G.N.Lalith Pankaj Raj Nadimuthu | Renewable Energy | Best Researcher Award

Published on by Engineering Scientist

Dr. G.N.Lalith Pankaj Raj Nadimuthu | RenewableEnergy
|Best Researcher Award

 

Faculty at The Gandhigram Rural Institute – Deemed to be University ,India.

Dr. G.N. Lalith Pankaj Raj, a dedicated scholar in Energy Engineering, is a DST INSPIRE Fellow with exceptional contributions to renewable energy research. With over 260 citations, an h-index of 10, and 11 indexed publications, his impactful work in solar photovoltaics, electric mobility, and smart grid technology demonstrates academic excellence and real-world relevance. His interdisciplinary approach, field innovations, and gold-medal academic record make him a strong contender for the Best Researcher Award. His research aligns with national sustainability goals, especially in rural energy solutions. He consistently merges theory with application, helping to shape energy policy and empower rural communities through technology. His dedication to innovation and sustainability exemplifies the highest standards of academic research.



🌍 Professional Profile:


Orcid


Google scholar


🏆 Suitability for the Best Researcher Award


 


 














































Dr. G.N. Lalith Pankaj Raj, B.E., M.Tech., Ph.D., is a distinguished DST INSPIRE Fellow with an exceptional academic and research profile in energy engineering. His work focuses on impactful, community-driven innovations such as solar photovoltaic-based cold storage and nano-grids for rural livelihood improvement. With 262 citations, an h-index of 10, and 11 i10-indexed publications, his research demonstrates both quality and real-world applicability. A Gold Medalist and First Rank holder in M.Tech, he blends technical excellence with societal relevance. His dedication to renewable energy, electric mobility, and climate change mitigation through green technologies aligns with national sustainability missions. His contributions make him a strong candidate for the Best Researcher Award, reflecting innovation, impact, and academic leadership.




















































🎓 Education 


Dr. Lalith Pankaj Raj earned his Ph.D. in Energy Engineering from The Gandhigram Rural Institute (Ministry of Education, GoI), where he was awarded the prestigious DST INSPIRE Fellowship. He completed his M.Tech in Renewable Energy with a stellar CGPA of 9.19, securing the First Rank and Gold Medal. He also holds a Certificate in Energy Auditing with distinction (CGPA 10) from the same institution. His B.E. in Electrical and Electronics Engineering was obtained from PSNA College of Engineering and Technology, affiliated with Anna University, with a CGPA of 7.95. His strong academic foundation is complemented by excellence in pre-university studies, including 89.2% in SSLC. His project work spans energy auditing, photovoltaic thermal systems, and smart vehicle technologies.


🏢 Work Experience 


Dr. Lalith Pankaj Raj has rich academic and research experience in the field of renewable energy, combining field implementation with high-impact research. He currently serves as a DST INSPIRE Fellow at The Gandhigram Rural Institute, where he is executing a pioneering project on a Combined Solar Photovoltaic-Based Micro Cold Storage–E-Mobility–Nano Grid system to benefit rural farmers. He previously conducted advanced studies on hybrid photovoltaic thermal systems and energy benchmarking for grid-tied solar rooftops in collaboration with REC-IPMT, Ministry of Power. His undergraduate innovations include vehicle emission control systems. His active involvement in field audits, training, and technical assessments reflects hands-on expertise. His career reflects a trajectory of applying research to real-world sustainability and rural development goals.


🏅 Awards and Honors 


Dr. Lalith Pankaj Raj is a recipient of the DST INSPIRE Fellowship from the Department of Science and Technology, Government of India—one of the nation’s most competitive awards for research excellence. He earned a Gold Medal and First Rank in his M.Tech program in Renewable Energy. His academic excellence has been consistently recognized with top scores and distinctions throughout his career, including a perfect CGPA in his Certificate in Energy Auditing. He has been honored for presenting high-impact research and contributing to national renewable energy forums. His Google Scholar metrics (262 citations, h-index 10, i10-index 11) demonstrate academic impact and scholarly recognition. His strong track record of innovation and excellence has earned him national and institutional acclaim.


🔬 Research Focus 
































































Dr. Lalith Pankaj Raj’s research centers on sustainable energy technologies with applications in rural development. His key areas include solar photovoltaics, thermoelectric refrigeration, electric mobility, vehicle-to-grid integration, smart grids, and energy conservation. His Ph.D. work focuses on a novel solar photovoltaic-based cold storage and nanogrid system aimed at enhancing the livelihoods of rural farmers. He is passionate about building integrated renewable systems, Net Zero energy buildings, and climate change mitigation through energy efficiency. His interdisciplinary work bridges technical innovation and social impact, promoting low-carbon solutions and decentralized energy systems. With a sharp focus on practical implementation and policy relevance, his research contributes to India’s renewable energy transition and aligns with global sustainability goals.




























































































📊 Publication Top Notes:


1. Energy conservation approach for continuous power quality improvement: A case study
Authors: LPR Nadimuthu, K Victor, CH Basha, T Mariprasath, C Dhanamjayulu, et al.
Journal: IEEE Access, Vol. 9, pp. 146959–146969
Citations: 48
Year: 2021


2. Environmental friendly micro cold storage for last-mile Covid-19 vaccine logistics
Authors: LPR Nadimuthu, K Victor
Journal: Environmental Science and Pollution Research, 29(16), 23767–23778
Citations: 39
Year: 2022


3. Performance analysis and optimization of solar-powered E-rickshaw for environmental sustainability in rural transportation
Authors: LPR, GN Kirubakaran V
Journal: Environmental Science and Pollution Research, Vol. 28, pp. 34278–34289
Citations: 32
Year: 2021


4. Energy Efficiency Enhancement and Climate Change Mitigations of SMEs through Grid-Interactive Solar Photovoltaic System
Authors: LPR, GN Kirubakaran V
Journal: International Journal of Photoenergy
Citations: 32
Year: 2021


5. Hybrid photovoltaic-thermal systems: innovative CHP approach
Authors: PRGN Lalith, G Prabakaran, A Murugaiyan, V Kirubakaran
Conference: 4th International Conference on Electrical Energy Systems (ICEES), pp. 726–730
Citations: 19
Year: 2018


6. Simulation and experimental study on performance analysis of solar photovoltaic integrated thermoelectric cooler using MATLAB Simulink
Authors: LPR Nadimuthu, DA Selvaraj, K Victor
Journal: Thermal Science, 26(2 Part A), pp. 999–1007
Citations: 16
Year: 2022


7. Fast thermal degradation of biomass using scrapped solar cell with special focus on photovoltaic (PV) waste disposal
Authors: GN Lalith Pankaj Raj Nadimuthu, VM Karthik, M Mohanraj, V Kirubakaran
Book Chapter: Waste Valorisation and Recycling: 7th IconSWM—ISWMAW 2017, Volume 2, pp. 349–361
Citations: 16
Year: 2019


8. Bench marking of grid tied solar roof top photovoltaic system: a case comparison
Authors: GNP, S. S. Chopade, L. P. Raj
Journal: International Journal of Engineering & Technology, 7(2.33), pp. 553–556
Citations: 15
Year: 2018


9. Optimization of energy-intensive process in ayurvedic medicine manufacturing unit—a case study
Authors: LPR Nadimuthu, K Victor
Journal: Process Integration and Optimization for Sustainability, 5(4), pp. 975–992
Citations: 13
Year: 2021


10. Monitoring and simulation of parabolic trough collector powered vapor absorption refrigeration system for rural cold storage
Authors: DA Selvaraj, LPR Nadimuthu, K Victor
Journal: Thermal Science, 26(2 Part A), pp. 975–982
Citations: 12
Year: 2022


11. Feasibility of renewable energy microgrids with vehicle-to-grid technology for smart villages: A case study from India
Authors: LPR Nadimuthu, K Victor, M Bajaj, MB Tuka
Journal: Results in Engineering, Vol. 24, Article 103474
Citations: 11
Year: 2024


12. An experimental and spectroscopic investigation on pongamia pinata as liquid dielectrics for rural micro grid under various load conditions
Authors: LPR Nadimuthu, NS Moorthy, K Victor, M Thenkaraimuthu, B Khan, A Ali
Journal: Scientific Reports, 14(1), Article 19653
Citations: 3
Year: 2024


13. Waste Valorisation and Recycling
Authors: JP Sarkar, B Das (Book includes contribution by GN Lalith Pankaj Raj Nadimuthu)
Publisher: Springer
Citations: 3
Year: 2019

	


	

	






	
	

		


Shiva Khani | plasmonic | Best Researcher Award
			

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Assist. Prof. Dr.Shiva Khani| plasmonic

|Best Researcher Award




 


Assist. Prof.at Semnan University, Iran.


 


Dr. Shiva Khani is an Assistant Professor at Semnan University, Iran, specializing in electrical engineering with a strong research focus on plasmonics, nonlinear optics, and sensor design. She earned her Ph.D. from Semnan University in 2020, followed by a postdoctoral fellowship at Razi University. Dr. Khani has published in reputed international journals such as Results in Optics, Heliyon, and Optical and Quantum Electronics. Her recent works highlight advancements in refractive index sensors, Fano resonance, and plasmonic filters. She brings expertise in simulation software such as Lumerical, CST, and ADS. With growing impact in nanophotonics and biosensing applications, she is a promising researcher in the field of photonic and microwave circuit design.




