Dr. Suraj Yadav | Data-Driven Engineering | Research Excellence Award

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Dr. Suraj Yadav | Data-Driven Engineering | Research Excellence Award

Dr. Suraj Yadav | Mississippi State University | United States

Dr. Suraj Yadav is a researcher specializing in radar remote sensing, precision agriculture, and AI-driven geospatial analytics. His work integrates UAV-based multispectral, hyperspectral, LiDAR, and microwave sensing with physics-informed modeling and deep learning to enable robust crop monitoring, nitrogen estimation, and yield prediction. He has led the calibration and validation of advanced imaging spectroscopy platforms across diverse crop types and land surface conditions. His scholarly contributions include 21 research documents, receiving 173 citations across 141 citing publications, with an h-index of 6, reflecting sustained research impact.

Citation Metrics (Scopus)

200
150
100
50
0

Citations
173

Documents
21

h-index
6


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Featured Publications

Mrs. Hanane ABBOU | Biomedical Engineering | Research Excellence Award

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Mrs. Hanane ABBOU | Biomedical Engineering | Research Excellence Award

Mrs. Hanane ABBOU | Mohammed VI university of Sciences and Health | Morocco

Mrs. Hanane ABBOU is a PhD Candidate and Research Assistant in Medical Biotechnology at Mohammed VI University of Sciences and Health and the Mohammed VI Center for Research and Innovation. Her research focuses on computational investigations of cannabinoid-based therapeutics targeting the endocannabinoid system, with emphasis on Cannabis and Moroccan genetic diversity. She holds an MSc in Medical Biotechnology and has professional experience in pharmacovigilance and scientific publishing. Her scholarly profile reflects 14 citations by 13 documents, 7 published documents, and an h-index of 2, with the h-index view disabled in preview mode, highlighting her growing research impact in computational pharmacology.

Citation Metrics (Scopus)

20

15

10

5

0

Citations
14

Documents
7

h-index
2

🟦 Citations    🟥 Documents    🟩 h-index


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Featured Publications

Assist. Prof. Dr. Yan Zeng | AI in Engineering | Best Researcher Award

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Assist. Prof. Dr. Yan Zeng | AI in Engineering | Best Researcher Award

Assist. Prof. Dr. Yan Zeng | Hangzhou Dianzi University | China

Assist. Prof. Dr. Yan Zeng, an accomplished associate professor at the School of Computer Science, Hangzhou Dianzi University, has made significant contributions in the fields of distributed and parallel computing, distributed machine learning, and big data analytics. After earning her PhD from the Institute of Software, Chinese Academy of Sciences in 2016, her research has focused on advancing large-scale computation and data-intensive systems.  The Key Research and Development Program of Zhejiang Province, the Yangtze River Delta Project, and the Natural Science Foundation of Zhejiang Province. Her academic influence is reflected in 173 citations by 161 documents, 42 published papers, and an h-index of 9, demonstrating strong research impact and visibility. With 10 peer-reviewed publications in SCI and Scopus-indexed journals, Yan Zeng’s scholarly output showcases innovation in computational frameworks and distributed systems. Furthermore, she has been actively involved in practical technological advancements, holding 34 patents that bridge theoretical insights with industrial applications. Through her extensive research, publication record, and innovation-driven approach, Yan Zeng continues to play a pivotal role in shaping advancements in computer science and data engineering.

Profile: Scopus

Featured Publications

Zeng, Y., et al. (2025). FedAMM: Federated learning for brain tumor segmentation with arbitrary missing modalities [Conference paper]. Proceedings of the International Conference on Artificial Intelligence and Machine Learning.

Zeng, Y., et al. (2025). TransAware: An automatic parallel method for deep learning model training with global model structure awareness [Conference paper]. Proceedings of the International Conference on Advanced Computing and Applications.

Zeng, Y., et al. (2025). A correlation analysis-based federated learning framework for defending against collusion-free-riding attacks. Cybersecurity, 2025(1), 1–12.

Zeng, Y., et al. (2025). FedAEF: Optimizing federated learning with mining and enhancing local data features. Cluster Computing, 2025(1), 1–15.

