Dr. Qingyong Li | Composite Materials | Research Excellence Award

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Dr. Qingyong Li | Composite Materials | Research Excellence Award

Guangdong University of Petrochemical Technology | China

Dr. Qingyong Li is an emerging researcher in composite materials and environmental catalysis whose work has contributed significantly to advanced material design, heterogeneous catalysis, and sustainable pollutant treatment technologies. With a growing research footprint reflected in 453 citations across 370 citing documents, he has established a solid academic reputation supported by 11 scientific documents and a steadily rising h-index of 8, demonstrating both impact and consistency in high-quality research output. As a faculty member in the School of Environmental Science and Engineering at Guangdong University of Petrochemical Technology, Dr. Li focuses on the development of functional composite materials, catalytic nanostructures, and clay-based or mineral-supported metal quantum dots aimed at efficient degradation of persistent organic pollutants. His research integrates composite chemistry, environmental engineering, photocatalysis, and advanced oxidation processes, with particular emphasis on peroxymonosulfate and peroxydisulfate activation mechanisms, oxygen-vacancy engineering, and visible-light-driven catalytic systems. Dr. Li’s contributions include the design of kaolin-supported cobalt nanostructures, red-mud-derived layered composites, magnetic oxide systems, and mixed metal catalysts with enhanced activity and stability. His publications in respected international journals highlight his expertise in mechanochemical synthesis, pollutant mineralization pathways, catalyst reusability, and structure–function relationships in composite materials. Through interdisciplinary collaborations, he has advanced the understanding of composite catalyst behavior, free-radical generation, charge separation efficiency, and surface-adsorption kinetics, offering practical solutions for wastewater treatment and environmental remediation. Dr. Li’s research not only deepens theoretical insights into catalytic mechanisms but also provides scalable strategies for transforming industrial waste into high-value materials, demonstrating strong alignment with global sustainability priorities. His rapidly increasing citation profile, innovative approaches to catalyst development, and commitment to environmental materials research position him as an impactful and promising scientist deserving of recognition through the Research Excellence Award.

Profiles: Scopus | Orcid

Featured Publications

Li, Q., Yan, Z., Yang, X., Li, J., Li, R., Qiu, B., Wang, N., & Wang, S. (2026). Natural layered kaolin supported cobalt quantum dots for rapid degradation of carbamazepine via peroxymonosulfate activation: Performance and mechanism. Chemical Engineering Science.

Li, Q., Zhang, J., Xu, J., Cheng, Y., Yang, X., He, J., Liu, Y., Chen, J., Qiu, B., Zhong, Y., et al. (2024). Magnetic CuFe₂O₄ nanoparticles immobilized on mesoporous alumina as highly efficient peroxymonosulfate activator for enhanced degradation of tetracycline hydrochloride. Separation and Purification Technology.

Li, Q. (2022). Photocatalysis activation of peroxydisulfate over oxygen vacancies-rich mixed metal oxide derived from red mud-based layered double hydroxide for ciprofloxacin degradation. Separation and Purification Technology.

Ba, J., Wei, G., Zhang, L., Li, Q., Li, Z., & Chen, J. (2021). Preparation and application of a new Fenton-like catalyst from red mud for degradation of sulfamethoxazole. Environmental Technology.

Li, Q. (2021). Novel step-scheme red mud based Ag₃PO₄ heterojunction photocatalyst with enhanced photocatalytic performance and stability in photo-Fenton reaction. Chemical Engineering Journal.