🌍 Professional Profile:


Scopus


Google scholar


🏆 Suitability for the Best Researcher Award


 






































Dr. Shiva Khani is a strong contender for the Best Researcher Award due to her innovative contributions to the fields of plasmonics, optical sensors, and nonlinear optics. Her research addresses critical challenges in high-resolution sensing and miniaturized photonic devices, making her work highly relevant to emerging technologies in health and environmental monitoring. With multiple first-author publications in top-tier journals in 2023–2025 and active collaborations with international researchers, she has demonstrated both leadership and impact in her field. Her postdoctoral and academic experience further reflect a trajectory of scholarly growth. Dr. Khani’s fusion of theory, simulation, and practical device design exemplifies research excellence, innovation, and interdisciplinary relevance—key qualities for this prestigious award.






































🎓 Education 


Dr. Shiva Khani holds a B.Sc. in Electrical Engineering from Razi University, Kermanshah (2007–2011), followed by an M.Sc. in Electrical Engineering from the Islamic Azad University, Science and Research Branch, Kermanshah (2012–2014). She earned her Ph.D. in Electrical Engineering from Semnan University in 2020, where she focused on advanced topics in plasmonic and photonic device design. Following her Ph.D., she pursued postdoctoral research at Razi University (2021–2022), further enhancing her expertise in sensor development and microwave photonics. Her academic path has been marked by a consistent focus on innovative device design, supported by strong theoretical and simulation capabilities.


🏢 Work Experience 


Dr. Khani currently serves as an Assistant Professor in the Department of Electrical Engineering at Semnan University, a position she began in 2024. Prior to this, she completed a postdoctoral fellowship at Razi University (2021–2022), where she conducted research on nonlinear optical devices and biosensors. Her experience includes teaching undergraduate and postgraduate courses, mentoring students, and leading independent research projects in plasmonics and sensor technology. She is proficient in high-end simulation software tools such as Lumerical, CST, and ADS, enabling her to design and optimize complex nanophotonic devices. Dr. Khani’s academic and research experiences equip her to contribute significantly to both education and innovation in electrical and photonic engineering.


🏅 Awards and Honors 


While Dr. Shiva Khani’s record does not list specific named awards to date, her growing citation count, publication in leading international journals, and appointment as Assistant Professor at Semnan University indicate academic recognition and rising impact. Her selection for a postdoctoral fellowship at Razi University reflects peer recognition of her research competence. Moreover, her lead authorship in advanced sensor design papers and collaborations with international scholars highlight her emerging reputation. Her work contributes to key technologies such as high-resolution biosensors and compact plasmonic filters, aligning with global scientific priorities. With ongoing publications in SCI-indexed journals, Dr. Khani is well-positioned to receive competitive research awards in the near future.


🔬 Research Focus 
































































Dr. Khani’s research centers on plasmonics, nonlinear optics, and sensor and biosensor technologies. Her work explores how nanoscale metal-dielectric structures can enhance optical sensing performance through phenomena such as Fano resonance and surface plasmon resonance (SPR). She has designed high-resolution refractive index sensors and wideband plasmonic filters for integrated photonic circuits. Additionally, she investigates the application of microwave circuits in photonic system integration. Her publications reflect a balance between theoretical modeling, numerical simulation, and practical device functionality. Dr. Khani leverages advanced software (Lumerical, CST, ADS) to simulate and optimize next-generation optical devices. Her research contributes to biomedical diagnostics, environmental sensing, and nano-optoelectronic systems.




























































































📊 Publication Top Notes:


    

  1. 

    Khani, S., Danaie, M., & Rezaei, P. (2018).
    Realization of single-mode plasmonic bandpass filters using improved nanodisk resonators.
    Optics Communications, 420, 147–156.
    Citations: 110
    

    2. 

  2. 

    Khani, S., & Hayati, M. (2022).
    Optical biosensors using plasmonic and photonic crystal band-gap structures for the detection of basal cell cancer.
    Scientific Reports, 12(1), 5246.
    Citations: 97
    

    3. 

  3. 

    Khani, S., & Hayati, M. (2021).
    An ultra-high sensitive plasmonic refractive index sensor using an elliptical resonator and MIM waveguide.
    Superlattices and Microstructures, 156, 106970.
    Citations: 91
    

    4. 

  4. 

    Khani, S., Danaie, M., & Rezaei, P. (2019).
    Design of a single-mode plasmonic bandpass filter using a hexagonal resonator coupled to graded-stub waveguides.
    Plasmonics, 14, 53–62.
    Citations: 85
    

    5. 

  5. 

    Armaghani, S., Khani, S., & Danaie, M. (2019).
    Design of all-optical graphene switches based on a Mach-Zehnder interferometer employing optical Kerr effect.
    Superlattices and Microstructures, 135, 106244.
    Citations: 70
    

    6. 

  6. 

    Khani, S., Danaie, M., & Rezaei, P. (2018).
    Double and triple-wavelength plasmonic demultiplexers based on improved circular nanodisk resonators.
    Optical Engineering, 57(10), 107102.
    Citations: 70
    

    7. 

  7. 

    Khani, S., & Hayati, M. (2022).
    Optical sensing in single-mode filters based on surface plasmon H-shaped cavities.
    Optics Communications, 505, 127534.
    Citations: 69
    

    8. 

  8. 

    Khani, S., Danaie, M., & Rezaei, P. (2019).
    Tunable Single-Mode Bandpass Filter Based on Metal-Insulator-Metal Plasmonic Coupled U-Shaped Cavities.
    IET Optoelectronics.
    Citations: 65
    

    9. 

  9. 

    Khani, S., Vald Makki, S., Mousavi, S.M.H., Danaie, M., & Rezaei, P. (2017).
    Adjustable compact dual-band microstrip bandpass filter using T-shaped resonators.
    Microwave and Optical Technology Letters, 59(12), 2970–2975.
    Citations: 62
    

    10. 

  10. 

    Khani, S., Farmani, A., & Mir, A. (2021).
    Reconfigurable and scalable 2, 4- and 6-channel plasmonics demultiplexer utilizing symmetrical rectangular resonators containing silver nano-rod defects with FDTD method.
    Scientific Reports, 11(1), 13628.
    Citations: 59
    

    11. 


	


	

	






	
	

		


Frantisek Wald | Fire engineering | Best Researcher Award
			

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Prof. Frantisek Wald| Fire engineering

|Best Researcher Award




 


Prof. Frantisek Wald Czech Technical University, Czech Republic.


Professor František Wald is a leading expert in steel and timber structures at Czech Technical University in Prague. With over three decades of dedicated research in structural steel joints and fire engineering, he has pioneered academic programs in fire safety and led several EU-wide collaborations such as COST TU and Erasmus Mundus SUSCOS. His leadership roles in European technical committees and presidency of the ECCS (2023–2024) reflect his significant influence in civil engineering. His prolific research, international impact, and innovation in structural safety under fire and seismic conditions make him a highly suitable candidate for the Best Researcher Award. His work bridges advanced theory and practical design, contributing extensively to safety standards and sustainable construction practices in Europe.




🌍 Professional Profile:


Orcid


Scopus


🏆 Suitability for the Best Researcher Award






































Professor František Wald is a pioneering researcher in structural steel joints and fire engineering, with over three decades of impactful contributions to structural safety. His work has advanced European standards through leadership in technical committees (TC10 Joints, TC3 Fire, TC14 FEM) and his role in drafting prEN1993-1-8. As President of ECCS (2023–2024), he strengthened international cooperation in steel construction. He has initiated and led transformative research projects such as FISHWALL and MADESCO, combining theory with real-world application. His academic influence is evident through the creation of comprehensive fire safety programs. With strong citation metrics and global collaborations, Prof. Wald exemplifies excellence in research, education, and innovation, making him a highly deserving candidate for the Best Researcher Award.






































🎓 Education 


František Wald pursued his engineering education at the Czech Technical University in Prague, where he laid the foundation for his career in structural engineering. He earned his doctoral degree with a focus on steel structures and fire safety, contributing to the advancement of structural resilience under extreme conditions. Over the years, he expanded his academic influence by establishing bachelor’s, master’s, and doctoral programs dedicated to building fire safety, reflecting a commitment to both education and research. His expertise was further refined through collaboration with European academic institutions, shaping international educational programs like the Erasmus Mundus Master’s in Steel Structures (SUSCOS), which he co-developed. His academic background exemplifies a lifelong dedication to technical excellence and educational innovation in structural engineering.


🏢 Work Experience 


Professor Wald has over 30 years of experience in structural engineering, primarily at Czech Technical University in Prague. Since 1992, he has actively contributed to European technical committees including TC10 (Joints), TC3 (Fire), and TC14 (FEM). He also worked on the drafting of prEN1993-1-8, influencing steel joint design standards across Europe. His academic leadership includes establishing multi-level fire safety programs and managing international networks like the COST TU on Fire Engineering. As president of ECCS (2023–2024), he fostered collaboration across Europe’s steel construction community. His consultancy roles and applied research in projects like Steel Hall 4.0 reflect a strong connection to industry. His experience blends academic excellence with real-world application and international research coordination.


