Assoc. Prof. Dr Wei Wang | Smart Grid Systems | Best Researcher Award

Assoc. Prof. Dr Wei Wang | Smart Grid Systems | Best Researcher Award

Assoc. Prof. Dr Wei Wang | Nanjing Normal University | China

Assoc. Prof. Dr. Wei Wang, is an accomplished Associate Professor and Assistant to the Dean at the School of Electrical and Automation Engineering, Nanjing Normal University, and an IEEE Senior Member recognized for his extensive contributions to electrical engineering. Holding M.S. and Ph.D. degrees from Southeast University, his research expertise spans electromagnetic field computation, energy harvesting, and innovative wireless power transfer (WPT) systems. He has successfully led or participated in 26 research projects and 21 consultancy collaborations with industry, published 35 peer-reviewed journal papers, authored two academic books, and holds 32 patents. His research achievements are reflected in 1,165 citations by 972 documents, with 90 publications and an h-index of 19. As an editorial board member and guest editor of several international journals, Dr. Wang also serves as a guest researcher at the State Key Laboratory for Smart Grid Protection and Operation Control. His notable innovation—the PPS-S topology with adjustable output power and a quasi-constant-power-constant-voltage (QCP-CV) charging strategy—addresses the limitations of conventional WPT systems by achieving zero-voltage-switching (ZVS) while maintaining power stability around 65 W and reducing power fluctuation by 80% under varying loads. His pioneering work has earned him prestigious honors, including the Second Prize for Scientific Research and Technological Invention from the Ministry of Education and a Gold Award at the 2023 Geneva International Invention Exhibition, solidifying his impact in advanced power transfer technologies.

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Featured Publications

Wang, W. (2025). Research on self-powered high precision voltage measurement technology for the power lines based on the inversion of electric field. Zhongguo Dianji Gongcheng Xuebao Proceedings of the Chinese Society of Electrical Engineering.

Wang, W. (2025). Regulation strategy of impact response of regional integrated energy system based on ultra short term prediction. Journal of Electrical Engineering China.

Wang, W. (2025). Optimized constant power charging of PT-symmetry-based three-coil WPT system. Conference Paper.

Wang, W. (2025). Analysis and optimization of energy harvesting characteristics of converter valve magnetic field self-powered harvester. Electric Power Engineering Technology.

Wang, W. (2025). Extended effective distance of PT-symmetry-based double-coil WPT system. Conference Paper.

Wang, W. (2025). Quasi-constant power wireless charging strategy based on power adjustable PPS-S topology. Journal of Power Electronics.

Dr. Aamir Ali | Smart Grid Systems | Best Researcher Award

Dr. Aamir Ali | Smart Grid Systems | Best Researcher Award

Dr. Aamir Ali | Quaid-e-Awam University of Engineering Science and Technology | Pakistan

Dr. Aamir Ali is currently serving as an Assistant Professor (BPS-19) in the Department of Electrical Engineering at Quaid-e-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan. He is a highly dedicated academic and researcher specializing in power system planning and optimization, distributed generation, and microgrid operations in both islanded and grid-connected modes. Dr. Ali earned his Ph.D. in Electrical Engineering from QUEST in 2020, where his doctoral research focused on single and multi-objective mathematical programming, direct search evolutionary algorithms, and optimization techniques for economic dispatch, optimal power flow, and unit commitment with renewable energy integration such as wind and solar PV systems. Prior to his doctorate, he completed his Master of Engineering in Power System Optimization from the same institution in 2015 and his Bachelor of Engineering in Electrical Power with an outstanding 85% score in 2012. His academic journey began with strong foundational performance at the intermediate and matriculation levels, both from the Board of Intermediate and Secondary Education, Hyderabad, Sindh, where he secured first division and A-1 grade distinctions. With 445 citations by 342 documents, 27 published works, and an h-index of 11, Dr. Aamir Ali has established himself as an active researcher in power systems optimization. He aspires to continue contributing to academia and research while leading a top-tier institution toward excellence in education and innovation.