Dr. Daniel Osezua Aikhuele | Material Failure Analysis | Research Excellence Award

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Dr. Daniel Osezua Aikhuele | Material Failure Analysis | Research Excellence Award

University of Port Harcourt | Nigeria

Dr. Daniel Osezua Aikhuele is a distinguished scholar in Material Failure Analysis whose extensive body of work has significantly advanced the understanding of reliability, safety, and intelligent decision-making in complex engineering systems. With an impressive research footprint reflected in 530 citations generated by 434 documents, 71 published documents, and a robust h-index of 14, he is recognized for consistently producing high-impact contributions that bridge theoretical innovation with practical engineering solutions. As an Associate Professor at the University of Port Harcourt, he has built a reputation for excellence in manufacturing engineering, intelligent reliability modeling, fault diagnosis, product design, and sustainable materials, using advanced fuzzy logic, multi-criteria decision-making approaches, and data-driven techniques that address reliability challenges in modern industrial environments. His scholarly output spans journals, book chapters, and international conferences, demonstrating his leadership in developing hybrid fuzzy systems, reliability-centered models, renewable-energy decision frameworks, and intelligent predictive tools for mechanical components, offshore systems, and wind-energy technologies. Beyond research, Dr. Aikhuele plays an active role in the global engineering community as a reviewer for major journals and a member of several professional bodies, contributing to quality assurance and scientific advancement across multiple disciplines. He has supervised numerous postgraduate researchers and collaborated widely on interdisciplinary projects that enhance industrial safety, optimize energy systems, and support sustainable engineering practices. His commitment to academic excellence, combined with impactful teaching and mentorship, has earned him recognition as a dynamic leader whose contributions continue to influence material behavior assessment, reliability optimization, and the design of resilient engineering systems.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Azubuike, G. D., Aikhuele, D. O., & Nwosu, H. U. (2025). Development of an optimization model for reducing energy utilization and to increase biomass yield in a brewery process. Process Integration and Optimization for Sustainability.

Diemuodeke, O. E., Vera, D., Ojapah, M. M., Nwachukwu, C. O., Nwosu, H. U., Aikhuele, D. O., Ofodu, J. C., & Nuhu, B. S. (2024). Hybrid solar PV–agro-waste-driven combined heat and power energy system as feasible energy source for schools in Sub-Saharan Africa. Biomass, 4(4), 67.

Aikhuele, D. O., & Diemuodeke, O. E. (2024). Computational analysis of stiffness reduction effects on the dynamic behaviour of floating offshore wind turbine blades. Journal of Marine Science and Engineering, 12(10), 1846.

Aikhuele, D. O., & Sorooshian, S. (2024). A proactive decision-making model for evaluating the reliability of infrastructure assets of a railway system. Information, 15(4), 219.

Onukwube, C. U., Aikhuele, D. O., & Sorooshian, S. (2024). Development of a fault detection and localization model for a water distribution network. Applied Sciences, 14(4), 1620.

Mr. Fawad Khan | Smart Materials | Best Researcher Award

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Mr. Fawad Khan | Smart Materials | Best Researcher Award

Shenzhen Institutes of Advanced Technology | Chinese Academy of Sciences | China

Mr. Fawad Khan is a promising researcher at the intersection of smart materials, safe robotics, reinforcement learning, and human–robot collaboration, recognized for his innovative contributions to the development of intelligent, safety-aware autonomous systems. As a PhD Researcher at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, he focuses on advancing constrained reinforcement learning frameworks that enable robots to operate reliably and safely alongside humans in dynamic and safety-critical environments such as collaborative manufacturing, warehouse automation, and assistive robotics. His scholarly output includes 3 research documents, and he has contributed to journal articles, conference papers, and manuscripts addressing precision grasping, adaptive safety constraints, multi-object manipulation, and safety-critical coordination. His research introduces novel approaches that combine tactile–visual perception, adaptive constraint satisfaction, and multi-modal learning to significantly reduce safety violations while maintaining high task performance in robotic systems. He has designed benchmark platforms for safe robotic manipulation and expanded the capabilities of existing tools such as Safety Gym to enable high-fidelity evaluation of robotic arms with multiple degrees of freedom. Prior to his doctoral research, Mr. Khan gained industry experience as a Python developer and data analyst, where he automated logistics operations, designed data-driven decision-support tools, and streamlined complex workflows, demonstrating his ability to integrate practical engineering solutions with theoretical AI advancements. His technical expertise spans reinforcement learning algorithms, constrained optimization, robotics simulation environments, computer vision, multi-modal neural networks, and high-performance computing frameworks. He actively collaborates with interdisciplinary teams working on intelligent manufacturing, safe autonomy, and human-centered robotics. With strong analytical skills, a clear research vision, and a growing academic footprint, Mr. Fawad Khan represents a new generation of AI and robotics researchers dedicated to creating safer, smarter, and more adaptive robotic systems, making him a highly deserving candidate for the Best Researcher Award.