Mr. Chaohui Zhao | Structural Engineering | Best Researcher Award

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Mr. Chaohui Zhao | Structural Engineering | Best Researcher Award

Mr. Chaohui Zhao | shanghai dianji university | China

Mr. Chaohui Zhao is a distinguished researcher specializing in power electronics, motion control, and the design and control of special electric machines. His work encompasses advanced motion control systems, high-performance power conversion technologies, and energy-efficient electric machine design. He has contributed to multiple research projects focused on integrating power electronics with motion control to improve system performance, reliability, and efficiency. Professor Zhao has authored several technical publications and holds patents such as CN119834502A, demonstrating his focus on translating research into practical engineering solutions. His research has impacted the development of intelligent drive technologies, precision control of electromechanical devices, and optimization of industrial electrification systems. By bridging theoretical innovation with applied engineering, his work advances knowledge in power electronics and specialized electric machines while addressing practical challenges in automation and electrical system design.

Profile: Orcid

Featured Publications

Gao, H., Zhao, C., & Cao, Z. (2025). Research on motor torque performance of AHRPM motor based on MFS effect. IEEJ Transactions on Electrical and Electronic Engineering. Advance online publication.

Tan, F., Ma, Y., & Zhao, C. (2025). Research on speed control of PMSM based on super-twisting sliding mode corrected differential linear active disturbance rejection. Energies, 18(17455).

Cao, Z., Zhao, C., & Gao, H. (2025). Structural optimization and characteristic analysis of TMPS-HEG based on particle swarm optimization algorithm. Journal of Electrical Engineering & Technology. Advance online publication.

Xie, S., Zhang, W., Feng, X., Zhang, W., Gu, P., Lei, Z., & Zhao, C. (2025). Torque ripple suppression of open-winding permanent magnet synchronous motor with common DC bus based on field circuit coupling method. International Journal of Circuit Theory and Applications. Advance online publication.

Ma, Y., Zhao, C., Gu, P., Lei, Z., & Zhang, W. (2025). Speed control of PMSM based on series lead correction doubly fed differential LADRC. International Journal of Circuit Theory and Applications. Advance online publication.

Cao, Z., Zhao, C., & Gao, H. (2025). Research on the four-quadrant operating mechanism of a hybrid excitation generator with magnetic field modulation and the power distribution ratio between permanent magnet and magnetic field modulation. International Journal of Circuit Theory and Applications. Advance online publication.

Dr. Zahra Beheshti | AI in Engineering | Best Researcher Award

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Dr. Zahra Beheshti | AI in Engineering | Best Researcher Award

Dr. Zahra Beheshti | Islamic Azad University | Iran

Dr. Zahra Beheshti is an Assistant Professor at the Islamic Azad University, Najafabad Branch, with a distinguished background in computer engineering and artificial intelligence. She holds a B.Sc. and M.Sc. in Computer Engineering (Software) and a Ph.D. in Computer Science with a focus on Artificial Intelligence, followed by postdoctoral research in Soft Computing. Dr. Beheshti has made significant contributions to the field, including the compilation of the book Centripetal Accelerated Particle Swarm Optimization and Applications. Her academic excellence has been recognized through scholarships awarded to top international Ph.D. students. She is actively involved in knowledge dissemination, having conducted multiple workshops on advanced topics such as Machine Learning, Fuzzy Expert Systems and their application in algorithm parameter determination, and Introduction to Fuzzy Logic along with the Design and Implementation of Fuzzy Expert Systems. Her research output includes 34 documents, cited 1,865 times by 1,698 publications, with an h-index of 20, reflecting the significant impact of her work. Through her teaching, research, and publications, Dr. Beheshti demonstrates a strong commitment to advancing computational intelligence, fostering innovation, and mentoring the next generation of researchers in AI and soft computing, combining both academic rigor and practical application.

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Featured Publications

  • Z Beheshti, SMH Shamsuddin, A review of population-based meta-heuristic algorithms, Int. J. Adv. Soft Comput. Appl 5 (1), 1-35, 744 citations, 2013

  • H Abedinpourshotorban, SM Shamsuddin, Z Beheshti, DNA Jawawi, Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm, Swarm and Evolutionary Computation 26, 8-22, 414 citations, 2016

  • M Jafarzadegan, F Safi-esfahani, Z Beheshti, Combining Hierarchical Clustering approaches using the PCA Method, Expert Systems with Applications 137, 1-10, 156 citations, 2019

  • Z Beheshti, SM Shamsuddin, S Hasan, Memetic binary particle swarm optimization for discrete optimization problems, Information Sciences 299, 58-84, 129 citations, 2015

  • Z Beheshti, SMH Shamsuddin, CAPSO: centripetal accelerated particle swarm optimization, Information Sciences 258, 54-79, 120 citations, 2014