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Featured Publications

Akbar Talani, R., Kaloi, G. S., Ali, A., Abbas, G., Emara, A., & Touti, E. (2025, July 29). Fault analysis and performance improvement of grid-connected doubly fed induction generator through an enhanced crowbar protection scheme. PLOS One.

Ali, A., Akbar Talani, R., Kaloi, G. S., Bijarani, M. A., Abbas, G., Hatatah, M., Mercorelli, P., & Touti, E. (2025, January 29). Dynamic performance analysis and fault ride-through enhancement by a modified fault current protection scheme of a grid-connected doubly fed induction generator. Machines, 13(2).

Ali, A., Ali, A., Liu, Z., Abbas, G., Touti, E., & Nureldeen, W. (2024). Dynamic multi-objective optimization of grid-connected distributed resources along with battery energy storage management via improved bidirectional coevolutionary algorithm. IEEE Access.

Ali, A., Shah, A., Keerio, M. U., Mugheri, N. H., Abbas, G., Touti, E., Hatatah, M., Yousef, A., & Bouzguenda, M. (2024). Multi-objective security constrained unit commitment via hybrid evolutionary algorithms. IEEE Access.

Abbas, G., Wu, Z., & Ali, A. (2024, December). A two-stage reactive power optimization method for distribution networks based on a hybrid model and data-driven approach. IET Renewable Power Generation.

Ali, A., Aslam, S., Mirsaeidi, S., Mugheri, N. H., Memon, R. H., Abbas, G., & Alnuman, H. (2024, December). Multi-objective multiperiod stable environmental economic power dispatch considering probabilistic wind and solar PV generation. IET Renewable Power Generation.

Prof. Aleksander Yurov | Robotics & Automation | Best Researcher Award

Prof. Aleksander Yurov | Robotics & Automation | Best Researcher Award

Dr. Aleksander Yurov | Don State Technical University | Russia

Prof. Aleksander Yurov is the Head of the Department of Digital Technologies and Platforms in the Electric Power Industry at Don State Technical University, leading multiple high-impact research and innovation initiatives. He serves as the principal executor of grants from the Russian Science Foundation and the Foundation for the Promotion of Innovation, working on programs such as START, DevelopmentNTI/Energynet, CODE-Digital Technologies, and Export, with a focus on “Resource-saving Energy” and “New Devices and Intelligent Production Technologies.” His research encompasses diagnostics of power cable lines, devices and methods for detecting damage to overhead lines, relay protection and emergency automation, and monitoring and analysis of insulation materials in distribution networks. Yurov has published over 60 scientific articles, holds four utility model patents, eight computer certificates, and has authored six textbooks, demonstrating a robust commitment to both academic scholarship and applied innovation. His completed and ongoing projects include a Russian Science Foundation grant on the vibrational-wave phenomena affecting dielectric composition and residual insulation life in power transmission lines, as well as projects on adaptive high-voltage power supply technology for intelligent diagnostic systems and the deployment of software-hardware complexes for distribution network diagnostics in international markets. He has actively contributed to consultancy and industry projects, totaling five, strengthening the bridge between research, practical implementation, and technological advancement in the electric power sector.

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Featured Publications

  • Yurov, A. A. (2023). Device for determining the places of damage to the insulation of 6-10 kV power cable lines based on intelligent control functions. Electrical Stations.

  • Yurov, A. A. (2021). Determining the mode of operation of the system section, taking into account the current topology and predictive analysis of the active-adaptive network of 6-10 kV. Conference Paper.

  • Yurov, A. A. (2021). High-voltage smart electricity metering of 110 kV digital electric networks. Conference Paper.

  • Yurov, A. A., & Voronov, A. S. (2021). Improving the efficiency of technical means and methods for diagnostics of isolation of high-voltage distribution networks. IOP Conference Series: Materials Science and Engineering, 1029(1), 012038.

  • Yurov, A. A., Minkin, M. S., & Kuimov, D. N. (2021). Schemes of high-voltage rectifiers as part of dust removal electric gates. IOP Conference Series: Materials Science and Engineering, 1029(1), 012044.