Profile: Scopus

Featured Publications

Khan, F., Feng, W., Wang, Z., Huang, T., Xiao, L., et al. (2025). Safe reinforcement learning for objects manipulation in safety-critical coordinated tasks. In ISARC: Proceedings of the International Symposium on Automation and Robotics in Construction (Vol. 42, pp. 334–341). IAARC Publications.

Khan, F., et al. Reinforcement learning for precision grasping and safety-critical coordination in a robotic arm. Journal of Intelligent Service Robotics.

Khan, F., et al. Safe reinforcement learning for vision-based robotic manipulation in human-centered environment. Journal of Intelligent Robotics and Applications.

Khan, F., et al. Safe reinforcement learning for multi-object robotic manipulation with adaptive safety constraint. Expert Systems with Applications.

Mr. Angelos Athanasiadis | Smart Materials | Research Excellence Award

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Mr. Angelos Athanasiadis | Smart Materials | Research Excellence Award

Aristotle University of Thessaloniki | AUTH | Greece

Mr. Angelos Athanasiadis is an emerging researcher in smart materials, embedded intelligence, and high-performance computing architectures, known for his contributions to FPGA-accelerated deep learning and intelligent cyber-physical systems. Currently pursuing his PhD in Electrical and Computer Engineering at Aristotle University of Thessaloniki, he focuses on designing advanced hardware-accelerated frameworks that significantly enhance the speed, efficiency, and energy performance of full-precision Convolutional Neural Networks on modern AMD FPGA platforms. His early scientific influence is reflected in 5 citations, referenced across 4 citing documents, supported by ongoing scholarly outputs and an h-index recorded as 1–2, demonstrating his growing visibility in computational engineering research. Mr. Athanasiadis has contributed to significant EU-funded research initiatives, including the ADVISER and REDESIGN projects, where he developed high-fidelity emulation tools, hardware–software co-design solutions, and distributed embedded intelligence for heterogeneous systems combining CPUs, GPUs, and FPGAs. His work on FUSION an open-source, timing-accurate, multi-node emulation framework integrating QEMU with OMNeT++ using HLA/CERTI synchronization has advanced the ability to accurately prototype next-generation smart systems for robotics, aerial monitoring, real-time analytics, and autonomous decision-making. With a strong background in electronics, embedded systems, and management engineering, he has also completed industry-driven research roles at EXAPSYS, SEEMS PC, and Cadence Design Systems, contributing to R&D for sensor networks, FPGA-based acceleration pipelines, and complex digital-system workflows. In addition to his technical expertise, he maintains interdisciplinary strengths in AI-driven system optimization, hardware–software integration, multiphysics emulation, and intelligent system design. Collaborating with leading academic researchers and contributing to peer-reviewed venues, he continues to expand his research footprint. With strong analytical skills, innovation-oriented thinking, and a commitment to advancing smart materials and high-performance embedded intelligence, Mr. Angelos Athanasiadis stands out as a promising researcher and a deserving candidate for the Research Excellence Award.

Profiles: Google Scholar | Orcid

Featured Publications

Athanasiadis, A., Tampouratzis, N., & Papaefstathiou, I. (2025). Energy-efficient FPGA framework for non-quantized convolutional neural networks. arXiv Preprint, arXiv:2510.13362.

Athanasiadis, A., Tampouratzis, N., & Papaefstathiou, I. (2025). An efficient open-source design and implementation framework for non-quantized CNNs on FPGAs. Integration, Article 102625.