🏅 Awards and Honors 


Professor Wald’s distinguished career has been recognized through numerous honors. Most notably, he served as President of the European Convention for Constructional Steelwork (ECCS) from 2023 to 2024, a prestigious role acknowledging his leadership in steel construction research. He has received recognition for his coordination of major European programs including Erasmus Mundus SUSCOS and COST TU networks. His citation impact is substantial, with over 830 citations on Scopus and an h-index of 17, reflecting sustained scholarly influence. His projects have earned competitive funding from EU programs (e.g., RFCS, GACR), demonstrating trust in his innovative approaches to steel structure safety. His awards underscore a career of sustained excellence, international collaboration, and impactful contributions to engineering science.


🔬 Research Focus 
































































Professor Wald’s research centers on the behavior of steel structures under fire and dynamic loads, with a focus on structural joints, resilience, and safety design. His work integrates experimental analysis, numerical modeling, and probabilistic methods to improve fire resistance and joint performance. He has led major EU projects such as FISHWALL, MADESCO, and DYNAFIRE, addressing seismic, fire, and structural challenges in industrial steel buildings. As a long-standing member of technical committees, he helps shape European design standards. He is also deeply involved in developing advanced modeling techniques (e.g., LMSTRAIN) and structural optimization through AI (e.g., MADESCO). His research is grounded in real-world impact, bridging theoretical development with design innovation for safer and more sustainable infrastructure.




























































































📊 Publication Top Notes:


    

  • 

    Title: Determination of design plastic strain limit for notched structural steel tensile specimens
    Authors: Kirill Golubiatnikov, Abhishek Ghimire, František Wald, Vojtěch Stančík
    Year: 2025
    Journal: Alexandria Engineering Journal
    DOI: 10.1016/j.aej.2025.02.075
    

    • 

  • 

    Title: Calibration of the Induction Heating System for Dynamic Compression Test
    Authors: T. Jankowiak, W. Szymkuć, M. Malendowski, K. Cabová, J. Šejna, V. Mózer, F. Wald
    Year: 2025
    Journal: Experimental Techniques
    DOI: 10.1007/s40799-025-00807-3
    

    • 

  • 

    Title: Fire Protection of Steel Beam by OSB Claddings—A Fire Experiment and Numerical Models
    Authors: Jakub Šejna, Vojtěch Šálek, Stanislav Šulc, Kamila Cábová, Vít Šmilauer, Slávek Zbirovský, Milan Jahoda, František Wald
    Year: 2025
    Journal: Fire and Materials
    DOI: 10.1002/fam.3260
    

    • 

  • 

    Title: Numerical Design Calculation of Fin Plate Connections in Fire
    Authors: Batuhan Der, Frantisek Wald, Martin Vild
    Year: 2024
    Book Chapter: in Lecture Notes in Civil Engineering
    DOI: 10.1007/978-981-97-1972-3_60
    

    • 

  • 

    Title: The influence of sandwich panel cladding on horizontal structure stiffness
    Authors: Břetislav Židlický, Jiří Mareš, František Wald
    Year: 2024
    Journal: Thin-Walled Structures
    DOI: 10.1016/j.tws.2024.111771
    

    • 

  • 

    Title: Application of hybrid cement in passive fire protection of steel structures
    Authors: Jakub Šejna, Stanislav Šulc, Vít Šmilauer, Pavel Reiterman, František Wald
    Year: 2024
    Journal: Journal of Structural Fire Engineering
    DOI: 10.1108/JSFE-01-2023-0007
    

    • 

  • 

    Title: Analytical resistance of the laterally offset rectangular hollow sections connections under concentrated force
    Authors: Svitlana Kalmykova, František Wald
    Year: 2023
    Journal: Structures
    DOI: 10.1016/j.istruc.2023.105484
    

    • 

  • 

    Title: Optimisation of fatigue solution for welded T-stub joints by grading of FAT classes and correction of mean stress effect
    Authors: Kirill Golubiatnikov, Frantisek Wald, Martin Vild, Josef Holomek
    Year: 2023
    Journal: Structures
    DOI: 10.1016/j.istruc.2023.105582
    

    • 

  • 

    Title: Weld size and resistance in rectangular hollow section T-joints
    Authors: Petr Jehlicka, Frantisek Wald
    Year: 2023
    Journal: Heliyon
    DOI: 10.1016/j.heliyon.2023.e22689
    

    • 

  • 

    Title: The partial fire protection of steel members: a comparative study
    Authors: Jakub Šejna, Patrik Dobrovolný, František Wald
    Year: 2023
    Journal: Journal of Structural Fire Engineering
    DOI: 10.1108/JSFE-01-2023-0001
    

    • 

  • 

    Title: Emissivity of hot-dip galvanized surfaces in future development of EN 1993-1-2
    Authors: Batuhan Der, Sylvie Raszková, František Wald, Gisèle Bihina, Christian Gaigl, Vasile Rus, Mikko Malaska
    Year: 2022
    Journal: Journal of Structural Fire Engineering
    DOI: 10.1108/JSFE-11-2021-0070
    

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Changxin Yu | Digital technology | Best Researcher Award
			

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Dr. Changxin Yu | Digital technology

|Best Researcher Award




 


Dr at Beijing Institute of Technology ,China.


Changxin Yu is a Ph.D. candidate in Applied Economics at Beijing Institute of Technology. Her research bridges agricultural economics and digital technology, focusing on their combined impact on productivity, sustainability, and innovation. She has investigated public perceptions of GMOs, the role of R&D in Chinese pesticide firms, and the productivity effects of modern biotechnology. Yu applies empirical models, including machine learning, to analyze how digital technologies—such as industrial robots and digital trade—contribute to green development and economic transformation. Her work is published in leading journals, including Technological Forecasting and Social Change. With interdisciplinary expertise, she continues to explore how digital tools can enhance agricultural and manufacturing sector performance, contributing to China’s sustainable economic growth.




🌍 Professional Profile:


Scopus


🏆 Suitability for the Best Researcher Award




 






































Changxin Yu exemplifies the qualities sought in a Best Researcher Award recipient. Her work seamlessly integrates applied economics, digital innovation, and sustainability—a rare and valuable interdisciplinary nexus. She has produced high-impact research on topics such as industrial robots’ role in green growth and the effect of digital trade on agricultural productivity. Her ability to apply cutting-edge empirical and machine learning techniques enhances the credibility and applicability of her findings. With several prestigious publications and international collaborations, her research has advanced understanding of sustainable development and digital adoption in agriculture and manufacturing. Yu’s academic rigor, innovative approach, and commitment to real-world challenges position her as a strong candidate for the award.






































🎓 Education 


Changxin Yu has a robust academic background that spans economics, management, and agriculture. She is currently pursuing a Ph.D. in Applied Economics at Beijing Institute of Technology (2019–present), focusing on digital and green economic development. She also holds a Master’s degree in Management Science and Engineering (2017–2019) from the same institution. Her undergraduate education was completed at Beijing Forestry University, where she earned a Bachelor’s degree in Agricultural and Forestry Economic Management (2013–2017). Her multidisciplinary training enables her to address complex challenges across agricultural economics, digital transformation, and environmental sustainability. Through this academic trajectory, Yu has cultivated a deep understanding of the socioeconomic implications of digital tools in agriculture and industry, strengthening her research versatility.


🏢 Work Experience 


Changxin Yu has a diverse range of research experience rooted in interdisciplinary projects. She has worked on USDA-funded studies examining the impact of public and private R&D investment on total factor productivity in China. Her academic and project-based research focuses on digital adoption in agriculture, industrial innovation, and environmental sustainability. She has analyzed the economic effects of GMOs, digital trade, and robotics in manufacturing. Through these experiences, she has developed strong skills in data analysis, policy assessment, and empirical modeling. Yu’s contributions extend beyond academia to inform policy and innovation strategies in agriculture and industry. Her professional journey is marked by her involvement in internationally collaborative projects and publications in well-regarded scientific journals.


🏅 Awards and Honors 


While specific awards are not listed, Changxin Yu has earned academic recognition through her involvement in high-impact research projects and publications in reputable journals such as Technological Forecasting and Social Change. Her selection for a USDA-funded research initiative reflects her capabilities and potential for influencing policy and practice. Additionally, her ongoing doctoral research incorporates advanced econometric and machine learning techniques, distinguishing her in the field of applied economics. Yu’s research contributions have gained attention in academic and policy circles for their relevance to green development, digital transformation, and agricultural innovation. Given the scope and impact of her work, she is likely to be a strong contender for academic and research honors in the near future.