 

Dr. Qinglu Fan | Renewable Energy | Best Researcher Award

Dr. Qinglu Fan | Renewable Energy | Best Researcher Award

Dr. Qinglu Fan | YiBin Vocational And Technical College | China

Dr. Qinglu Fan is a lecturer at YiBin Vocational and Technical College, specializing in materials science and engineering with a research focus on nickel-based layered cathode materials for lithium-ion batteries. She earned her doctoral degree at Guangdong University of Technology from 2016 to 2021 and conducted research as a visiting Ph.D. student at Binghamton University from 2019 to 2021. Her work centers on interface and bulk regulation of Ni-rich layered cathode materials to enhance their electrochemical performance, stability, and efficiency. She has published more than ten papers as the first author in international journals, including Journal of Power Sources, ACS Applied Materials & Interfaces, and Applied Materials Today, and authored the book “Lithium-ion Battery Nickel-based Layered Cathode Materials and Its Modifications.” Her research is supported by multiple ongoing projects, including participation in the National Natural Science Foundation of China, as principal investigator of the Ph.D. Startup Fund at Yibin Vocational and Technical College, and leadership of the Academician Ouyang Minggao Workstation Youth Talent Development Fund. With an h-index of ten, she continues to contribute to the advancement of sustainable energy storage materials and innovative solutions for next-generation lithium-ion batteries.

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Featured Publications

  • Fan, Q., Li, X., Cheng, Y., Hu, Y., Ma, W., & Chen, Z. (2025). Enhanced cycling stability of nickel-rich single-crystal LiNi0.83Co0.12Mn0.05O2 at high voltage via low-temperature epitaxial rock-salt interface engineering. Journal of Materials Science.

  • Fan, Q., Li, X., Cheng, Y., Hu, Y., Ma, W., Almuqrin, A. H., Alodhayb, A. N., Chen, Z., & Shi, Z. (2025). Comprehensive investigation of the impact of calcination temperature-induced Li/Ni mixing on LiNi0.8Mn0.1Co0.1O2. Materials Today Energy.

  • Fan, Q., Chen, Z., Ma, W., & Shi, Z. (2025). Examining the collaborative impact of a heterojunction TiO2 coating and Ti substitution on LiNi0.8Co0.1Mn0.1O2 via a single-step modification approach. Applied Materials Today.

  • Fan, Q. (2021). Heterojunction TiO2@TiOF2 nanosheets as superior anode materials for sodium-ion batteries. Journal of Materials Chemistry A.

  • Fan, Q., Lin, K., Guan, S., Chen, J., Feng, S., Liu, L., & Shi, Z. (2021). Constructing high conductive composite coating with TiN and polypyrrole to improve the performance of LiNi0.8Co0.1Mn0.1O2 at high cutoff voltage of 4.5 V. ACS Applied Energy Materials.

  • Fan, Q. (2021). Can greener Cyrene replace NMP for electrode preparation of NMC 811 cathodes? Journal of The Electrochemical Society.

 

 

 

Prof. Dr. Galina Malykhina | Biomedical Engineering | Best Researcher Award

Prof. Dr. Galina Malykhina | Biomedical Engineering | Best Researcher Award

Prof. Dr. Galina Malykhina | Peter the Great Saint Petersburg Polytechnic University | Russia