Athanasiadis, A., Tampouratzis, N., & Papaefstathiou, I. (2024). An open-source HLS fully parameterizable matrix multiplication library for AMD FPGAs. WiPiEC Journal—Works in Progress in Embedded Computing Journal, 10(2).

Katselas, L., Jiao, H., Athanasiadis, A., Papameletis, C., Hatzopoulos, A., … (2017). Embedded toggle generator to control the switching activity during test of digital 2D-SoCs and 3D-SICs.

Katselas, L., Athanasiadis, A., Hatzopoulos, A., Jiao, H., Papameletis, C., … (2017). Embedded toggle generator to control the switching activity.

Mr. Prashant Kishor Sharma | Smart Materials | Research Excellence Award

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Mr. Prashant Kishor Sharma | Smart Materials | Research Excellence Award

National Cheng Kung University | Taiwan

Mr. Prashant Kishor Sharma is an emerging researcher in smart materials, microfluidics, and AI-integrated engineering, recognized for his rapidly growing contributions to advanced flow control, active matter systems, and micro-robotics for biomedical applications. As a doctoral researcher in Mechanical Engineering at National Cheng Kung University, Taiwan, he focuses on magnetically actuated artificial cilia, swarm microrobots, and intelligent microfluidic platforms that enable high-precision particle manipulation, drug delivery studies, and biomimetic flow control. His work spans computational hemodynamics, physics-informed neural networks, CFD-based flow modeling, and advanced lab-on-a-chip design, with research outcomes published in reputable SCI and Scopus-indexed journals covering microfluidic mixing, cognitive dynamics of zebrafish, AI-integrated magnetic microrobots, and solar-energy-based engineering systems. Mr. Sharma has successfully completed and contributed to several innovative research projects, including the development of artificial-cilia-based microactuation systems, computational hemodynamics of aneurysm flows using AI-accelerated models, a natural-zeolite oxygen concentrator, solar-powered thermal drying solutions, and bio-inspired drag-reduction strategies for energy-efficient flow systems. He actively collaborates across multidisciplinary teams involving mechanical engineering, biomedical engineering, microfabrication, and computational sciences, integrating simulation, experimentation, and AI-driven optimization. His work has earned recognition such as the Veritas Conscientia Scholarship, Excellence Research Work Award at CTAM, and Best Poster distinction for his contributions to thermal fluidics and micro-robotic navigation. In addition to scientific research, he contributes to technological innovation through a patent on a natural zeolite-based oxygen concentrator and participates in professional societies such as the Chinese Society of Theoretical and Applied Mechanics. His dedication to advancing smart materials, microfluidic intelligence, and biomedical engineering underscores his commitment to impactful, interdisciplinary research. With strong technical proficiency, innovative thinking, and a rapidly expanding academic footprint, Mr. Prashant Kishor Sharma stands out as a promising young scientist and an excellent candidate for the Research Excellence Award.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Sharma, P. K., Wei, P.-W., Loganathan, D., Lu, Y.-H., & Chen, C.-Y. (2025, November 18). Microflow switching using artificial cilia for on‐demand particle manipulation. Advanced Intelligent Systems.

Sharma, P. K., Wei, P.-W., Loganathan, D., Lu, Y.-H., & Chen, C.-Y. (2025, July 24). Microflow switching using artificial cilia for on‐demand particle manipulation. Advanced Intelligent Systems.

Sharma, P. K., Loganathan, D., Chen, M.-L., Lu, Y.-H., Wang, P.-H., & Chen, C.-Y. (2025, May 1). Cognitive dynamics of drug-mediated zebrafish under sound stimuli in a microfluidic environment. Biomicrofluidics.

Kandukuri, K. S., Sharma, P. K., & Arun, R. K. (2024). A comparative assessment of distributive mode active solar dryers: Flat plate collector vs evacuated tube collector with thermal energy storage and perforated baffled trays. Solar Energy, 112421.

