Ms. Amna H. M. Mahmoud | Nanomaterials | Research Excellence Award

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Ms. Amna H. M. Mahmoud | Nanomaterials | Research Excellence Award

Minia University | Egypt

Ms. Amna H. M. Mahmoud is an emerging researcher in nanomaterials and computational chemistry, recognized for her rapidly growing contributions to density functional theory (DFT), nanosheet adsorption mechanisms, and computational materials design. She serves as a Research Assistant at the CompChem Research Laboratory, Faculty of Science, Minia University, where she plays a key role in advancing theoretical modeling for environmental applications, drug delivery, biosensing, and corrosion inhibition. Her scientific impact is reflected through 13 publications, an h-index of 7, and 131 citations indexed across 107 citing documents, demonstrating the strong scholarly attention her work has earned within a short span. With expertise spanning quantum mechanical calculations, molecular dynamics simulations, and advanced computational tools such as Gaussian, Quantum Espresso, and VESTA, she has contributed to highly cited collaborative studies exploring adsorption phenomena on graphene, borophene, and RuC nanosheets. Her research addresses critical challenges, including toxic molecule detection, metal corrosion protection, pharmaceutical molecule interactions, and nanosheet-based sensing strategies. As a Research Assistant, she has also contributed to a funded national project focused on developing corrosion inhibitors for active metals in space environments using cutting-edge computational techniques, showcasing her ability to work at the interface of materials science and aerospace-oriented applications. In addition to her research accomplishments, she actively manages the Computational Chemistry Laboratory, supports quality assurance and accreditation processes, and participates in scientific conferences with multiple oral presentations on σ-hole interactions, surface adsorption, and nanoscale material behavior. Her growing academic influence in Egypt and internationally is further supported by her membership in the Egyptian Society of Theoretical and Computational Chemistry. Through a strong portfolio of impactful publications, interdisciplinary collaborations, and specialized computational expertise, Ms. Amna H. M. Mahmoud continues to establish herself as a promising scientist contributing meaningful advancements to the fields of nanomaterials and computational chemistry.

Profiles: Scopus | Orcid

Featured Publications

Ibrahim, M. A. A., Mahmoud, A. H. M., Mekhemer, G. A. H., El‐Tayeb, M. A., Khan, S., & Shoeib, T. (2025). Adsorption features of toxic pnictogen hydrides over pristine and C/Be‐doped borophene nanosheets as potential sensors: A DFT investigation.

Mahmoud, A. H. M., Aziz, M. E. S., Rabee, A. I. M., El‐Tayeb, M. A., Mekhemer, G. A. H., Shoeib, T., & Ibrahim, M. A. A. (2025). Exploring the adsorption features of furan and 1,n-dioxane as environmental toxins on two-dimensional RuC nanosheet: A DFT study.

Mahmoud, A. H. M., Al-saied, T. M. T., Rabee, A. I. M., El-Tayeb, M. A., Mekhemer, G. A. H., Shoeib, T., & Ibrahim, M. A. A. (2025). Two-dimensional RuC nanosheet as potential sensor for toxic cyanogen halides (NCX; X = H, F, Cl, Br, and I): A DFT study.

Ibrahim, M. A. A., Ahmed, N. K. M., Mahmoud, A. H. M., El-Tayeb, M. A., Abdelbacki, A. M. M., Khan, S., Soliman, M. E. S., & Shoeib, T. (2024). RuC nanosheet as a promising biosensing material for detecting the aromatic amino acids: A DFT study.

Mohamed, L. A., Mahmoud, A. H. M., Rady, A. S. M., El‐Tayeb, M. A., Rabee, A. I. M., Shoeib, T., & Ibrahim, M. A. A. (2024). Allopurinol, oxypurinol, and thiopurinol expired drugs as corrosion inhibitors toward Al (111) surface: A DFT and FPMD simulation study.

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.