Prof. Dr. Galina Malykhina is a distinguished scientist and educator affiliated with the Peter the Great St. Petersburg Polytechnic University, serving at the Institute of Informatics and Cybersecurity, Graduate School of Computer Technology and Information Systems. She earned her foundational and advanced degrees from the St. Petersburg Polytechnic Institute, completing her PhD in Technical Cybernetics and later defending her DSc thesis in Information, Measurement, and Control Systems. Over her prolific career, Galina Malykhina has made significant contributions to the development of technical diagnostics systems, measurement technologies for two-phase and multiphase flows in the oil industry, and intelligent medical measurement systems utilizing artificial neural networks. Her expertise extends to advanced control mechanisms for thermal power plants and industrial automation processes. As an academic, she has delivered comprehensive lectures on Information Technology, Computer Networks, and Machine Vision, shaping generations of engineers and researchers. Her research output includes 38 documents with 89 citations from 73 documents and an h-index of 5. Her scholarly influence is reflected through numerous publications indexed in Google Scholar, DBLP, Semantic Scholar, and ORCID. Galina Malykhina’s research continues to bridge cybernetics, intelligent systems, and applied informatics, reinforcing her reputation as a leading figure in Russian and international computer science and control engineering.

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Featured Publications

Malykhina, G. F., & Guseva, A. I. (2017). Early fire prevention in the plant. Industrial Engineering, Applications and Manufacturing (ICIEAM).

Tarkhov, D. A., & Malykhina, G. F. (2019). Neural network modelling methods for creating digital twins of real objects. Journal of Physics: Conference Series, 1236(1), 012056.

Malykhina, G. F., & Tarkhov, D. A. (2018). Digital twin technology as a basis of the industry in future. European Proceedings of Social and Behavioural Sciences, 51.

Lazovskaya, T., Malykhina, G., & Tarkhov, D. (2021). Physics-based neural network methods for solving parameterized singular perturbation problem. Computation, 9(9), 97.

Dashkina, A., Khalyapina, L., Kobicheva, A., Lazovskaya, T., Malykhina, G., & others. (2020). Neural network modeling as a method for creating digital twins: From industry 4.0 to industry 4.1. Proceedings of the 2nd International Scientific Conference on Innovations in …

Vasilyev, A. N., Tarkhov, D. A., & Malykhina, G. F. (2018). Methods of creating digital twins based on neural network modeling. Sovremennye Informatsionnye Tekhnologii i IT-Obrazovanie, 14(3), 521–532.*

Dr. Anatoly Nikolaevich Makarov | Heat Transfer Analysis | Distinguished Scientist Award

Dr. Anatoly Makarov | Heat Transfer Analysis | Distinguished Scientist Award

Dr. Anatoly Makarov | Tver State Technical University | Russia

Dr. Anatoly Nikolaevich Makarov is a Doctor of Engineering Sciences, Professor, and Honoured Worker of the Higher School of the Russian Federation. He has served as the Head of the Electric Power Supply and Electrical Engineering Department at Tver State Technical University since 1996. He is a leading specialist in power engineering and the author of a scientific discovery recognized with the P.L. Kapitsa Gold Medal “For Scientific Discovery.” His research output includes 65 documents, cited 59 times by 26 other works, with an h-index of 3. He has developed a pioneering theory of heat transfer in electric arc steelmaking furnaces and discovered the laws of thermal radiation from gas volumes of electric arcs and torches—achievements comparable to the classical laws of Stefan, Boltzmann, Wien, and Planck. Based on these discoveries, he formulated a multidisciplinary heat transfer calculation method applied to electric arc and torch furnaces, boiler fireboxes, and combustion chambers of gas turbine plants. His work, documented in monographs, textbooks, and numerous journal articles, is widely used in research and education, shaping advancements in power engineering, metallurgy, heat technology, and applied physics.

Profile: Scopus

Featured Publications

  • Makarov, A. N. (2025). Convective and conductive heat transfer in the bath under the arcs of high-power arc steel-melting furnaces: Part II. Distribution of isotherms over the surfaces of slag and metal in the EAF. Metallurgist.

  • Makarov, A. N. (2025). Heat transfer by convection and conduction in the bath beneath the arcs of high-power arc steel-melting furnaces: Part I. Laws of thermal radiation of gas volumes in arcs and flames and their use for calculating heat transfer in electric arc furnaces (EAF). Metallurgist.

  • Makarov, A. N. (2025). Calculation of thermal fluxes of arc radiation over the surface and depth of the bath of electric arc steelmaking furnaces. Conference Paper.