Sharma, P. K., Arun, R. K., Lata, A., & Shiva, S. (2023, June 15). A natural zeolite based oxygen concentrator for supplying pure oxygen [Patent].

Sharma, P. K., Shukla, R. K., & Oberoi, A. S. (2022, August 25). Understanding of drag reduction & biofouling using shark skin denticle through CFD simulation (Master’s thesis or dissertation).

Dr. Jiang Bi | Material Degradation and Corrosion | Research Excellence Award

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Dr. Jiang Bi | Material Degradation and Corrosion | Research Excellence Award

Yanshan University | China

Dr. Jiang Bi is an accomplished materials scientist specializing in material degradation, corrosion behavior, alloy design, and advanced additive manufacturing processes, with a strong research portfolio that integrates laser processing, selective laser melting, metal matrix composites, and microstructural engineering. His scientific contributions have earned significant global visibility, reflected in 2,046 citations drawn from 1,654 citing documents, supported by 63 published documents and an h-index of 29, demonstrating the high impact and reliability of his research across the fields of materials science and manufacturing engineering. Dr. Bi’s work spans a broad range of topics including laser melting deposition, microstructure–property relationships, high-performance aluminum alloys, grain refinement mechanisms, and defect control strategies that enhance corrosion resistance and mechanical integrity. His studies on aluminum-magnesium-scandium-zirconium alloys, TiB₂-reinforced composites, and ultrasonic-assisted laser processing have contributed important insights into densification behavior, phase evolution, strengthening mechanisms, and fatigue performance of additively manufactured metals. He has authored influential research in well-recognized journals covering optics and laser technology, materials engineering, manufacturing processes, powder metallurgy, mechanical behavior of alloys, and composite fabrication. Dr. Bi possesses extensive expertise in metallography, SEM, microhardness analysis, tensile evaluation, simulation-based material design, and advanced characterization techniques, making him a valuable contributor to both fundamental materials research and industry-driven innovation. His academic journey includes research in forming technologies, high-pressure forming, and thermomechanical treatment of tubular components, further strengthening his multidisciplinary foundation. Through dedicated laboratory leadership, collaborative project involvement, and guidance of students and young engineers, he continues to advance cutting-edge technologies in corrosion mitigation, microstructural optimization, lightweight alloy development, and laser-based manufacturing. Dr. Jiang Bi’s commitment to research excellence, innovation in material degradation and corrosion science, and contributions to modern manufacturing technologies establish him as a prominent figure in the global materials science community and a distinguished candidate for recognition in research excellence.

Profile: Scopus

Featured Publications

Bi, J. (2026). Microstructure evolution and synergistic strengthening mechanisms of wear and corrosion resistance in laser cladding fabricated TC11-xMo coatings. Tribology International.

Bi, J. (2026). Regulating microstructure and strength–ductility synergy of laser-arc hybrid additive manufactured Al-Zn-Mg-Cu alloy. Journal of Materials Processing Technology.

Bi, J. (2025). Defects and fatigue properties of LPDC-fabricated aluminum alloy wheel: Experimental and numerical simulation methods. Engineering Failure Analysis.

Bi, J. (2025). Effect of aging treatment on microstructure, mechanical properties and corrosion resistance of 2219 aluminium alloy laser welded joint. Journal of Materials Research and Technology.

Bi, J. (2025). Coordinated control of multi-region solidification in complex-shaped die-cast wheels via cooling adjustment strategies to minimize defects and enhance performance. Journal of Materials Processing Technology.