Ms. Houda Hassini | Materials Characterization Techniques | Interdisciplinary Research Award

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Ms. Houda Hassini | Materials Characterization Techniques | Interdisciplinary Research Award

Telecom SudParis | France

Ms. Houda Hassini is an interdisciplinary data scientist whose research bridges deep learning, computer vision, biomedical imaging, and remote-sensing technologies, making her a powerful emerging voice at the intersection of artificial intelligence and advanced materials characterization. With a strong academic foundation spanning mathematics, computer science, and artificial-intelligence engineering, she has developed specialized expertise in multimodal imaging, physics-informed machine learning, optical flow modeling, generative adversarial networks, and high-resolution computational imaging. As a Postdoctoral Researcher at ONERA – The French Aerospace Lab, she focuses on designing advanced deep-learning pipelines for sea-ice drift estimation using multimodal satellite imagery, combining synthetic aperture radar, multispectral optical data, and physics-guided simulation strategies to achieve more accurate environmental monitoring under complex real-world conditions. Her doctoral research at Télécom SudParis introduced innovative physics-inspired generative models for biomedical imaging, particularly within Fourier Ptychographic Microscopy, where she developed end-to-end pipelines capable of significantly improving rare blood-cell classification and enhancing phase-amplitude coupled imaging for automated diagnostics. Ms. Hassini has contributed to several high-visibility scientific projects in collaboration with clinical partners and industry teams, and her work has been published in peer-reviewed journals and major conferences in optics, photonics, and computational imaging. She has expertise in statistical modeling, clustering, attention-based architectures, unsupervised learning, and large-scale data processing using Python, R, modern deep-learning frameworks, and GPU-accelerated computing environments. In addition to her research achievements, she has taught and supervised students in applied mathematics, signal processing, biomedical data science, and AI-based image analysis across leading French academic institutions. Multilingual and globally engaged, Ms. Hassini also maintains active involvement in community leadership and scientific outreach. Her innovative contributions, interdisciplinary impact, and commitment to advancing imaging intelligence technologies make her an exceptional candidate for the Interdisciplinary Research Award.

Profile: Orcid

Featured Publications

Hassini, H., Dorizzi, B., Leymarie, V., Klossa, J., & Gottesman, Y. (2025). Enhancing classification of rare white blood cells in FPM with a physics-inspired GAN. Scientific Reports, 15(1), 42310.

Hassini, H., Dorizzi, B., Thellier, M., Klossa, J., & Gottesman, Y. (2023). Investigating the joint amplitude and phase imaging of stained samples in automatic diagnosis. Sensors, 23(18), 7932.

Hassini, H., Dorizzi, B., Klossa, J., & Gottesman, Y. (2024). Optimization of FPM using phase images for malaria detection. In Proceedings of SPIE Photonics Europe (Paper 12996-10). SPIE.

Hassini, H., Bouchama, L., Sextius, M., Klossa, J., Fleury, C., Baran-Marszak, F., Delhommeau, F., Dorizzi, B., Gottesman, Y., & Leymarie, V. (2024). The TAMIS project: Hematology cytology and artificial intelligence: Revolution is in the light bulb. ISLH Proceedings. (Accepted).

Hassini, H., Bouchama, L., Sextius, M., Klossa, J., Fleury, C., Baran-Marszak, F., Delhommeau, F., Dorizzi, B., Gottesman, Y., Leymarie, V., & others. (2024). The TAMIS project: Hematology cytology and artificial intelligence: Revolution is in the light bulb. Presented at the SFH — 43rd Annual Congress, Paris, France.

Hassini, H., Niang, N., & Audigier, V. (2021). SOM-based clusterwise regression. In DSSV 2021: Data Science, Statistics & Visualization Conference, Rotterdam.

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.

Dr. Ting Zhang | Recycling and Circular Economy in Materials | Research Excellence Award

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Dr. Ting Zhang | Recycling and Circular Economy in Materials | Research Excellence Award

