Mohamed Kanniche | Separation | Best Researcher Award

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Dr. Mohamed Kanniche | Separation | Best Researcher Award

Dr. Mohamed Kanniche | Electricity of France – R&D Division | France

Dr. Mohamed Kanniche, a French national, is an Expert Researcher at Electricité de France (EDF) – R&D Division, where he has dedicated over 35 years to advancing energy and environmental technologies. He earned his Ph.D. in 1990 from École Centrale de Lyon in collaboration with EDF R&D, specializing in second order turbulence modelling of stratified and recirculating flows, following his Master’s in Fluid Mechanics and his engineering degree from the same institution. His professional expertise spans more than three decades of R&D in classical thermal power plants, with contributions to pulverized coal, combined cycle, and integrated gasification combined cycle systems, particularly in energy performance optimization and emission reduction. Dr. Kanniche has developed recognized expertise in turbulent combustion of coal, gas, and biomass, as well as in chemical and process engineering for wastewater depollution, seawater desalination, and industrial gas treatment (DeNOx, DeSOx, and dedusting). A specialist in CO2 capture technologies, he has extensively studied absorption- and membrane-based processes for both post- and pre-combustion applications. His work has contributed to European and international projects such as HiPerCap under FP7 and EDF’s industrial decarbonation initiatives, with over 50 publications, 1,763 citations, and an h-index of 17 (Scopus Author ID: 56297868600),Orcid Author ID: 0000-0003-2956-163X.

 Profile: Orcid | Scopus 

Featured Publications

  • de Joannis, P., Castel, C., Kanniche, M., Favre, E., & Authier, O. (2025, September 22). Techno-economic analysis of hybrid adsorption–membrane separation processes for direct air capture. ChemEngineering, 9(5), 102.

  • de Joannis, P., Castel, C., Kanniche, M., Favre, E., & Authier, O. (2025, January 29). Direct air capture by monoethanolamine absorption with heat pump enhancements. Industrial & Engineering Chemistry Research, 64(4), 2033–

Nkanyiso Msweli | Electrical Engineering | Best Researcher Award

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Mr. Nkanyiso Msweli | Electrical Engineering
| Best Researcher Award

Mr. Nkanyiso Msweli | Tshwane University of Technology | South Africa

Mr. Nkanyiso Msweli is an experienced and results-driven Plant Manager  with over a decade of expertise in power generation, renewable energy, and maintenance management, currently leading operations at a solar power plant under Enel Green Power in Upington, South Africa. He has a proven track record in ensuring compliance with the Occupational Health and Safety Act, statutory regulations, and international standards, while driving operational excellence through strategic maintenance leadership, budget optimization, and risk control. His career spans key roles at Vestas Group, Eskom Rotek Industries, and AMG Power Systems, where he gained extensive knowledge of solar PV systems, boilers, HV/MV networks, transformers, and wind plant operations. Mr. Msweli is highly skilled in root cause failure analysis (RCFA), World Class Manufacturing (WCM) practices, and reliability-centered maintenance, enabling him to enhance asset performance and minimize downtime. He has successfully managed complex engineering teams, coordinated plant overhauls, led safety audits, and delivered technical advisory services on high-pressure systems and emission controls. Academically, His scholarly impact is reflected in her Google Scholar he is pursuing a Doctor of Engineering at Tshwane University of Technology, holds an MPhil in Electrical Engineering from the University of Johannesburg, and is certified in GCC and multiple ISO standards, reflecting his commitment to professional excellence and innovation in sustainable energy.

 Profile: Orcid 

Featured Publications

Msweli, N., Nnachi, G. U., & Richards, C. G. (2025). A review of green hydrogen technologies and their role in enabling sustainable energy access in remote and off-grid areas within Sub-Saharan Africa. Energies, 18(18), 5035.