Assoc. Prof. Dr. Guangyuan Xu | Smart Materials | Best Researcher Award

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Assoc. Prof. Dr. Guangyuan Xu | Smart Materials | Best Researcher Award

Beijing University of Posts and Telecommunications | China

Assoc. Prof. Dr. Guangyuan Xu is a leading researcher in brain computer interfaces, embodied intelligence, neural sensing, flexible electronics, and cognitively driven robotic systems, serving at the School of Artificial Intelligence at Beijing University of Posts and Telecommunications. His work is recognized internationally for pioneering advances that bridge neuroscience, materials science, artificial intelligence, and robotics, with a strong focus on creating intelligent systems capable of seamless human machine interaction. His scientific influence is reflected in 618 citations drawn from 572 citing documents, supported by 10 research documents and an h-index of 8, demonstrating the growing global relevance and impact of his contributions. Dr. Xu directs the Cognitive and Embodied Intelligence Laboratory, where he leads interdisciplinary teams in developing next-generation task-relevant mental imagery BCIs, high-performance flexible interfaces, multimodal neuro-robotic co-adaptation systems, intelligent sensing materials, and robust human–machine decision-making frameworks. He has published extensively in high-impact journals and international conferences covering biosensing, neurotechnology, flexible electronics, affective computing, and embodied robotics. His leadership extends to major professional societies, including active roles within the Chinese Association for Artificial Intelligence, the China Computer Federation, the China Graphics Society, and the national Brain Computer Interface Industry Alliance, reflecting his prominent standing in the scientific community. Dr. Xu also contributes to national strategic innovation programs and collaborative platforms in artificial intelligence, neurotechnology, and bio-integrated sensing, helping shape the scientific direction of emerging intelligent technologies. His collaborations with global institutions have strengthened international research networks in neuro-robotic integration and intelligent sensing systems, driving forward cutting-edge advancements in BCI-enabled robotics. Through his vision, interdisciplinary expertise, and dedication to advancing neuro-intelligent systems, Dr. Xu continues to push the boundaries of cognitive interaction technologies, flexible neural interfaces, and embodied intelligence, establishing himself as a key contributor to the future of human machine integration and intelligent robotic development.

Profiles: Scopus | Google Scholar

Featured Publications

Fu, Z., Lin, Y., Xu, G., & Zhang, M. (2025). Comparative performance of IMU and sEMG in locomotion mode prediction across transitional and steady-state cyclic/non-cyclic gaits. IEEE Journal of Biomedical and Health Informatics

Li, W., Zhang, J., Guo, J., Wang, X., Xu, G., Peng, Y., & Tu, L. (2025). Automated detection and classification of pediatric middle ear diseases from CT using entropy projection and feature interaction. In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE.

Xu, G. (2018). Laser scribed graphene: fabrication and electrochemical biosensors for neurotransmitters. ResearchSpace@Auckland.

Liu, Y., Xu, G., Li, C., Ma, Y., Ji, N., & Feng, X. (2025). Stretchable multilevel mesh brain electrodes for neuroplasticity in glioma patients undergoing surgery. Advanced Healthcare Materials, e03358.

Xu, G., Chen, Y., Chen, F., Meng, Y., Ma, Y., & Feng, X. (2021). Fabrication of laser scribed graphene stretchable supercapacitor by laser-assisted transfer printing strategy. In 2021 IEEE 16th International Conference on Nano/Micro Engineered and Molecular Systems (NEMS). IEEE.

Dr. Behnaz Arefian | Composite Materials | Research Excellence Award

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Dr. Behnaz Arefian | Composite Materials | Research Excellence Award