🔬 Research Focus 
































































Changxin Yu’s research sits at the intersection of applied economics, digital transformation, and sustainable development. She focuses on how digital technologies, such as industrial robots and digital trade platforms, impact agricultural productivity and green growth. Her current doctoral research investigates the effects of modern biotechnology on agricultural total factor productivity (TFP), using robust empirical and machine learning methods. Yu also examines the economic implications of public and private R&D investments, particularly in agriculture and manufacturing. Her work has explored public attitudes toward GMOs and the economic impact of carbon abatement via digitalization. By analyzing how emerging technologies reshape economic systems, her research provides valuable insights for policy makers, academics, and industries working toward sustainable innovation.




























































































📊 Publication Top Notes:


Citation:
Deng, H., Yu, C., Pray, C. E., & Jin, Y. (Forthcoming). How is China Shaping Global Food Supply Chains? Insights from the Seed Industry. European Review of Agricultural Economics.


Authors:


    

  • 

    Haiyan Deng
    

    • 

  • 

    Changxin Yu
    

    • 

  • 

    Carl E. Pray
    

    • 

  • 

    Yanhong Jin* (Corresponding author)
    

    • 



Year:
Forthcoming (Accepted, not yet published)


Citation:
Deng, H., Huang, Z., Wu, J., Güneri, F., Shen, Z., & Yu, C.* (2025). Harnessing the power of industrial robots for green development: Evidence from China’s manufacturing industry. Technological Forecasting and Social Change, 215, 124099. https://doi.org/10.1016/j.techfore.2025.124099


Authors:


    

  • 

    Haiyan Deng
    

    • 

  • 

    Zhonghua Huang
    

    • 

  • 

    Jian Wu
    

    • 

  • 

    Fatma Güneri
    

    • 

  • 

    Zhiyang Shen
    

    • 

  • 

    Changxin Yu* (Corresponding author)
    

    • 



Year:
2025


Citation:
Hu, R., Yu, C., Jin, Y., Pray, C., & Deng, H. (2022). Impact of government policies on research and development (R&D) investment, innovation, and productivity: Evidence from pesticide firms in China. Agriculture, 12(5), 709. https://doi.org/10.3390/agriculture12050709


Authors:


    

  • 

    Ruifa Hu
    

    • 

  • 

    Changxin Yu
    

    • 

  • 

    Yanhong Jin
    

    • 

  • 

    Carl Pray
    

    • 

  • 

    Haiyan Deng
    

    • 



Year:
2022

	


	

	






	
	

		


Zhenyun Tang |Structural engineering |Best Research Article Award
			

				Published on  by Engineering Scientist			

		
	


	

		
Prof. Dr. Zhenyun Tang | Structuralengineering

|Best Research Article Award




 


Professor at BEIJING UNIVERSITY OF TECHNOLOGY ,China.


 


Professor Tang Zhenyun is a distinguished expert in earthquake engineering and disaster mitigation at Beijing University of Technology. As a doctoral supervisor, he contributes significantly to experimental seismic technology and structural vibration control. He serves on multiple national youth editorial and technical committees focused on disaster resilience. His innovative research spans real-time hybrid simulation, base isolation systems, and tuned liquid dampers. Tang has authored high-impact papers in top journals like International Journal of Structural Stability and Dynamics and Soil Dynamics and Earthquake Engineering. He has earned prestigious awards, including the Silver Medal at the Geneva International Exhibition of Inventions and the First Prize from the China Highway and Transportation Society. His scholarly excellence makes him a prime candidate for the Best Research Article Award.




🌍 Professional Profile:


Scopus


🏆 Suitability for the Best Research Article Award




 














































Professor Tang Zhenyun is an internationally recognized scholar in earthquake engineering, whose research integrates experimental innovation and practical seismic mitigation strategies. His recent articles in high-impact journals such as Soil Dynamics and Earthquake Engineering and International Journal of Structural Stability and Dynamics reflect cutting-edge advancements in vibration control, base isolation, and real-time hybrid simulation. His award-winning work—recognized by the China Inspection and Testing Society, Geneva International Exhibition of Inventions, and others—demonstrates both theoretical depth and practical impact. As a doctoral supervisor and active member of key professional societies, Professor Tang’s research not only advances academic knowledge but also contributes to safer infrastructure. His scientific rigor and innovation make him highly suitable for the Best Research Article Award.














































🎓 Education 


Professor Tang Zhenyun holds a Ph.D. in Engineering, specializing in structural dynamics and earthquake resilience. His doctoral research laid a solid foundation in advanced experimental methods, real-time hybrid simulation, and vibration control technologies for civil infrastructure. He has received comprehensive academic training from leading Chinese institutions, culminating in his doctoral degree, which has empowered him to contribute meaningfully to seismic safety and geotechnical innovation. Throughout his education, Professor Tang demonstrated exceptional academic merit and research capability, which propelled him into a prominent academic and professional trajectory. His educational background enables him to mentor graduate and doctoral students while advancing theoretical and applied research in structural and earthquake engineering.


🏢 Work Experience 


With extensive academic and research experience, Professor Tang Zhenyun serves as a full professor and doctoral supervisor at Beijing University of Technology. He has led and collaborated on national research projects involving seismic mitigation, vibration control, and soil-structure interaction. Tang has developed innovative real-time hybrid simulation techniques and applied them to civil engineering challenges, producing highly cited publications. His engineering expertise is recognized nationally and internationally, and he has played key roles on editorial boards and professional committees in earthquake prevention and disaster resilience. He also bridges academia and industry through applied research, contributing to testing standards and resilient infrastructure development. His multifaceted experience underscores his suitability for awards recognizing impactful and applied research in structural safety.


🏅 Awards and Honors 


Professor Tang Zhenyun has received numerous national and international honors recognizing his contributions to seismic engineering. These include the First Prize from the China Inspection and Testing Society (1/15) and the Second Prize from the Fujian Science and Technology Awards (2/7). He won the Silver Medal at the Geneva International Exhibition of Inventions (1/5) for his innovative engineering solutions. As the sole recipient (1/1) of the Personal Prize from the China Industry-University-Research Institute Collaboration Association, Tang demonstrated exceptional leadership in applied research. He also contributed to the First Prize from the China Highway and Transportation Society (11/15). These accolades collectively reflect his groundbreaking research, interdisciplinary collaborations, and impactful innovations in earthquake resilience and structural safety.


🔬 Research Focus 
































































Professor Tang Zhenyun’s research is centered on earthquake engineering, with specific expertise in experimental technology, base isolation, seismic mitigation, and vibration control. He specializes in real-time hybrid simulation, where he develops and applies novel methods to model complex soil-structure systems under seismic loads. His studies have advanced the use of GPU computing for structural simulations and proposed new frequency-domain analysis techniques for systems employing tuned liquid dampers. Tang’s work on the stability of hybrid testing systems and parameter identification in dynamic models has influenced the development of resilient infrastructure. His research addresses both theoretical modeling and practical application, making significant contributions to safety-critical structures in earthquake-prone regions and aligning with national resilience strategies.




























































































📊 Publication Top Notes:


    

  1. 

    Yang, B., Li, Z., Lv, J., Tang, Z., & Wang, L. (2025). Experimental study on load-bearing capacity of T-shaped semi-rigid connected double skin composite shear walls. KSCE Journal of Civil Engineering.
    Citations: 1
    

    2. 

  2. 

    Shang, Q., Tang, Z., & Wang, T. (2024). Component-level seismic fragility database of suspended piping systems in buildings. Earthquake Engineering and Resilience.
    Citations: 0
    

    3. 

  3. 

    Li, X., Tang, Z., & Du, X.L. (2024). Identification of stable parameters for discrete-time rational approximation of MDOF frequency response functions in semi-infinite media. Gongcheng Lixue/Engineering Mechanics.
    Citations: 1
    

    4. 

  4. 

    Liu, H., Tang, Z., & Enokida, R. (2024). Stability prediction method of time-varying real-time hybrid testing system on vehicle-bridge coupled system. Mechanical Systems and Signal Processing.
    Citations: 1
    

    5. 

  5. 

    Tang, Z., Li, J., Wang, M., Yu, C., & Li, Z. (2024). Investigation on bearing resistance of thin-walled circular steel tube subjected to eccentric loading. Advances in Structural Engineering.
    Citations: 0
    

    6. 

  6. 

    Yi, S., Su, T., & Tang, Z. (2024). Robust adaptive Kalman filter for structural performance assessment. International Journal of Robust and Nonlinear Control.
    Citations: 4
    

    7. 

  7. 

    Wu, Y., Dong, X., Liao, W., Zheng, G., & Shang, H. (2024). Field dynamic characteristics testing of foundation isolation structures under horizontal initial displacement. Zhendong Gongcheng Xuebao/Journal of Vibration Engineering.
    Citations: 1
    

    8. 

  8. 

    Liu, H., & Tang, Z. (2024). Stability prediction method for real-time hybrid test system based on the measured dynamics of physical test system. Soil Dynamics and Earthquake Engineering.
    Citations: 0
    

    9. 

  9. 

    Tang, Z., & Li, X. (2023). Stable parameters identification for rational approximation of single degree of freedom frequency response function of semi-infinite medium. International Journal for Numerical Methods in Engineering.
    Citations: 0
    

    10. 


	


	

	






	
	

		


Fareeha Fatima | Materials Science | Young Scientist Award
			

				Published on  by Engineering Scientist			

		
	


	

		
Ms. Fareeha Fatima| Materials Science

|Young Scientist Award


 


Visiting Lecturer at The Islamia University of Bahawalpur,,Pakistan.