Juliana Sanchez | Nuclear Engineering | Best Researcher Award

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Dr. Juliana Sanchez | Nuclear Engineering
| Best Researcher Award

Dr. Juliana Sanchez |  Federal University of Rio de Janeiro | Brazil

Dr. Juliana Sanchez, a Brazilian Nuclear Safety and Environmental Remediation specialist born in Rio de Janeiro, began her research career at the Federal University of Rio de Janeiro  in 2017 and has since built a strong academic and professional trajectory in nuclear engineering and safety methodologies. She is currently a Ph.D. student in Nuclear Engineering through a joint program between UFRJ and Porto University, holding a Master’s degree in Nuclear Engineering from the Institute of Nuclear Engineering at UFRJ. Her expertise spans nuclear safety analysis using MCNP Monte Carlo N-Particle and HotSpot Health Physics codes, radioactive dispersion modeling, dose assessment, and risk calculation in facilities handling radioactive materials. Dr. Sanchez is a researcher at the Process Monitoring Laboratory, COPPEAD UFRJ, and has international training in radiological safety, nuclear power plant safety practices, and research reactors from the Moscow Institute of Physical Engineering. Complementing her technical expertise, she earned MBAs in Complex Systems Modeling from Southern Federal University, Applied Projects in Civil Construction, and Construction Management, alongside her background as a Civil and Nuclear Engineer. Recognized globally, she was co-winner of the IAEA Student Travel Competition at ICEM 2023 in Germany and part of the winning team at Hackatom Brazil 2023, organized by IPEN, MEPhI, and ROSATOM. Her research record includes 4 citations by 4 documents  from 2 documents with an h-index of 1, and her publications are indexed in Scopus under ID 58766405500.

 Profile: Scopus | Linked IN

Featured Publication

Sanchez, J., dos Santos Nicolau, A., Pereira, C. M. N. A., & Marques Salgado, C. (2024). Methodology to calculate doses from gamma-emitting plumes using MCNP6 Monte Carlo N-particle and HotSpot codes. Nuclear Engineering & Design.

Shahina Begum | Artificial Intelligence | Best Researcher Award

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Prof. Dr. Shahina Begum | Artificial Intelligence
| Best Researcher Award

Prof. Dr. Shahina Begum | Mallardalen University | Sweden

Prof. Dr. Shahina Begum, a Swedish national, is a distinguished Professor of Artificial Intelligence at the Artificial Intelligence and Intelligent Systems Research Group, Mälardalen University, Sweden, where she has been serving since 2019 after progressing through roles as Senior Lecturer  and Postdoctoral Researcher . She holds a Ph.D. ,Licentiate (2009), and Docent (2015) in Artificial Intelligence from Mälardalen University, as well as an M.Sc. in Computer Science (Intelligent Systems) from Dalarna University (2005). With over a decade of teaching and research experience, she has made significant contributions to AI through pioneering work in machine learning, intelligent decision support, and AI applications for health and well-being. Prof. Begum has demonstrated exceptional leadership in academia by securing substantial external research funding, amounting to approximately 224.4 MSEK as Principal Investigator and Co-PI, enabling groundbreaking multidisciplinary projects bridging AI with real-world applications. Her scholarly impact is reflected in her Google Scholar record, with an h-index of 30 and around 3,689 citations, and her Scopus record, with 88 indexed publications, 1,497 citations from 1,292 documents, and an h-index of 18. A passionate educator and mentor, she continues to inspire the next generation of AI researchers while actively contributing to the global AI research community through publications, collaborations, and leadership in funded projects.

 Profile: Scopus | Google Scholar | Linked IN | Staff Page | Orcid

Featured Publications

Islam, M. R., Ahmed, M. U., Barua, S., & Begum, S. (2022). A systematic review of explainable artificial intelligence in terms of different application domains and tasks. Applied Sciences, 12(3), 1353.

Begum, S., Ahmed, M. U., Funk, P., Xiong, N., & Folke, M. (2010). Case-based reasoning systems in the health sciences: A survey of recent trends and developments. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 40(2), 241–257.

Barua, S., Ahmed, M. U., Ahlström, C., & Begum, S. (2019). Automatic driver sleepiness detection using EEG, EOG and contextual information. Expert Systems with Applications, 115, 121–135.