  • M Banaie-Dezfouli, MH Nadimi-Shahraki, Z Beheshti, R-GWO: Representative-based grey wolf optimizer for solving engineering problems, Applied Soft Computing 106, 1-28, 108 citations, 2021

 

 

Dr. Bin Zhang | Structural Engineering | Best Researcher Award

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Dr. Bin Zhang | Structural Engineering | Best Researcher Award

Dr. Bin Zhang | Chongqing University of Science and Technology | China

Dr. Bin Zhang holds a Doctorate in Engineering and has completed postdoctoral research. He is a lecturer and master’s supervisor in the Department of Road and Bridge Engineering, School of Civil and Hydraulic Engineering, and a youth committee member of the World Transport Convention. His research focuses on the dynamic characteristics of underground and tunnel structures, the development of new materials and technologies for structural reinforcement, and intelligent monitoring of structural health. His research output includes 26 documents, 171 citations, 146 citing documents, and an h-index of 8. He teaches both undergraduate and postgraduate courses, including Tunnel Engineering, Engineering Surveying, Tunnel Mechanics, and Frontier Technologies in Civil Engineering, integrating theoretical knowledge with practical applications to advance innovation in civil and tunnel engineering. Additionally, he has developed advanced experimental methods for studying tunnel lining mechanics, contributing to safer and more efficient tunnel design practices.

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Featured Publications

  • Study on the Stability of Buildings During Excavation in Urban Core Areas, Applied Sciences, 2025. Contributors: Kang Liu, Huafeng Liu, Yuntai Gao, Zijian Wang, Yunchuan Wang, Qi Liu, Chaolin Jia, Zihang Huang, Bin Zhang.

  • Experimental Study on Mechanical Differences Between Prefabricated and Cast-In Situ Tunnel Linings Based on a Load-Structure Model, Buildings, 2025. Contributors: Li-Ming Wu, Hong-Kun Li, Feng Gao, Zi-Jian Wang, Bin Zhang, Wen-Jie Luo, Jun-Jie Li.

  • Mechanical Properties of Steel Fiber-Reinforced Concrete Tunnel Secondary Lining Structure and Optimization of Support Parameters, Buildings, 2025. Contributors: Zijian Wang, Yunchuan Wang, Xiaorong Wang, Baosheng Rong, Bin Zhang, Liming Wu, Chaolin Jia, Zihang Huang.

  • Crystallization Blockage in Highway Tunnel Drainage System Based on Molecular Dynamics, AIP Advances, 2025. Contributors: Shiyang Liu, Xuefu Zhang, Bin Zhang.

  • Experimental Study on Grouting Diffusion Law of Tunnel Secondary Lining Cracks Based on Different Slurry Viscosities, Applied Sciences, 2025. Contributors: Bin Zhang, Peng Liu, Yi Wu, Liming Wu, Chen Li, Shiyang Liu, Yuanfu Zhou.

  • Experimental Study on Grouting Diffusion Law of the Different Crack Widths in Tunnel Lining, KSCE Journal of Civil Engineering, 2023. Contributors: Bin Zhang, Yuanfu Zhou, Xuefu Zhang, Zijian Wang, Wei Yang, Yixuan Ban.

  • Anti Crystallization Blocking of Flocking Drainage Pipe Based on Natural Phenomenon, Materials Science, 2022. Contributors: Xuefu Zhang, Shiyang Liu, Feng Gao, Yuanfu Zhou, Bin Zhang.

Dr. Priya Tyagi | Sustainable Engineering | Best Researcher Award

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Dr. Priya Tyagi | Sustainable Engineering | Best Researcher Award

Dr. Priya Tyagi | Sharda University | India

Dr. Priya Tyagi is a dedicated sustainable architect with extensive academic and professional expertise in sustainable design and rural housing development. She earned her Doctor of Philosophy from Malaviya National Institute of Technology, Jaipur, focusing on a decision-making framework for design quality assessment of rural houses in India, following her Master of Architecture in Sustainable Architecture from Deenbandhu Chhotu Ram University of Science and Technology, Murthal, and Bachelor of Architecture from Shri Ram Group of Colleges, Lucknow. She has actively contributed to research and practice in architecture, including a joint research project on municipal waste management at Massachusetts Institute of Technology, Boston, and holds professional credentials as a Green Rating for Integrated Habitat Assessment certified professional. Currently, she serves as Assistant Professor at Sharda School of Design, Architecture and Planning, Greater Noida, having previously held academic positions at Sanskar College of Architecture and Planning and practical experience with Shelter Architects and M/s Raj Architects and Builders. Dr. Tyagi has been recognized for her expertise through appointments as a reviewer for Scopus-indexed journals, including the Journal of Infrastructure, Policy and Development, and the Journal of Civil, Construction and Environmental Engineering. Her research output includes 9 documents with 6 citations and an h-index of 2, reflecting her growing impact in sustainable architecture, design quality assessment, and environmentally responsible building practices in India.