Fareeha Fatima is a passionate young physicist from Bahawalnagar, Pakistan, known for her academic excellence and early-career contributions to scientific research. With a strong foundation in theoretical and applied physics, she has pursued advanced studies at The Islamia University of Bahawalpur, where she recently completed her M.Phil with distinction. Her research in density functional theory and nanocomposites showcases her analytical depth and commitment to innovation. Fareeha also possesses practical teaching experience and a strong grasp of digital tools essential for modern scientific work. With exceptional communication and collaboration skills, she stands out as a motivated and promising young scientist. Her work ethic, enthusiasm, and dedication to knowledge advancement make her an ideal candidate for the Young Scientist Award.




🌍 Professional Profile:


Scopus


🏆 Suitability for the Young Scientist Award




 






































Fareeha Fatima exemplifies the spirit of the Young Scientist Award through her academic brilliance, research potential, and proactive engagement in the scientific community. Her M.Phil research applying advanced DFT techniques to novel LiZnZ compounds, and her M.Sc work on nanocomposite applications in theragnostics, reflect an impressive breadth and depth of understanding. At a young age, she has combined strong theoretical knowledge with practical teaching and laboratory skills. Her active participation in academic environments and strong interpersonal abilities further highlight her leadership qualities. Fareeha demonstrates innovation, discipline, and a forward-thinking approach that are critical for impactful scientific progress. She represents the future of physics research in Pakistan and is a deserving nominee for the Young Scientist Award.






































🎓 Education 


Fareeha Fatima has consistently excelled in her academic journey, marked by high achievements in physics. She completed her M.Phil in Physics (2022–2024) at The Islamia University of Bahawalpur with a CGPA of 3.88, conducting advanced theoretical research on LiZnZ (Z = Sb, Bi) compounds using GGA, WC, and mBJ methods. Her M.Sc in Physics (2019–2021), also from the same university with a CGPA of 3.68, involved exploring bismuth-based nanocomposites for theragnostic applications. Her B.Sc (2017–2019) established a strong scientific base. She previously completed her F.Sc (Pre-Engineering) and Matriculation with distinction. Her education reflects a consistent commitment to excellence and a growing focus on computational and materials science in the context of physics.


🏢 Work Experience 


Fareeha Fatima has gained valuable experience in both academic and educational settings. She served as a Teaching Assistant at The Islamia University of Bahawalpur, Bahawalnagar Campus (Jan–May 2023), where she assisted in delivering lectures, managing student queries, and supporting practical sessions. Earlier, she worked as a science teacher at First Moon Kindergarten School and Pioneer Science Academy (Nov 2021–May 2022), demonstrating her ability to communicate scientific concepts effectively at different academic levels. These roles have enhanced her capabilities in team collaboration, time management, and active listening—key skills for any researcher. Her hands-on exposure to both theoretical instruction and practical demonstration underlines her readiness for more advanced research roles and makes her a well-rounded young academic professional.


🏅 Awards and Honors 


Fareeha Fatima’s academic achievements speak volumes about her dedication and potential. While still early in her career, she has earned distinction through outstanding CGPAs in both her M.Phil (3.88) and M.Sc (3.68) programs. Her performance has consistently placed her among the top students in her department. She has been commended by faculty for her critical thinking, dedication to research, and strong academic ethics. Her work has attracted attention for its innovative approach to theoretical materials science and nanotechnology. Though formal national awards are still forthcoming, she is widely regarded by her peers and mentors as a future leader in physics research. Her academic accomplishments and potential make her a strong candidate for prestigious recognitions like the Young Scientist Award.


🔬 Research Focus 
































































Fareeha Fatima’s research centers on theoretical condensed matter physics, particularly using Density Functional Theory (DFT) to study the structural and electronic properties of emerging compounds. Her M.Phil thesis focuses on LiZnZ (Z = Sb, Bi) semiconducting materials analyzed using GGA, WC, and mBJ schemes, offering insights relevant to next-generation electronic applications. Earlier, her M.Sc research explored bismuth-based nanocomposites for dual-use in medical diagnostics and therapy—highlighting an interdisciplinary approach that blends physics with nanomedicine. Fareeha is also proficient in digital tools like Origin Lab and MS Office for data analysis and scientific reporting. Her focus on simulation-driven prediction of material behaviors aligns with global research trends, making her contributions timely, impactful, and promising for future scientific development.




























































































📊 Publication Top Notes:


    

  1. 

    Fatima, F., & Co-authors. (2024). Exploring the physical attributes of NaCaX (X = As, Sb) semiconductors by first principles calculations. The European Physical Journal Plus, W Category Journal.
    

    2. 

  2. 

    Fatima, F., & Co-authors. (2024). Detailed DFT based exploration on spin-gapless features of IrCoNbX (X = Al, Ga, In) alloys. Journal of Magnetism and Magnetic Materials, W Category Journal.
    

    3. 

  3. 

    Fatima, F., & Co-authors. (2024). Unveiling the robustness of half-metallicity under strain effects of CoVYZ (Z = Si, Ge, Sn) alloys. Journal of Magnetism and Magnetic Materials, W Category Journal.
    

    4. 

  4. 

    Fatima, F., & Co-authors. (2024). Comparative Density Functional Theory Based Study of LiZnZ (Z = Sb, Bi) Compounds via GGA, WC and mBJ Schemes. Indian Journal of Physics, W Category Journal.
    

    5. 


	


	

	






	
	

		


Mohd Usama | Machine Learning | Best Researcher Award
			

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Assist. Prof. Dr. MohdUsama|MachineLearning

|Best Researcher Award




Postdoctoral Researcher at Umea University, Sweden Sweden.




Dr. Mohd Usama is a Postdoctoral Researcher at the Department of Diagnostics and Intervention, Umea University, Sweden. He holds a Ph.D. in Computer Science from Huazhong University of Science and Technology, China, focusing on deep learning for disease prediction and sentiment analysis. His research bridges artificial intelligence and medical imaging, particularly using GANs for domain adaptation and plaque detection in ultrasound imagery. With a solid teaching and research background across reputed institutions in India, he has significantly contributed to developing AI-based clinical decision support systems. His scholarly work, practical innovation, and interdisciplinary expertise make him highly suitable for the Best Researcher Award, exemplifying excellence in research, innovation, and educational service in the domains of biomedical engineering and artificial intelligence.




🌍 Professional Profile:


Scopus


Orcid


🏆 Suitability for the Best Researcher Award


 






































Dr. Mohd Usama exemplifies the qualities of a top-tier researcher through his impactful contributions to AI-driven medical imaging and clinical decision support systems. Currently a Postdoctoral Researcher at Umea University, Sweden, his work on generative adversarial networks for ultrasound-based atherosclerosis risk assessment addresses critical challenges in healthcare diagnostics. His strong academic foundation, interdisciplinary approach, and global research collaborations demonstrate exceptional innovation and dedication. Dr. Usama’s ability to translate deep learning research into real-world clinical applications, alongside a consistent record of teaching, publishing, and mentoring, positions him as a leader in his field. His scientific rigor, creativity, and societal impact make him a highly deserving candidate for the Best Researcher Award.






































🎓 Education 


Dr. Usama earned his Ph.D. in Computer Science from Huazhong University of Science and Technology, China (2016–2020), with a dissertation on “Recurrent Deep Learning for Text Processing with Application to Disease Prediction and Sentiment Analysis,” supervised by Prof. Min Chen. He completed his Master’s in Computer Science and Applications (71.78%, First Division) from Aligarh Muslim University (2013–2016), focusing on cloud-based electric vehicle charging management. His undergraduate degree is a B.Sc. (Hons) in Statistics (71.07%, First Division), also from Aligarh Muslim University (2009–2012), with a thesis on students’ opinions on the Ombudsman Bill in India. His academic journey reflects a blend of statistical foundations, computing applications, and interdisciplinary insights, crucial for innovative AI research in biomedical domains.


🏢 Work Experience 


Dr. Mohd Usama has served as a Postdoctoral Researcher at Umea University, Sweden (Dec 2022–Present), contributing to AI-powered clinical decision support systems and generative models for carotid ultrasound imaging. Previously, he worked as an Assistant Professor at the University of Petroleum and Energy Studies (2022), Kalasalingam Academy of Research and Education (2021–2022), and Madanapalle Institute of Technology and Science (2020–2021). He taught various courses including Deep Learning, Algorithms, Programming, and Information Security. His work spans both academia and research, with a deep engagement in curriculum development and applied machine learning. His experience in medical imaging research and teaching demonstrates a strong integration of theoretical and practical knowledge, making him a well-rounded and impactful scholar.


🏅 Awards and Honors 


Dr. Mohd Usama has been recognized for his innovative interdisciplinary research contributions at the intersection of artificial intelligence and healthcare. He received prestigious academic scholarships for his doctoral studies in China and earned consistent recognition throughout his academic career. He has been invited to deliver expert lectures and guest talks on AI, deep learning, and statistical computing at various institutions. His role in international collaborative projects on ultrasound imaging and disease prediction further demonstrates his global impact. As a frequent reviewer for reputed journals and contributor to academic forums, he maintains high standards of scholarly excellence. These achievements, coupled with his dedication to knowledge dissemination and impactful research, position him as a strong candidate for the Best Researcher Award.