Chen, R. Y., Kung, V. L., Das, S., Hossain, M. S., Hibberd, M. C., Guruge, J., … & Begum, S. (2020). Duodenal microbiota in stunted undernourished children with enteropathy. New England Journal of Medicine, 383(4), 321–333.

Begum, S., Ahmed, M. U., Funk, P., Xiong, N., & Von Schéele, B. (2009). A case-based decision support system for individual stress diagnosis using fuzzy similarity matching. Computational Intelligence, 25(3), 180–195.

Degas, A., Islam, M. R., Hurter, C., Barua, S., Rahman, H., Poudel, M., Ruscio, D., … & Begum, S. (2022). A survey on artificial intelligence (AI) and explainable AI in air traffic management: Current trends and development with future research trajectory. Applied Sciences, 12(3), 1295.

Weiran Liu | Digital Twin | Best Researcher Award

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Dr. Weiran Liu | Digital Twin | Best Researcher Award

Dr. Weiran Liu | Beihang University | China

Dr. Weiran Liu, is a postdoctoral researcher at the Digital Twin International Research Center, International Research Institute for Multidisciplinary Science, Beihang University, China, where he specializes in digital twin technologies and their applications. He earned his B.S. degree in Automation Science and Electrical Engineering from Beihang University in 2014 and completed his Ph.D. in the same field at Beihang University in 2024. His research focuses on digital twin theory, digital twin satellites, and digital twin shop-floor systems, with pioneering work that introduced the novel concept of the digital twin satellite. At the China Academy of Space Technology, he spearheaded the development of an internationally advanced digital twin satellite assembly shop-floor, which has been adopted as a benchmark to guide the construction of the Tianjin satellite factory, demonstrating strong translational impact from theory to industry. To date, Dr. Liu has completed or is engaged in 10 research projects, published 16 SCI/Scopus-indexed journal articles, and holds 9 patents that underline his innovative capacity. His academic influence is reflected in 240 citations across 207 documents, 28 indexed publications, and an h-index of 10, establishing his reputation as a rising researcher whose work significantly strengthens the global advancement of digital twin technologies.

 Profile: Scopus | Google Scholar | Researchgate 

Featured Publications

Tao, F., Liu, W., Zhang, M., Hu, T., Qi, Q., Zhang, H., Sui, F., Wang, T., & Xu, H. (2019). Five-dimension digital twin model and its ten applications. Comput. Integr. Manuf. Syst, 25(1), 1-18.

Tao, F., Liu, W., Liu, J., Liu, X., Liu, Q., Qu, T., Hu, T., Zhang, Z., Xiang, F., & Xu, W. (2018). Digital twin and its potential application exploration. Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, 24(1), 1-18.

Tao, F., Sun, X., Zhu, Y., Liu, W., Yong, W., & Xu, H. (2024). makeTwin: A reference architecture for digital twin software platform. Chinese Journal of Aeronautics, 37(1), 1-18.

Tao, F., Ma, X., Hu, T., Huang, Z., Cheng, J., Qi, Q., Zhang, M., Liu, W., Zhang, H., & … (2019). Research on digital twin standard system. Computer Integrated Manufacturing Systems, 25(10), 2405-2418.

Tao, F., Zhang, H., Qi, Q. L., Zhang, M., Liu, W. R., & Cheng, J. F. (2020). Ten questions towards digital twin: Analysis and thinking. Computer Integrated Manufacturing Systems, 26(1), 1-17.

Liu, W., Tao, F., Cheng, J., Zhang, L., & Yi, W. (2020). Digital twin satellite: Concept, key technologies and applications. Computer Integrated Manufacturing Systems, 26(3), 565-588.

Tao, F., Ma, X., Qi, Q., Liu, W., He, Z., & Chenyuan, Z. (2023). Theory and key technologies of digital twin connection and interaction. Computer Integrated Manufacturing System, 29(1), 1.