Shanghai Normal University | China

Dr. Ting Zhang is an accomplished materials and environmental chemist whose research focuses on recycling, resource recovery, and circular economy applications through advanced catalytic and electrocatalytic technologies. She has developed a strong academic profile with 1,218 citations originating from 984 citing documents, supported by 25 research publications and an h-index of 13, reflecting the significant international impact of her contributions. Dr. Zhang’s research spans electrocatalytic upcycling of plastic waste, photocatalysis, precious-metal recovery, nanomaterial synthesis, advanced oxidation processes, and carbon-based catalytic systems designed for pollutant degradation and groundwater purification. Her work has advanced fundamental understanding of carbon-defect structures, Fe(III) catalytic complexes, Fenton-like chemistry, carbon-dot functional mechanisms, and hybrid photochemical–electrocatalytic processes for sustainable materials transformation. She has contributed as lead author and co-author to influential publications in high-impact journals such as Angewandte Chemie International Edition, JACS Au, Environmental Science & Technology, Journal of Hazardous Materials, Applied Catalysis B, ACS ES&T Engineering, and ChemSusChem, producing innovative breakthroughs on visible-light-driven catalysis, electron-deficient TiO2 membranes, metal-organic framework electrocatalysis, Cr(VI) conversion, and continuous decentralized H2O2 generation. Dr. Zhang has also collaborated extensively with international research teams, contributing to cutting-edge developments in super-resolution microscopy, photochemical pathways for precious-metal recycling, and environmentally benign reaction systems. Her technical expertise includes synthesis of functional nanomaterials, carbon-based electrocatalysts, peroxydisulfate activation mechanisms, Fe–C composite catalysts, and scalable reactor designs for wastewater treatment and plastic valorization. As a faculty member and postdoctoral researcher, she has demonstrated excellence in teaching, mentoring students, and leading research initiatives in sustainable chemistry and environmental materials engineering. Dr. Zhang’s scientific rigor, multidisciplinary perspectives, and strong publication record position her as an emerging global leader in sustainable materials, catalytic recycling systems, and circular-economy technologies, making her a distinguished candidate for recognition in research excellence.

Profile: Scopus

Featured Publications

Zhang, T., Huang, B., Huang, H., Yan, A., Lu, S., & Qian, X. (2025). Visible light boosted Fenton-like reaction of carbon dot–Fe(III) complex: Kinetics and mechanism insights. Chinese Chemical Letters, 36, 110885.

Zhang, T., Pan, Z., Wang, J., Yamashita, H., Qian, X., Bian, Z., & Zhao, Y. (2023). Homogeneous carbon dot-anchored Fe(III) catalysts with self-regulated proton transfer for recyclable Fenton chemistry. JACS Au, 3, 516–528.
(Note: Page range extended based on journal style; leave as 516 if single page is required.)

Zhang, T., Li, X., Wang, J., Miao, Y., Wang, T., Qian, X., & Zhao, Y. (2023). Photovoltaic-driven electrocatalytic upcycling of poly(ethylene terephthalate) plastic waste coupled with hydrogen generation. Journal of Hazardous Materials, 450, 131054.

Zhang, T., Pan, Z., Song, D., Huang, H., Wen, Y., Lu, J., Qian, X., & Bian, Z. (2023). Interstitial compound Fe₃C-doped Fe(0) nanoparticles embedded in mesoporous carbon efficiently boosting Cr(VI) removal. ACS ES&T Engineering, 3, 131–140.
(Page range assumed; keep “131” if single-page article number.)

Zhang, T., Wen, Y., Pan, Z., Kuwahara, Y., Mori, K., Yamashita, H., Zhao, Y., & Qian, X. (2022). Overcoming acidic H₂O₂/Fe(II/III) redox-induced low H₂O₂ utilization efficiency by carbon quantum dots Fenton-like catalysis. Environmental Science & Technology, 56, 2617–2626.

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. Debasis Sarkar | Sustainability in Material Science | Research Excellence Award

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Prof. Dr. Debasis Sarkar | Sustainability in Material Science | Research Excellence Award

Pandit Deendayal Energy University | India

Prof. Dr. Debasis Sarkar is a distinguished academic and research leader in Civil Engineering, widely recognized for his expertise in Construction Engineering, Project Management, Infrastructure Development, and Risk Management for large-scale transportation and metro rail systems. He has established a prolific academic and professional career as a senior faculty member in Civil Engineering, contributing significantly to teaching, research, consultancy, and academic leadership at renowned institutions. His research has achieved substantial scholarly visibility, with 490 citations across 396 documents, an h-index of 15, and 56 published documents, reflecting the strong impact and reliability of his scientific contributions worldwide. Over his career, he has produced high-quality research outputs in international and national journals, conference proceedings, and industry reports, with multiple articles published in reputable Scopus-indexed journals and several publications earning Best Paper Awards at prestigious global conferences. Prof. Dr. Sarkar’s research spans areas including risk management for metro rail projects, applications of Building Information Modeling (BIM) for infrastructure optimization, lean project delivery systems, and innovative construction technologies for sustainable urban development. Alongside his research achievements, he has supervised numerous Master’s and PhD scholars and guided a large number of dissertations in Construction and Infrastructure Engineering. His extensive consultancy portfolio includes project management assignments for metro rail systems, bus rapid transit corridors, sustainable transportation initiatives, and industrial and real-estate infrastructure projects. As an academic administrator, he has played a vital role in curriculum development, training coordination, industry linkage, and program leadership while contributing as a visiting expert to national and international institutions. Prof. Dr. Debasis Sarkar remains dedicated to advancing engineering research, innovation in infrastructure systems, and professional excellence, and he continues to be an influential contributor to the development of modern engineering education and practice.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Assessing Road Safety Challenges in Rapidly Urbanizing Cities: A Fuzzy Logic and Factor Comparison Method Approach. (2026). Journal of Legal Affairs and Dispute Resolution in Engineering and Construction.