🔬 Research Focus 
































































Dr. Mohd Usama’s research lies at the convergence of artificial intelligence, deep learning, and medical imaging. His work primarily involves the use of generative adversarial networks (GANs) to address domain adaptation, noise reduction, and feature interpolation in carotid ultrasound images. He develops AI-powered clinical decision support systems to enhance subclinical atherosclerosis risk prediction and ultrasound diagnostics. His doctoral research explored recurrent deep learning for text analysis in healthcare applications. He is also keenly interested in disease modeling, natural language processing, and sentiment analysis within clinical contexts. Dr. Usama’s work emphasizes real-world application of machine learning in healthcare, contributing to early diagnosis and precision medicine through robust, data-driven solutions, reinforcing his value as a research innovator.




























































































📊 Publication Top Notes:


    

  1. 

    Usama, M., Nyman, E., Näslund, U., & Grönlund, C. (2025).
    A domain adaptation model for carotid ultrasound: Image harmonization, noise reduction, and impact on cardiovascular risk markers.
    Computers in Biology and Medicine.
    https://doi.org/10.1016/j.compbiomed.2025.110030
    

    2. 

  2. 

    Usama, M., & Grönlund, C. (2023).
    Carotid Ultrasound Image Denoising Using Low-to-High Image Quality Domain Adaptation.
    The Medical Technology Days (MTD), 2023, Stockholm.
    

    3. 

  3. 

    Singh, A. P., Kumar, S., Kumar, A., & Usama, M. (2022).
    Machine Learning based Intrusion Detection System for Minority Attacks Classification.
    2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES).
    https://doi.org/10.1109/cises54857.2022.9844381
    

    4. 

  4. 

    Ahmad, B., Usama, M., Ahmad, T., Khatoon, S., & Alam, C. M. (2022).
    An ensemble model of convolution and recurrent neural network for skin disease classification.
    International Journal of Imaging Systems and Technology, 32(1), 15–24.
    https://doi.org/10.1002/ima.22661
    

    5. 

  5. 

    Ahmad, B., Usama, M., Huang, C. M., Hwang, K., Hossain, M. S., & Muhammad, G. (2020).
    Discriminative Feature Learning for Skin Disease Classification Using Deep Convolutional Neural Network.
    IEEE Access, 8, 39098–39110.
    https://doi.org/10.1109/ACCESS.2020.2975198
    

    6. 

  6. 

    Qamar, S., Jin, H., Zheng, R., Ahmad, P., & Usama, M. (2020).
    A variant form of 3D-UNet for infant brain segmentation.
    Future Generation Computer Systems, 108, 618–628.
    https://doi.org/10.1016/j.future.2019.11.021
    

    7. 

  7. 

    Usama, M., Ahmad, B., Song, E., Hossain, M. S., Alrashoud, M., & Muhammad, G. (2020).
    Attention-based sentiment analysis using convolutional and recurrent neural network.
    Future Generation Computer Systems, 106, 336–347.
    https://doi.org/10.1016/j.future.2020.07.022
    

    8. 

  8. 

    Usama, M., Ahmad, B., Xiao, W., Hossain, M. S., & Muhammad, G. (2020).
    Self-attention based recurrent convolutional neural network for disease prediction using healthcare data.
    Computer Methods and Programs in Biomedicine, 187, 105191.
    https://doi.org/10.1016/j.cmpb.2019.105191
    

    9. 

  9. 

    Ahmad, P., Jin, H., Qamar, S., Zheng, R., Jiang, W., Ahmad, B., & Usama, M. (2019).
    3D Dense Dilated Hierarchical Architecture for Brain Tumor Segmentation.
    Proceedings of the 2019 4th International Conference on Big Data and Computing (ICBDC).
    https://doi.org/10.1145/3335484.3335516
    

    10. 

  10. 

    Ahmad, B., Usama, M., Lu, J., Xiao, W., Wan, J., & Yang, J. (2019).
    Deep Convolutional Neural Network Using Triplet Loss to Distinguish the Identical Twins.
    2019 IEEE Globecom Workshops (GC Wkshps).
    https://doi.org/10.1109/GCWkshps45667.2019.9024704
    

    11. 

  11. 

    Usama, M., Xiao, W., Ahmad, B., Wan, J., Hassan, M. M., & Alelaiwi, A. (2019).
    Deep Learning Based Weighted Feature Fusion Approach for Sentiment Analysis.
    IEEE Access, 7, 140361–140373.
    https://doi.org/10.1109/ACCESS.2019.2940051
    

    12. 

  12. 

    Usama, M., Ahmad, B., Yang, J., Qamar, S., Ahmad, P., Zhang, Y., Lv, J., & Guna, J. (2019).
    Equipping recurrent neural network with CNN-style attention mechanisms for sentiment analysis of network reviews.
    Computer Communications, 149, 111–121.
    https://doi.org/10.1016/j.comcom.2019.08.002
    

    13. 

  13. 

    Hao, Y., Usama, M., Yang, J., Hossain, M. S., & Ghoneim, A. (2019).
    Recurrent convolutional neural network based multimodal disease risk prediction.
    Future Generation Computer Systems, 98, 296–304.
    https://doi.org/10.1016/j.future.2018.09.031
    

    14. 


	


	

	






	
	

		


Huakun Bi | Electrical Engineering | Best Researcher Award
			

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Dr. Huakun Bi| Electrical Engineering

|Best Researcher Award




Lecturer at School of Electrical and Automation Engineering, Shandong University of Science and Technology, Qingdao, China.




 


Dr. Huakun Bi, a Lecturer at the School of Electrical and Automation Engineering, Shandong University of Science and Technology, is a prolific researcher in power electronics. He earned his Ph.D. from Tianjin University in 2020 and has since demonstrated significant academic and industrial contributions. With 17 research papers—12 SCI and 15 EI indexed—and multiple prestigious research projects, he has become a leading expert in DC-DC converters, electric vehicles, and DC microgrids. Dr. Bi’s innovative designs have enhanced voltage regulation and energy efficiency in electric vehicle systems. His high citation count, active role as a journal reviewer, and leadership in government- and industry-funded projects reflect outstanding research impact and make him an excellent candidate for the Best Researcher Award.




🌍 Professional Profile:


Scopus


Orcid


🏆 Suitability for the Best Researcher Award


 






































Dr. Shahrzad Falahat exemplifies excellence in applied AI research, making her a highly suitable candidate for the Best Researcher Award. With a Ph.D. in Computer Vision and over five years of impactful industrial experience, she has led innovative projects that address critical real-world challenges. Her development of AI-powered fault detection software for power transmission lines reduced outages by 70%, while her automated cartography system cut map production time by 80%. She combines deep technical expertise in Python, PyTorch, TensorFlow, and embedded AI with strong project management and cross-sector collaboration. Her work integrates research and practice, resulting in scalable, intelligent solutions with tangible societal benefits, positioning her as a leader in the field of AI and computer vision.






































🎓 Education 


Dr. Huakun Bi earned his Ph.D. in Electrical Engineering from Tianjin University, Tianjin, China, in 2020, where he conducted advanced research in power conversion technologies and electric transportation systems. His doctoral work focused on the design and optimization of DC-DC converters, especially for fuel cell and electric vehicle applications. His academic foundation includes rigorous training in circuit theory, control systems, and energy systems. During his doctoral studies, he led one independent innovation project and contributed to several national-level research initiatives. His education equipped him with a strong theoretical and practical understanding of modern electrical systems, laying the groundwork for his impactful contributions as a researcher and lecturer at the Shandong University of Science and Technology.


🏢 Work Experience 


Dr. Huakun Bi currently serves as a Lecturer at the School of Electrical and Automation Engineering, Shandong University of Science and Technology, Qingdao. Since earning his Ph.D. in 2020, he has taken on leadership roles in academic and industrial research, including projects funded by the Shandong Natural Science Foundation, State Grid Corporation of China, and Huaneng Group. He has contributed to three additional school-enterprise cooperation projects. Dr. Bi also acts as a dedicated reviewer for five international journals in electrical engineering. His dual involvement in academia and applied industrial projects demonstrates a versatile and impactful career. His research work is not only academically significant but also practically relevant, bridging the gap between theoretical advancements and real-world implementation.


🏅 Awards and Honors 


Dr. Huakun Bi’s research excellence is reflected in the high citation of his publications, notably in top-tier journals such as IEEE Transactions on Industrial Electronics and IEEE Transactions on Vehicular Technology. His 2019 publication has been cited 77 times, showcasing his work’s global impact. He has received recognition for his leadership in innovation projects at Tianjin University and has earned competitive funding from the Shandong Provincial Natural Science Foundation. Dr. Bi’s sustained contribution to national and industry-funded projects highlights the practical value of his research. His selection as a peer reviewer for multiple international journals further underscores his expertise and reputation in the field of power electronics and DC microgrids. These honors position him strongly for research excellence awards.