Cyrille Feybesse | Data Science | Best Researcher Award

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Dr. Cyrille Feybesse | Data Science | Best Researcher Award

Dr. Cyrille Feybesse | Guillaume Regnier Hospital | France

Dr. Cyrille Feybesse, a French psychologist and Maître de Conférences (MCF, 2022), is a researcher and clinical psychologist specializing in love, creativity, and cross-cultural psychology. He earned his Ph.D. in Psychology (2015) at Université Paris Descartes under the supervision of Professors Geneviève Coudin and Todd Lubart, with additional mentorship from Professor Elaine Hatfield (University of Hawai‘i). His academic background spans clinical, health, and social psychology, with training in France, Portugal, and Brazil. Dr. Feybesse has held postdoctoral fellowships at Université Paris Descartes and the University of Porto, collaborating with the Portuguese Foundation for Science and Technology (FCT) on pioneering research into passionate love and creativity. Since 2022, he has been conducting clinical and research activities at the Centre Hospitalier Guillaume Régnier, Rennes, focusing on child psychiatry, creativity, and high-potential intelligence. He has authored over 14 publications, contributed to multiple book chapters, and presented at numerous international conferences. His work has been cited more than 350 times (Scopus Author ID: 57191835134; ORCID: 0000-0001-7795-568X) with an h-index of 6. Multilingual in English, Portuguese, and Spanish, Dr. Feybesse also serves as Assistant Editor for Interpersona and reviewer for leading journals including Sexuality & Culture and European Psychologist, advancing research at the intersection of love, creativity, and human development.

 Profile: Scopus | Orcid  | Researchgate 

Featured Publications

Feybesse, C., Forthmann, B., Neto, F., Holling, H., & Hatfield, E. (2025). Measuring love around the world: A cross-cultural reliability generalization. Sexuality & Culture. Advance online publication.

Feybesse, C. (2024). Social representation of passionate love among Brazilian and French youngsters. Trends in Psychology. Advance online publication.

Feybesse, C., Fu, S., Lubart, T., Rasa, L., Ossom, C., Cavasino, V., Jacob, J., & Lemonnier, T. (2020). Social representation of fair price among professional photographers. PLOS ONE, 15(12), e0243547.

Feybesse, C. (2018). Assessing passionate love: Italian validation of the PLS (reduced version). Sexual and Relationship Therapy, 33(2), 221–229.

Feybesse, C. (2016). Sensory values in romantic attraction in four European countries: Gender and cross-cultural comparison. Journal of Cross-Cultural Research, 50(2), 109–123.

Murat Ozkut | Reliability Engineering | Best Researcher Award

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Assoc. Prof. Dr. Murat Ozkut | Reliability Engineering
| Best Researcher Award

Assoc. Prof. Dr. Murat Ozkut | Izmir University of Economics | Turkey

Assoc. Prof. Dr. Murat Ozkut is an accomplished scholar and Associate Professor in the Department of Mathematics at Izmir University of Economics, Türkiye, with over a decade of academic and research experience in applied mathematics, reliability theory, and stochastic modeling. His research primarily focuses on the reliability assessment of complex engineering systems, shock models, dependent component analysis, and optimization of replacement policies, producing significant contributions published in high-impact journals such as IEEE Transactions on Reliability, Journal of Computational and Applied Mathematics, Reliability Engineering & System Safety, and Computers & Industrial Engineering. With a strong academic background, including a Ph.D. in Applied Mathematics and Statistics , Dr. Ozkut has authored 188 Citations 15 journal papers that have been cited in 155 documents, achieving an h-index of 7, demonstrating the scholarly impact and relevance of his work. His collaborative research with prominent statisticians and engineers has advanced the understanding of reliability in coherent and multi-state systems under Marshall–Olkin type shocks, run shock models, and k-out-of-n frameworks, offering practical applications in risk and reliability engineering. Beyond research, he is skilled in multiple programming languages (Python, R, Java, SQL, LATEX) and integrates computational methods into his teaching and consultancy. With proven expertise, international collaborations, and growing citation influence, Dr. Ozkut is well-positioned to expand his contributions to reliability engineering, applied probability, and interdisciplinary applications of mathematical sciences.