Isfahan University of Technology | Iran

Dr. Behnaz Arefian is a dedicated civil engineering researcher specializing in fiber-reinforced polymer (FRP) composites, structural strengthening systems, and the performance evaluation of reinforced concrete subjected to various loading conditions. She has developed a strong academic and professional reputation through impactful experimental and analytical research on FRP-reinforced and FRP-strengthened concrete structures, contributing to improved understanding of bond behavior, interface mechanics, and the structural response of advanced composite-concrete assemblies. Her research achievements demonstrate measurable scholarly influence, with 52 citations referenced across 40 citing documents, supported by 3 peer-reviewed research documents and an h-index of 2, reflecting an emerging yet growing presence in the scientific community. Dr. Arefian’s work includes the development of analytical models and experimental frameworks for assessing effective bond length, GFRP bar performance, flexural strengthening mechanisms, debonding behavior, and the structural reliability of composite-enhanced concrete beams and joints. She has conducted extensive laboratory investigations addressing bond strength enhancement, acoustic emission monitoring, failure depth modeling, and progressive cracking behavior under mechanical and thermal loading. Her scholarly contributions appear in reputable scientific journals such as Composite Structures, Journal of Composites for Construction, Construction and Building Materials, and Results in Engineering, along with presentations at international conferences. Dr. Arefian additionally engages in professional peer-review activities for international journals and has been recognized for academic excellence through competitive awards, demonstrating dedication to scientific rigor, leadership, and innovation. Her research supports sustainable and resilient construction technologies through the integration of lightweight high-strength materials, performance-optimized reinforcement solutions, and advanced failure prediction models. With strong expertise in FRP composites, GFRP bars, structural analysis, scientific writing, international collaboration, and experimental testing, Dr. Arefian continues to advance innovation in structural material science and modern engineering practice. She remains committed to contributing impactful solutions for safer, more durable, and sustainable infrastructure systems.

Profile: Scopus

Featured Publications

Generic assessment of effective bond length of FRP-concrete joint based on the initiation of debonding: Experimental and analytical investigation. (2021). Composite Structures, 277, 114625.

Experimental investigation and modeling of FRP–concrete joint bond strength based on failure depth. (2021). Journal of Composites for Construction, 25(6), 04021050.

Bond strength and load-carrying capacity of GFRP rebars embedded in concrete: An experimental and analytical study. (2025). Construction and Building Materials, 479, 141512.

Flexural performance of RC beams strengthened with grid-reinforced ECC panels using the EBROG technique. (2025). Results in Engineering, 108502.

Effect of thermal load on the parametric analysis of acoustic emission signals in concrete. (2025). Proceedings of the Second International Conference on the Exchange of Scientific Information.

Prof. Dr. Feng Wang | Composite Materials | Research Excellence Award

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Prof. Dr. Feng Wang | Composite Materials | Research Excellence Award

Agro-Environmental Protection Institute | Ministry of Agriculture and Rural Affairs | China

Prof. Dr. Feng Wang is an eminent environmental scientist and research leader serving as a senior researcher and Director of the Rural Environmental Governance Center at the Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, China. He is widely recognized for his pioneering contributions to the development of environmental adsorption materials, catalytic oxidation materials, and advanced strategies for the control and remediation of agricultural non-point source pollution and livestock wastewater. His extensive scientific influence is demonstrated by 1,488 citations, recorded across 1,255 citing documents, supported by 105 published scientific documents, and an h-index of 23, positioning him among the leading researchers advancing sustainable agricultural environmental protection. Prof. Wang has participated in more than thirty substantial national research initiatives, including major governmental and institutional R&D programs addressing critical environmental management challenges across rural regions and watershed systems. His innovations include the development of metal-modified biochar, quaternary ammonium-modified straw materials, modified layered double hydroxides, perovskite-based catalytic materials, and enzyme immobilization technologies, which achieve internationally competitive performance levels for the adsorption and degradation of complex pollutants. His research outcomes have directly supported major policy and strategic planning programs, including the formulation of national prevention and control plans for agricultural non-point source pollution in key river basins. As an author, he has published a large portfolio of impactful scientific papers in internationally indexed journals and co-authored eight professional books addressing aquaculture wastewater utilization, manure management, and agricultural pollution control. He holds an extensive patent portfolio with dozens of granted invention patents and successful technology transfer implementations. In addition, he is a reviewer for more than thirty international SCI journals and maintains active collaborations with leading universities and research institutions across the world. Prof. Dr. Feng Wang continues to advance innovation in environmental materials and ecological governance, making transformative contributions to sustainable agriculture and global environmental protection.

Profiles: Scopus | Orcid

Featured Publications

Design optimization of bimetal-modified biochar for enhanced phosphate removal performance in livestock wastewater using machine learning. (2025). Bioresource Technology.

