement for Portland cement in coating mortars. Journal of Materials Research and Technology.

Baptista Junior, G., Nascimento, L. C., Xavier, G. C., Monteiro, S. N., Vieira, C. M. F., Marvila, M. T., & Alledi, C. T. D. B. (2024). Durability for coating mortars: Review of methodologies. Journal of Materials Research and Technology.

Nascimento, L. C., Baptista Junior, G., Xavier, G. C., Monteiro, S. N., Vieira, C. M. F., Azevedo, A. R. G. de, & Alexandre, J. (2023). Use of wood bottom ash in cementitious materials: A review. Journal of Materials Research and Technology.

Nascimento, L. C., Baptista Junior, G., Nascimento, L. C., & Santos, G. F. (2021). Manifestações patológicas causadas por sistemas de climatização no IFES Campus Vitória. Revista Ifes Ciência, 7(1).