 Profile: Scopus | Orcid  

Featured Publications

  • Ozkut, M., & Tutuncu, G. Y. (2025). Reliability analysis and optimization problems for a weighted-k-out-of-n: G system with multiple types of components. Computers & Industrial Engineering.

  • Ozkut, M., Kan, C., & Franko, C. (2024). Analyzing the multi-state system under a run shock model. Probability in the Engineering and Informational Sciences.

  • Torrado, N., & Ozkut, M. (2024). Analyzing component failures in series-parallel systems with dependent components. Computers & Industrial Engineering.Ozkut, M. (2024). Reliability assessment of consecutive k-out-of-n systems with two types of dependent components. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability.

  • Ozkut, M. (2023). Reliability and optimal replacement policy for a generalized mixed shock model. TEST.

 

Monis Bin Abid | Chemical Engineering | Best Researcher Award

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Dr. Monis Bin Abid | Chemical Engineering
| Best Researcher Award

Dr. Monis Bin Abid | Prince Muqrin of Madinah | Saudi Arabia

Dr. Monis Bin Abid is an accomplished chemistry lecturer and researcher with over eight years of diverse teaching experience across leading institutions in Saudi Arabia and Pakistan, currently serving at the University of Prince Mugrin, Madinah. His expertise spans teaching, curriculum design, quality assurance, and student advising, where he has consistently demonstrated leadership as chairman of the course design team, deputy chairman of the General Studies Department, and active member of quality and accreditation committees. A recipient of multiple honors including the Best Researcher Award (2024) and the Dr. Alsayyed Scientific Research Award, Dr. Abid has also been recognized as Best Teacher of the Year in 2017 and 2018, reflecting his dual excellence in research and pedagogy. His Ph.D. project at Universiti Teknologi Malaysia focused on membrane distillation desalination using advanced omniphobic membranes, a field in which he has authored impactful publications indexed in Scopus and ISI Q1/Q2 journals, contributing to the advancement of sustainable water treatment technologies. With a portfolio of over 90 citations, nine published papers, and an h-index of 3, his scholarly influence is growing steadily. Dr. Abid has earned certifications from prestigious institutions worldwide, reflecting his commitment to continuous professional development. His research collaborations extend internationally with universities such as King Abdulaziz University, Universiti Tun Hussein Onn Malaysia, Universiti Malaysia Pahang, and the University of Manchester, underscoring his role as a global academic contributor in chemistry, nanotechnology, and membrane science.

 Profile: Scopus

Featured Publication

Abid, M. B. (Year). Exploring AlUla, Saudi Arabia: A journey through history, heritage, resources, and tourism. Journal Name, Volume(Issue), pages..

Joel Freidy Ebolembang | Complex Systems | Best Researcher Award

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Mr. Joel Freidy Ebolembang | Complex Systems
| Best Researcher Award

Mr. Joel Freidy Ebolembang | National Higher Polytechnic School of Douala | Cameroon

Mr. Joel Freidy Ebolembang is a dynamic PhD candidate in his third year at the Energy, Materials, Modeling, and Methods Laboratory of the National Higher Polytechnic School of Douala, Cameroon, where his research focuses on the innovative use of artificial intelligence and simulation for the control and diagnostics of dual-fuel engines. Holding a Master’s degree in Energy Research and an Engineering degree in Mechanical Construction, he has developed strong expertise in modeling, deep learning, and energy optimization, positioning himself at the intersection of mechanics, energy, and artificial intelligence. His academic journey has been enriched with advanced projects, including the study of diesel engine performance and the modeling of fatigue wear in automotive brake pads. He has published in reputable journals such as International Journal of Heat and Technology and Applied Sciences, and is actively working on novel applications of neural networks for intelligent diagnostics of diesel engines. Alongside his research, he has practical professional experience as an Assistant Train Driver at Camrail since 2020, where he ensures the safe and efficient operation of critical mechanical systems. Proficient in advanced engineering software like Ansys, OpenFOAM, Matlab, SolidWorks, and programming frameworks such as TensorFlow, PyTorch, and Keras, Joel demonstrates versatile technical competence. His research areas encompass CFD modeling, predictive diagnostics, and intelligent control of mechatronic systems, contributing to sustainable mobility and cleaner energy solutions. A shortlisted nominee for the Best Researcher Award, he exemplifies academic excellence, innovation, and dedication to advancing knowledge at the interface of engineering and artificial intelligence, with aspirations to drive impactful contributions in energy optimization and sustainable technologies.