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Featured Publications

Tyagi, P., Shrivastava, B., & Kumar, N. (2024). Investigating rural housing quality indicators in the Indian scenario for inclusive imageability. Environment, Development and Sustainability, 26(10), 25609-25643.

Tyagi, P., Shrivastava, B., & Kumar, N. (2023). Towards creating inclusive villages: The types of rural settlements in India. ISVS e-Journal, 10(2), 91-106.

Bhyan, P., Tyagi, P., Doddamani, S., Kumar, N., & Shrivastava, B. (2023). Life cycle assessment of lightweight and sustainable materials. Lightweight and Sustainable Composite Materials, 117-142.

Tyagi, P., Shrivastava, B., & Kumar, N. (2024). A comprehensive investigation of rural and low-rise housing design quality: A thematic and bibliometric analysis. Journal of Housing and the Built Environment, 39(3), 1323-1353.

Tyagi, P., Shrivastava, B., & Kumar, N. (2025). Optimizing rural housing design quality: Indicators and parameters for comprehensive assessment. Environment, Development and Sustainability, 1-43.

Prof. Ouajdi Korbaa | AI in Engineering | Innovative Research Award

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Prof. Ouajdi Korbaa | AI in Engineering | Innovative Research Award

Prof. Ouajdi Korbaa | University of Sousse | Tunisia

Prof. Ouajdi Korbaa is a distinguished researcher and professor at the Institute of Computer Science and Communication Techniques, University of Sousse, Tunisia, and a member of the Modeling of Automated Reasoning Systems Laboratory. His research focuses on modeling, discrete optimization, scheduling, and artificial intelligence, contributing significantly to the development of advanced methodologies in these areas. He has supervised numerous Master’s and PhD students and actively participates in academic juries, reflecting his commitment to mentoring the next generation of researchers. Prof. Korbaa has authored 157 documents cited by 998 sources, achieving an h-index of 18, demonstrating his strong impact and influence in the field. His work integrates theoretical foundations with practical applications, advancing computational techniques for problem-solving and decision-making. Recognized for his expertise in optimization and AI, he has made substantial contributions to both the academic community and the broader field of computer science, fostering innovation in modeling and automated reasoning systems.

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Featured Publications

  • Nssibi, M., Manita, G., & Korbaa, O. (2023). Advances in nature-inspired metaheuristic optimization for feature selection problem: A comprehensive survey. Computer Science Review, 49, 100559.

  • Jemili, F., Meddeb, R., & Korbaa, O. (2024). Intrusion detection based on ensemble learning for big data classification. Cluster Computing, 27(3), 3771–3798.

  • Benzarti, S., Triki, B., & Korbaa, O. (2017). A survey on attacks in Internet of Things based networks. In Proceedings of the 2017 International Conference on Engineering & MIS (ICEMIS) (pp. 1–7).

  • Meddeb, R., Jemili, F., Triki, B., & Korbaa, O. (2023). A deep learning-based intrusion detection approach for mobile Ad-hoc network. Soft Computing, 27(14), 9425–9439.

  • Abid, A., Jemili, F., & Korbaa, O. (2024). Real-time data fusion for intrusion detection in industrial control systems based on cloud computing and big data techniques. Cluster Computing, 27(2), 2217–2238.

  • Korbaa, O., Camus, H., & Gentina, J. C. (1997). FMS cyclic scheduling with overlapping production cycles. In Proceedings of the 18th International Conference on Application and Theory of Automation in Technology (pp. 1–10).

  • Lee, J., & Korbaa, O. (2004). Modeling and scheduling of ratio-driven FMS using unfolding time Petri nets. Computers & Industrial Engineering, 46(4), 639–653.

  • Meddeb, R., Triki, B., Jemili, F., & Korbaa, O. (2017). A survey of attacks in mobile ad hoc networks. In Proceedings of the 2017 International Conference on Engineering & MIS (ICEMIS) (pp. 1–7).