The coupling model of random forest and interpretable method quantifies the response relationship between PM₂.₅ and influencing factors. (2025). Atmospheric Environment.

Superoxide radical (·O₂⁻)–driven peroxymonosulfate activation via cation-deficient lanthanum ferrite perovskite oxides: Electronic structure modulation for high-efficiency estrogen degradation in dairy wastewater. (2025). Advanced Composites and Hybrid Materials.

Efficient recovery of high-concentration phosphorus from livestock wastewater: Combined effects of magnesium-based metal–organic framework-derived metal oxide morphology and magnesium oxide vacancy species. (2025). Separation and Purification Technology.

Trichoderma brevicompactum 6311: Prevention and Control of Phytophthora capsici and Its Growth-Promoting Effect. (2025). Journal of Fungi.

Dr. Rohit Kumar Pant | Thin Film Technologies | Material Scientist Award

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Dr. Rohit Kumar Pant | Thin Film Technologies | Material Scientist Award

University of Maryland | United States

Dr. Rohit Kumar Pant is a highly accomplished materials scientist whose work spans epitaxial thin films, quantum materials, superconductors, combinatorial materials science, and advanced device fabrication. He is recognized for his strong technical command of Molecular Beam Epitaxy, Pulsed Laser Deposition, Magnetron Sputtering, and a wide range of structural, electrical, and spectroscopic characterization tools, positioning him as a key contributor to both fundamental and applied research in electronic and quantum materials. His research output includes 31 scientific documents, collectively cited 559 times by 400 documents, reflecting a significant scholarly impact supported by an h-index of 15. Dr. Pant has played leading roles in developing complex quantum heterostructures, superconducting thin-film libraries, epitaxial oxide and nitride systems, and high-throughput materials platforms that accelerate discovery across thermoelectric, ferroelectric, optoelectronic, and quantum device technologies. His work includes the design and fabrication of photodetectors, Josephson junctions, resonators, and advanced prototype devices, along with major contributions to cleanroom operations, tool maintenance, and training of research personnel. He has collaborated with major academic, national laboratory, and industry partners on multidimensional projects involving machine learning–guided materials optimization, nanoscale device engineering, and the exploration of emergent electronic phases. Dr. Pant is also an active reviewer for high-impact scientific journals and has contributed to numerous invited talks, conference presentations, and mentorship initiatives. Known for his analytical rigor, problem-solving ability, and innovative approach to materials design, he continues to advance scientific understanding and technological applications within quantum information science, thin-film engineering, and next-generation electronic devices.

Profiles: Scopus | Google Scholar

Featured Publications

Liu, Y., Slautin, B., Bemis, J., Proksch, R., Pant, R., Takeuchi, I., Udovenko, S., Trolier-McKinstry, S., & Kalinin, S. V. (2025). Reward based optimization of resonance-enhanced piezoresponse spectroscopy. Applied Physics Letters, 126(4).

Oh, J. H., Nam, K., Kim, D., Lee, D., Park, J., Pant, R., Kang, M., Takeuchi, I., & Lee, S. (2025). Stoichiometry effect on the structure and phase of antiperovskite Sr₃SnO thin films prepared using combinatorial co-sputtering. Applied Physics Letters, 126(3).

Biswas, A., Vasudevan, R., Pant, R., Takeuchi, I., Funakubo, H., & Liu, Y. (2025). SANE: Strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions. Digital Discovery, 4(3), 853-867.

Zheng, D. J., Iriawan, H., Pant, R., Eom, C. J., Xu, H., Peng, J., Arase, C., Takeuchi, I., & others. (2025). In situ fluorescence imaging of oxygen evolution on epitaxial perovskite films with composition gradients. ACS Catalysis, 15(11), 8776-8787.

Yoon, H., Wong, T., Pant, R., Baek, S., Saha, S. R., Zhang, X., Paglione, J., Lee, S., & others. (2025). Topological YB₆/SmB₆/YB₆ trilayer Josephson junctions. SMT.