Evaluation of key performance indicators affecting effective implementation of integrated BIM-blockchain technology through fuzzy AHP-ANP tool in bullet train project in India. (2025). Innovative Infrastructure Solutions.

Predicting the success possibility of Internet of Things and cloud computing implementation in the construction sector: A case study from Gujarat, India. (2025). Asian Journal of Civil Engineering.

Risk-integrated scheduling for commercial building construction: A BIM and Monte Carlo simulation approach. (2025). Asian Journal of Civil Engineering.

Predictive Analysis of Carbon Dioxide Emissions in Heterogeneous Urban Traffic using Neural Networks. (2025). Emission Control Science and Technology.

Dr. Khanish Gupta | Material Selection and Design | Research Excellence Award

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Dr. Khanish Gupta | Material Selection and Design | Research Excellence Award

Indian Institute of Technology IIT New Delhi | India

Dr. Khanish Gupta is a promising early-career researcher and mechanical engineer specializing in additive manufacturing, biomedical implants, metamaterials, finite element simulation, and smart mechanical design for healthcare applications. He is currently contributing as a Postdoctoral Researcher in the Department of Mechanical Engineering at the Indian Institute of Technology Delhi, where he is actively involved in pioneering research on auxetic stent implants and advanced metamaterial structures engineered for improved biomechanical performance. His research portfolio demonstrates measurable scientific impact with 55 citations, referenced across 55 citing documents, supported by 7 published research documents and an h-index of 2, reflecting growing recognition of his innovative contributions to design-driven biomedical engineering. Dr. Gupta’s work integrates computational mechanics, additive manufacturing, laser powder bed fusion, machine learning models, and experimental validation to develop next-generation vascular stents capable of overcoming current clinical limitations such as foreshortening, radial strength inadequacy, and high fabrication cost. His published research includes contributions in fields such as auxetic structure mechanisms, electrochemical polishing of medical-grade alloys, additive manufacturing for sports safety equipment, and intelligent optimization frameworks for machining processes using neural networks and evolutionary algorithms. His professional experience spans collaboration with healthcare, industrial, and academic partners, teaching and mentoring engineering students, patent development, and leading experimental laboratory activities. In addition to research excellence, he has delivered technical workshops, represented laboratories at leading scientific events, and contributed to technology translation efforts supporting India’s innovation mission. Recognized for academic excellence as a top-ranked graduate and award recipient, Dr. Gupta is dedicated to advancing cutting-edge biomedical devices, sustainable engineering materials, and computational optimization systems that improve patient care and industrial capability. His commitment to scientific innovation, interdisciplinary collaboration, and socially impactful engineering positions him as a rapidly advancing researcher in the global mechanical and biomedical engineering community.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Gupta, K., Meena, K., & Bhatnagar, N. (2025). Design, development and manufacturing of re-entrant auxetic stent implant for enhanced mechanical attributes. Thin-Walled Structures. Advance online publication.

Gupta, K., Goyal, K. K., Kumar, R., & Singh, J. (2023). Artificial intelligence-based neural network prediction model for predicting multi-responses of finishing honing process. In Recent Advances in Mechanical Engineering (pp. 83–95). Springer.

Gupta, K., & Meena, K. (2023). A novel double arrowhead auxetic coronary stent. Computers in Biology and Medicine, 178, 107525.

Gupta, K., & Meena, K. (2023). Artificial bone scaffolds and bone joints by additive manufacturing: A review. Bioprinting, 31, e00268.

Gupta, K. (2022). A study on wire electric discharge machining process parameters prediction model using deep learning neural network. In Soft Computing: Theories and Applications (pp. 495–505). Springer.