 

Ms. Ekaterina Sadikova | Heat Transfer Analysis | Best Researcher Award

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Ms. Ekaterina Sadikova | Heat Transfer Analysis | Best Researcher Award

Ms. Ekaterina Sadikova | Peter the Great St.Petersburg Polytechnic University | Russia

Ms. Ekaterina Sadikova is a postgraduate student at Peter the Great St. Petersburg Polytechnic University, specializing in Thermo physics and Theoretical Heat Engineering, and currently working as a Research Scientist at Aurora Chemicals LLC. She earned her Bachelor’s degree in Applied Mathematics and Physics and a Master’s degree with honors in 2023 from the same institution, where she also received recognition for her strong academic achievements. Her research interests lie at the intersection of computational modeling, thermophysical processes, and applied mathematics, with an emphasis on validating theoretical models through experimental methods. She has contributed to both fundamental and applied research, completing projects such as her Bachelor’s thesis on the propagation of laminar flames over combustible surfaces and her Master’s thesis on computational analysis of the temperature state of fuel assemblies in the spent fuel pool of the Beloyarskaya Nuclear Power Plant under beyond-design accident conditions. Her expertise has been applied to consultancy and industry projects with organizations such as Atom Energy Project and Aurora Chemicals LLC, where she is engaged in developing a laboratory-scale prototype for synthesizing hexafluoroethane. She was recognized with the Best Presentation Award at the Minsk International Heat and Mass Transfer Forum.

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Featured Publications

  • Sadikova, E. V. (2023). Computational analysis of the temperature state of fuel rods in the spent fuel pool of power unit No. 4 at the Beloyarsk Nuclear Power Plant under beyond-design basis accidents (Master’s thesis). Peter the Great St. Petersburg Polytechnic University.

  • Sadikova, E. V., & Snegiryov, A. Yu. (2022). Propagation of a laminar flame over the surface of a combustible material. Science Week, PhysMech, 291–293.

 

Dr. Goutam Khankari | Sustainable Engineering | Best Researcher Award

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Dr. Goutam Khankari | Sustainable Engineering | Best Researcher Award

Dr. Goutam Khankari | Damodar Valley Corporation | India

Dr. Goutam Khankari is a distinguished researcher and engineer specializing in thermal power systems. His PhD research, titled “Thermodynamic Analysis and Performance Improvement of Coal-Fired Thermal Power Plants,” focused on a comprehensive 4-E approach—Energy, Exergy, Environment, and Economic analysis—of various coal-fired steam power plants using high-ash Indian coals. The primary objective of his work was to enhance the overall efficiency and net power output of these plants by exploiting low-grade waste energy through the Kalina Cycle System, integrating solar energy, and optimizing operational conditions. Dr. Khankari’s research not only provides critical insights into energy and exergy efficiencies but also emphasizes sustainable practices and environmental considerations in coal-based power generation. His work has been widely recognized, reflected in 97 citations across 88 documents and an h-index of 5, demonstrating significant academic influence. Through his innovative approaches to performance improvement and waste energy utilization, Dr. Khankari has contributed meaningfully to the field of thermal engineering, offering practical solutions for maximizing energy output while minimizing environmental impact in India’s coal-fired power sector.

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Featured  Publications

Khankari, G., & Karmakar, S. (2016). Power generation from coal mill rejection using Kalina cycle. Journal of Energy Resources Technology, 138(5), 052004.

Khankari, G., Munda, J., & Karmakar, S. (2016). Power generation from condenser waste heat in coal-fired thermal power plant using Kalina cycle. Energy Procedia, 90, 613–624.

Khankari, G., & Karmakar, S. (2018). Power generation from fluegas waste heat in a 500 MWe subcritical coal-fired thermal power plant using solar assisted Kalina Cycle System 11. Applied Thermal Engineering, 138, 235–245.

Khankari, G., & Karmakar, S. (2021). A novel solar assisted Kalina cycle system for waste heat utilization in thermal power plants. International Journal of Energy Research, 45(12), 17146–17158.

Roge, N. H., Khankari, G., & Karmakar, S. (2022). Waste heat recovery from fly ash of 210 MW coal fired power plant using organic rankine cycle. Journal of Energy Resources Technology, 144(8), 082107.

Khankari, G., & Karmakar, S. (2014). Operational optimization of turbo-generator (TG) cycle of a 500MW coal-fired thermal power plant. In 2014 6th IEEE Power India International Conference (PIICON) (pp. 1–6).

Khankari, G., Karmakar, S., Pramanick, A., & Biswas, M. (2013). Thermodynamic analysis of a 500MW coal-fired Indian power plant. In ESMOC Conference, NIT Durgapur, India.