  • Makarov, A. N. (2024). Complex heat transfer in a bath under arcs of high-power arc steel-melting furnaces: Part III. Evaporation of metal under arcs and influence of the absorption coefficient of the furnace atmosphere on flow density. Metallurgist.

  • Makarov, A. N. (2024). Complex heat transfer in a bath under arcs of high-power arc steel-melting furnaces: Part II. Conversion of radiant arc flows into convection and heat conduction flows in the bath. Metallurgist.

  • Makarov, A. N. (2024). Complex heat transfer in a bath under arcs of high-power arc steel-melting furnaces: Part I. Laws of thermal radiation of gas volumes and their rationale for calculating heat transfer in EAFs. Metallurgist.

 

Dr. Sekhar Reddy Kola | Semiconductor Devices | Best Researcher Award

Dr. Sekhar Reddy Kola | Semiconductor Devices | Best Researcher Award

Dr. Sekhar Reddy Kola | National Yang Ming Chiao Tung University | Taiwan

Dr. Sekhar Reddy Kola is a distinguished Postdoctoral Fellow at the National Yang Ming Chiao Tung University, Taiwan, with a Ph.D. in Electrical and Computer Engineering, specializing in semiconductor devices. His doctoral research, under the supervision of Professor Yiming Li, focused on the process variation effects and intrinsic parameter fluctuations of vertically stacked gate-all-around silicon nanosheet complementary field-effect transistors. His expertise spans advanced semiconductor device physics and modeling, including gate-all-around nanosheet and nanowire metal-oxide-semiconductor field-effect transistors, negative capacitance field-effect transistors, and complementary field-effect transistor circuit and static random-access memory designs. Dr. Kola’s work integrates statistical modeling, data analysis, and machine learning for performance optimization and variability analysis in nanoscale devices. With proficiency in technology computer-aided design, finite element method modeling, and quantum transport models, he has conducted extensive simulations related to process engineering, doping profiles, and stress effects. His research contributions also extend to radio frequency, reliability, and S-parameter analyses, highlighting his deep understanding of both theoretical and experimental semiconductor design. His research output includes 33 documents with 311 citations by 192 documents and an h-index of 10, reflecting the global recognition of his impactful scientific contributions. A recipient of the Best Paper Award at IEDMS in 2018 and the Outstanding Foreign Student Scholarship from 2017 to 2022, Dr. Kola exemplifies excellence in nanoelectronics and semiconductor innovation.

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Featured Publications

Sreenivasulu, V. B., Neelam, A. K., Kola, S. R., Singh, J., & Li, Y. (2023). Exploring the performance of 3-D nanosheet FET in inversion and junctionless modes: Device and circuit-level analysis and comparison. IEEE Access, 11, 90421–90429.

Yang, Y. S., Li, Y., & Kola, S. R. R. (2023). A physical-based artificial neural networks compact modeling framework for emerging FETs. IEEE Transactions on Electron Devices, 71(1), 223–230.

Butola, R., Li, Y., & Kola, S. R. (2022). A machine learning approach to modeling intrinsic parameter fluctuation of gate-all-around Si nanosheet MOSFETs. IEEE Access, 10, 71356–71369.

Kola, S. R., & Thoti, N. (2020). Characteristics of gate-all-around silicon nanowire and nanosheet MOSFETs with various spacers. 2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD), 26.

Kola, S. R., Li, Y., & Thoti, N. (2020). Effects of spacer and single-charge trap on voltage transfer characteristics of gate-all-around silicon nanowire CMOS devices and circuits. 2020 IEEE 20th International Conference on Nanotechnology (IEEE-NANO), 217–220.

Yu, X. R., Chuang, M. H., Chang, S. W., Chang, W. H., Hong, T. C., Chiang, C. H., … Kola, S. R. (2022). Integration design and process of 3-D heterogeneous 6T SRAM with double layer transferred Ge/2Si CFET and IGZO pass gates for 42% reduced cell size. 2022 International Electron Devices Meeting (IEDM), 20.5.1–20.5.4.

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

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

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

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.