🔬 Research Focus 
































































Dr. Huakun Bi’s research primarily targets high-performance DC-DC converters, energy-efficient electric vehicles, and stable DC microgrid systems. His work addresses core challenges in power electronics, including input current ripple reduction, wide voltage-gain range, and voltage stress mitigation. By introducing advanced converter topologies such as capacitor-clamped and dual-mode negative output converters, he enhances performance for fuel cell and EV applications. Dr. Bi has also contributed significantly to government- and industry-funded projects, applying theoretical innovations to practical systems. His papers are frequently cited in top journals, and his designs serve critical roles in electric transportation and energy systems. Through pioneering control methods and hardware design strategies, Dr. Bi is driving forward the next generation of clean, efficient energy solutions.




























































































📊 Publication Top Notes:


    

  1. 

    Huakun Bi, Zonglei Mou, Yu Chen
    
“Common Grounded Wide Voltage-Gain Range DC–DC Converter With Zero Input Current Ripple and Reduced Voltage Stresses for Fuel Cell Vehicles”
    
Journal: IEEE Transactions on Industrial Electronics
    
Year: 2023
    
DOI: 10.1109/TIE.2022.3172767
    
Citations: 23
    

    2. 



    

  1. 

    Huakun Bi, Bo Li, Ping Wang, Zhishuang Wang, Xiaochen Ma
    
“A New Coupled-Inductor-Based High-Gain Interleaved DC-DC Converter With Sustained Soft Switching”
    
Journal: IEEE Transactions on Vehicular Technology
    
Year: 2021
    
DOI: 10.1109/TVT.2021.3083317
    
Citations: Not specified
    

    2. 



    

  1. 

    Huakun Bi, Cong Jia
    
“Common Grounded Wide Voltage‐Gain Range DC–DC Converter for Fuel Cell Vehicles”
    
Journal: IET Power Electronics
    
Year: 2019
    
DOI: 10.1049/iet-pel.2018.6234
    
Citations: 16
    

    2. 



    

  1. 

    Guidan Li, Zhe Yang, Bin Li, Huakun Bi
    
“Power Allocation Smoothing Strategy for Hybrid Energy Storage System Based on Markov Decision Process”
    
Journal: Applied Energy
    
Year: 2019
    
DOI: 10.1016/j.apenergy.2019.03.001
    
Citations: Not specified
    

    2. 



    

  1. 

    Huakun Bi, Ping Wang, Yu Che
    
“A Capacitor Clamped H-Type Boost DC–DC Converter With Wide Voltage-Gain Range for Fuel Cell Vehicles”
    
Journal: IEEE Transactions on Vehicular Technology
    
Year: 2019
    
DOI: 10.1109/TVT.2018.2884890
    
Citations: 77
    

    2. 


	


	

	






	
	

		


Akibul Islam Chowdhury | Public Health Nutrition | Best Researcher Award
			

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Mr. AkibulIslam Chowdhury |Public Health Nutrition |Best Researcher Award




Senior Lecturer at Daffodil International University,Bangladesh.




 


Akibul Islam Chowdhury is a dedicated academic and researcher at Daffodil International University, serving in the Department of Nutrition and Food Engineering. He holds both B.Sc. and M.Sc. degrees in Food Technology and Nutrition Science from Noakhali Science and Technology University (NSTU), where he achieved top honors. With over 15 publications in peer-reviewed journals, his work explores nutritional biochemistry, public health, food allergies, metabolic disorders, and diet-disease correlations. Akibul’s passion for food science is reflected in his commitment to student-centered education and evidence-based research. Recognized for his academic excellence and communication skills, he received the Best PowerPoint Presentation Award at a national seminar. His balanced profile of teaching, research, and publication makes him a strong contender for the Best Researcher Award.




🌍 Professional Profile:


Google scholar


Orcid


Scopus


🏆 Suitability for the Best Researcher Award


 






































Akibul Islam Chowdhury is an outstanding young researcher with significant contributions in the fields of nutrition, public health, and food science. With over 15 peer-reviewed publications, including works in Food Chemistry: Molecular Sciences and Obesity Medicine, he has tackled topics ranging from allergen identification to metabolic disease management. He earned top academic honors during his M.Sc. and B.Sc. at NSTU and actively guides students through research-based learning at Daffodil International University. His strong publication record, academic excellence, and impactful research on health-related nutritional issues position him as a leading candidate for the Best Researcher Award. Akibul combines analytical rigor with social relevance, embodying the qualities of a dedicated scholar and innovator in nutrition science.






































🎓 Education 


Akibul Islam Chowdhury earned his M.Sc. in Food Technology and Nutrition Science from Noakhali Science and Technology University in 2020 (held in 2021), graduating with a perfect GPA of 4.00 and securing first position in his class. He also completed his B.Sc. from the same department and university in 2019 (held in 2020), earning a CGPA of 3.65 and ranking third. His earlier academic journey included an HSC from Govt. Science College, Dhaka (2015), and an SSC from A.K. High School (2013), both with outstanding results—GPA 5.00 in each. His academic record reflects consistent excellence and dedication to nutrition and food science, laying a solid foundation for his teaching and research contributions in the field.


🏢 Work Experience 


Akibul Islam Chowdhury has gained academic and research experience as a Research Assistant at the Department of Food Technology and Nutrition Science, NSTU. His responsibilities included conducting literature reviews, designing nutritional studies, data collection and analysis, and co-authoring scientific papers. Currently, he serves as a faculty member in the Department of Nutrition and Food Engineering at Daffodil International University, Savar, Dhaka. In this role, he integrates teaching with applied research, guiding students in nutritional science, public health, and dietary practices. His experience bridges both classroom education and lab-based research, providing students with a work-based learning approach. His involvement in multiple collaborative studies has sharpened his analytical skills and nurtured his academic leadership.


🏅 Awards and Honors 


Akibul Islam Chowdhury has been recognized for his academic performance and presentation skills. Most notably, he received the Best PowerPoint Presentation Award at the 2nd National Food Science Seminar organized at Noakhali Science and Technology University. This recognition reflects his clarity in scientific communication and ability to present complex data effectively to both academic and non-specialist audiences. In addition to this award, his consistent academic excellence—ranking first in his master’s program and third in his undergraduate class—demonstrates high academic merit. His early academic success in HSC and SSC examinations (GPA 5.00) further confirms a solid educational foundation. These achievements underscore his dedication and suitability for honors like the Best Researcher Award.


🔬 Research Focus 
































































Akibul Islam Chowdhury’s research is anchored in the intersections of nutrition, food science, and public health. His work investigates metabolic disorders, gene-nutrient interactions, micronutrient supplementation, food-borne allergies, and the role of traditional plants like Stevia and Aloe vera in managing diabetes and obesity. He has conducted meta-analyses, systematic reviews, and clinical evaluations, contributing to journals such as Food Chemistry: Molecular Sciences and Obesity Medicine. His current interests include the molecular identification of lentil allergens, dietary impacts on COVID-19 severity, and public health nutrition interventions in Bangladesh. By integrating biostatistics and nutritional biochemistry, Akibul’s research aims to inform public health policy and dietary guidelines, emphasizing evidence-based solutions for lifestyle diseases and community health.




























































































📊 Publication Top Notes:


    

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    Chowdhury, A. I., Ghosh, S., Hasan, M. F., Khandakar, K. A. S., & Azad, F. (2021). Prevalence of insomnia among university students in South Asian Region: a systematic review of studies. Journal of Preventive Medicine and Hygiene, 61(4), E525. Citations: 67
    

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    Chowdhury, A. I., Rahanur Alam, M., Raihan, M. M., Rahman, T., Islam, S., et al. (2022). Effect of stevia leaves (Stevia rebaudiana Bertoni) on diabetes: A systematic review and meta‐analysis of preclinical studies. Food Science & Nutrition, 10(9), 2868–2878. Citations: 34
    

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    Chowdhury, A. I., Alam, M. R., Rabbi, M. F., Rahman, T., & Reza, S. (2021). Does higher body mass index increase COVID-19 severity? A systematic review and meta-analysis. Obesity Medicine, 23, 100340. Citations: 31
    

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    Sultana, M., Dhar, S., Hasan, T., Shill, L. C., Purba, N. H., Chowdhury, A. I., et al. (2022). Knowledge, attitudes, and predictors of exclusive breastfeeding practice among lactating mothers in Noakhali, Bangladesh. Heliyon, 8(10). Citations: 28
    

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    Chowdhury, A. I. (2020). Role and effects of micronutrients supplementation in immune system and SARS-Cov-2 (COVID-19). Asian Journal of Immunology, 4(2), 47–55. Citations: 26
    

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    Chowdhury, A. I., Shill, L. C., Raihan, M. M., Rashid, R., Bhuiyan, M. N. H., Reza, S., et al. (2024). Human health risk assessment of heavy metals in vegetables of Bangladesh. Scientific Reports, 14(1), 15616. Citations: 22
    

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    Ghosh, S., Kabir, M. R., Alam, M. R., Chowdhury, A. I., & Al Mamun, M. A. (2022). Balanced diet related knowledge, attitude and practices (KAP) among adolescent school girls in Noakhali district, Bangladesh: A cross sectional study. International Journal of Adolescent Medicine and Health, 34(5), 319–325. Citations: 22
    