 Profile: ORCID

Featured Publications

Applied Sciences (2025)
Ebolembang, J. F., Nkol, F. P. N., Tabejieu, L. M. A., Nono, F. T., & Abbe, C. V. N. (2025). Prediction of combustion parameters and pollutant emissions of a dual-fuel engine based on recurrent neural networks. Applied Sciences, 15(18), 9868.

International Journal of Heat and Technology (2023)
Nkol, F. P. N., Ebolembang, J. F., Banta, N. J. I., Yotchou, G. V. T., Abbe, C. V. N., & Mouangue, R. M. (2023). Simulating the effect of methanol and spray tilt angle on pollutant emission of a diesel engine using different turbulence models. International Journal of Heat and Technology, 41(5), 105–1120.

Sattar Ezzati | Transportation Systems | Best Researcher Award

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Prof. Sattar Ezzati | Transportation Systems | Best Researcher Award

Prof. Sattar Ezzati | Gorgan University of Agricultural Sciences and Natural Resources | Iran

Prof. Sattar Ezzati is an accomplished scholar in forest engineering and natural resource management, currently serving as Assistant Professor at Gorgan University of Agricultural Sciences and Natural Resources, Iran. With a strong academic foundation including a Ph.D. in Forest Engineering from Tarbiat Modares University and a Postdoctoral Fellowship at Université Laval, Canada, he has built expertise in forest logistics, biomass supply chains, bioenergy systems, and sustainable resource management. His research integrates mathematical modeling, operations research, and machine learning algorithms to optimize timber harvest scheduling, biomass procurement, and eco-efficient forest operations. He has contributed to cutting-edge projects on biochar production, GHG emissions reduction, biomass-to-bioenergy logistics, and participatory forest planning, with extensive field studies in steep-slope and ecologically sensitive regions. Prof. Ezzati has authored 18 peer-reviewed documents, with 194 citations across 171 indexed sources (h-index: 8), and actively reviews for leading international journals in forestry, sustainability, and environmental engineering. His global engagements include research visits in Sweden, Canada, the USA, and Austria, supported by competitive grants and fellowships. Recognized with awards such as the National Elites Institute Award and Young Assistant Professors Award, he continues to advance forest-based bio-economy and sustainable ecosystem management, mentoring Ph.D. and master’s students in innovative forestry research.

 Profile: Google Scholar | Scopus

Featured Publications

Ghanji Vatan, A., Ezzati, S., Tavankar, F., & Rahmani, R. (2025). The effect of skid trail designs on the recovery of soil physical properties. Forest Research and Development.

Jaddi Hosseini, S. A. R., Parsakhoo, A., Ezzati, S., & Rezaei Motlagh, A. (2025). The effect of using agricultural waste ash on improving the mechanical properties of forest roadbed soil. Forest Research and Development.

Ganji, A., Ezzati, S., Tavankar, F., & Rahmani, R. (2025). Assessment of the recovery of compacted soil physical properties after skidding operations in Kuhmian forests in Golestān province. Journal of Water and Soil Conservation.

Ezzati, S., Malek, I., Tavankar, F., & Parsakhoo, A. (2025). The role of management practices and trail layouts on postharvest healing of residual trees in mountain broadleaves forests. European Journal of Forest Research, 144(3), 621–633.

Ezzati, S. M. H. N. (2025). Long-term prediction of wound closure in residual damaged trees using Markov chain analysis. Biosystem Engineering, 254.

Norouzi Sangtabi, A., Parsakhoo, A., Ezzati, S., & Mostafa, M. (2025). Forest road network planning based on topological measures in Hyrcanian recreational forest parks using graph theory. Iranian Journal of Forest, 16(5), 87–98.