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    Chowdhury, A. I., & Alam, M. R. (2024). Health effects of heavy metals in meat and poultry consumption in Noakhali, Bangladesh. Toxicology Reports, 12, 168–177. Citations: 16
    

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    Halima, O., Najar, F. Z., Wahab, A., Gamagedara, S., Chowdhury, A. I., Foster, S. B., et al. (2022). Lentil allergens identification and quantification: An update from omics perspective. Food Chemistry: Molecular Sciences, 4, 100109. Citations: 16
    

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    Islam, M. S., Chowdhury, A. I., Shill, L. C., Reza, S., & Alam, M. R. (2023). Heavy metals induced health risk assessment through consumption of selected commercially available spices in Noakhali district of Bangladesh. Heliyon, 9(11). Citations: 14
    

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    Habib, M. A., Alam, M. R., Rahman, T., Chowdhury, A. I., & Shill, L. C. (2023). Knowledge, attitudes, and practices (KAP) of nutrition among school teachers in Bangladesh: A cross-sectional study. PLOS ONE, 18(3), e0283530. Citations: 13
    

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    Habib, M. A., Chowdhury, A. I., Alam, M. R., & Rahman, T. (2023). Commercially available iodized salts in Noakhali, Bangladesh: estimation of iodine content, stability, and consumer satisfaction level. Food Chemistry Advances, 2, 100294. Citations: 10
    

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    Shill, L. C., Alam, M. R., Chowdhury, A. I., & Alam, S. (2021). Association of FTO gene (rs9939609) with obesity and type-2 diabetes mellitus: Review from current studies. Romanian Journal of Diabetes Nutrition and Metabolic Diseases, 28(4), 447–452. Citations: 8
    

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    Reza, S., Alam, M. R., Chowdhury, A. I., Mamun, M. A. A., Akhter, M., & Habib, M. A. (2023). Assessing nutritional status and functionality in geriatric population of Bangladesh: the hidden epidemic of geriatric malnutrition. Gerontology and Geriatric Medicine, 9, 23337214231172663. Citations: 6
    

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    Habib, M. A., Dey, M., Chowdhury, A. I., Rahman, T., & Kundu, R. K. (2022). Current knowledge, attitude, and practice (KAP) towards physical activity (PA) and its impact on obesity management in Bangladesh: A cross‐sectional study. Health Science Reports, 5(6), e960. Citations: 6
    

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    Alam, M. R., Hossain, M. S., Chowdhury, A. I., Akhter, M., Mamun, A. A., & Reza, S. (2020). Relationship between malnutrition and functional disability in selected community-dwelling geriatric population in Bangladesh. medRxiv, 2020.08.02.20167049. Citations: 4
    

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    Chowdhury, A. I., Habib, M. A., & Rahman, T. (2022). Factors Influencing the Utilization of Antenatal Care, Institutional Delivery, and Postnatal Care Services Among Women in Bangladesh. Makara Journal of Health Research, 26(3), 1. Citations: 3
    

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    Chowdhury, A. I., Habib, M. A., & Ghosh, S. (2021). Effect of Saffron (Crocus sativus L.) on Common Non-Communicable Disease: Review from Current Clinical Findings. Journal of Ayurvedic and Herbal Medicine, 7(2), 93–108. Citations: 3
    

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    Habib, M. A., Chowdhury, A. I., Hossen, K., Kibria, T., & Hossain, M. (2020). Fast food intake and prevalence of overweight/obesity in students: do eating habits have a differential impact on gender. Journal of Contemporary Medical Research, 7(6), F4–F9. Citations: 3
    

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Javier Ramírez | Computational Mechanics | Best Researcher Award
			

				Published on  by Engineering Scientist			

		
	


	

		
Dr. Javier Ramírez | Mechanics |Best Researcher Award




Professor at Universidad de Chile, Chile.


Dr. Javier Ramírez Ganga is an Adjunct Professor at the Universidad de Chile’s Department of Mathematical Engineering and a Project Engineer at the Center for Mathematical Modeling (CMM). With a Ph.D. in Engineering Sciences specializing in Mathematical Modeling, his research bridges numerical methods and real-world applications in mining, hydrology, and inverse problems. He has co-authored impactful publications in prestigious journals and actively contributes to national research projects. His international research visits and collaborations, especially in France, highlight his global engagement. Dr. Ramírez’s innovative work in gradient damage models and control theory positions him as a leader in applied mathematics, making him a highly deserving candidate for the Best Researcher Award.


🌍 Professional Profile:


Orcid


🏆 Suitability for the Best Researcher Award


 






































Dr. Javier Ramírez Ganga is a strong contender for the Best Researcher Award due to his significant contributions to computational mechanics, inverse problems, and applied mathematics. His academic path from a B.Sc. in Mathematics to a Ph.D. in Engineering Sciences with a focus on mathematical modeling demonstrates a deep commitment to interdisciplinary and application-driven research. His current roles as Adjunct Professor and Project Engineer at Universidad de Chile and the Center for Mathematical Modeling reflect leadership in impactful research environments.






































🎓 Education 


Javier Ramírez Ganga earned his Ph.D. in Engineering Sciences with a focus on Mathematical Modeling from Universidad de Chile in 2021. His doctoral thesis addressed the numerical reconstruction of inverse problems for partial differential equations under the supervision of Jaime H. Ortega and Gino Montecinos. He previously completed a Mathematical Engineering degree in 2016 at Universidad de Santiago de Chile, where he developed numerical approximations for exact controls in the 2D heat equation. His academic journey began with a B.Sc. in Mathematics from the same institution in 2015. This strong mathematical foundation supports his interdisciplinary research, blending advanced theory with real-world computational modeling. His training reflects both academic excellence and practical problem-solving skills.


🏢 Work Experience 


Dr. Ramírez currently serves as an Adjunct Professor at the Universidad de Chile’s Department of Mathematical Engineering and as a Project Engineer at the CMM. Since 2020, he has contributed to several major national research projects, including FONDEF IDEA initiatives and the Advanced Center for Water Technologies (CAPTA), working on numerical methods for engineering applications. His supervisors include prominent researchers such as Jaime H. Ortega and James Mc Phee. Internationally, he conducted two research stays at Institut Fourier, Université Grenoble-Alpes, France. His expertise spans numerical modeling, applied mathematics, and inverse problems, enabling collaborations across engineering and environmental sciences. His experience demonstrates versatility and a sustained commitment to high-impact, interdisciplinary research.


🏅 Awards and Honors 


While specific awards are not listed, Dr. Javier Ramírez Ganga’s scholarly output and participation in prestigious research projects demonstrate a high level of academic recognition. His publications in Applied Mathematical Modelling and Mathematical Reports, along with presentations at major conferences like MassMin 2020, highlight the academic impact of his work. His repeated invitations for international research visits to the Institut Fourier, Université Grenoble-Alpes, signal his growing global reputation. His continued selection for competitive national projects such as FONDEF IDEA and CAPTA also reflects the confidence of Chile’s research funding bodies in his expertise. These accomplishments collectively suggest a trajectory of excellence and make him a strong candidate for future honors and distinctions.


🔬 Research Focus 
































































Dr. Javier Ramírez Ganga’s research centers on numerical analysis, control theory, and inverse problems in partial differential equations (PDEs), with strong applications in engineering and environmental modeling. His recent work includes gradient damage models for underground mining, CGO solutions for coupled conductivity equations, and inverse modeling for water technologies. He applies computational tools like Python, FreeFem++, and Matlab to simulate complex systems and propose efficient solutions for practical challenges. His interdisciplinary collaborations bridge applied mathematics, geophysics, and hydrology, contributing to innovation in sustainable mining and water resource management. By integrating mathematical rigor with engineering relevance, his work enhances the predictive power of simulations and informs policy and design in critical sectors.




























































































📊 Publication Top Notes:


Journal Articles


Bonnetier, E., Gaete, S., Jofré, A., Lecaros, R., Montecinos, G., Ortega, J. H., Ramírez-Ganga, J., & San Martín, J. S. (2025). Gradient damage models for studying material behavior in underground mining. Applied Mathematical Modelling, 116171.


Lecaros, R., Montecinos, G., Ortega, J. H., & Ramírez-Ganga, J. (2022). CGO solutions for coupled conductivity equations. Mathematical Reports, 24(1–2), 217–220.


Conference Proceedings


Gaete, S., Jofré, A., Lecaros, R., Montecinos, G., Ortega, J. H., Ramírez-Ganga, J., & San Martín, J. S. (2020). A gradient damage model applied to underground mining methods. In MassMin 2020: Proceedings of the Eighth International Conference & Exhibition on Mass Mining. University of Chile.


Preprints


Bonnetier, E., Gaete, S., Jofré, A., Lecaros, R., Montecinos, G., Ortega, J. H., Ramírez-Ganga, J., & San Martín, J. S. (2020). A shear-compression damage model for the simulation of underground mining by block caving. arXiv preprint, arXiv:2012.11118.


Gaete, S., Jofré, A., Lecaros, R., Montecinos, G., Ortega, J. H., Ramírez-Ganga, J., & San Martín, J. S. (2020). A fast algorithm of the shear-compression damage model for the simulation of block caving. arXiv preprint, arXiv:2012.14776.