Reza SojoudiZadeh | Engineering | Best Researcher Award

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Assist. Prof. Dr. Reza SojoudiZadeh | Engineering | Best Researcher Award

Assistant Professor at Department of Civil Engineering, Mahabad Branch, Islamic Azad University, Mahabad, Iran

Dr. Reza Sojoudi Zadeh is an Associate Professor in the Department of Civil Engineering at Mahabad Branch, Islamic Azad University, Iran. His research focuses on structural optimization, seismic performance of buildings, and concrete technology. He has published extensively in high-impact journals, contributing to advancements in soft computing techniques, metaheuristic optimization, and earthquake-resistant structures. With a strong academic background, he teaches both undergraduate and graduate courses, specializing in finite element analysis, structural optimization, and reinforced concrete structures. His expertise bridges the gap between theoretical research and practical engineering applications, making significant contributions to civil engineering.

Professional Profile 

Education

Dr. Sojoudi Zadeh earned his Ph.D. in Civil Engineering (Structural Engineering) from Urmia University, Iran (2014-2018), where he focused on seismic performance-based life cycle cost optimization of steel moment frames using soft computing techniques. He completed his M.Sc. in Structural Engineering from Tabriz University (2000-2002), working on dynamic soil-structure interaction using SAP2000 software. His B.Sc. in Civil Engineering (1996-2000) from Tabriz University laid the foundation for his expertise in structural analysis and design.

Professional Experience

Dr. Sojoudi Zadeh is an Associate Professor at Islamic Azad University, Mahabad Branch, where he has been actively involved in research, teaching, and mentoring students. His academic career spans over two decades, during which he has taught undergraduate and postgraduate courses in statics, reinforced concrete design, structural optimization, and finite element analysis. He has authored numerous peer-reviewed research papers and collaborated on studies focusing on structural performance, seismic resilience, and advanced optimization algorithms. His contributions extend to engineering software applications and innovative design methodologies for sustainable and resilient structures.

Research Interest

Dr. Reza Sojoudi Zadeh is an Associate Professor in the Department of Civil Engineering at Mahabad Branch, Islamic Azad University, Iran. His research focuses on structural optimization, seismic performance of buildings, and concrete technology. He has published extensively in high-impact journals, contributing to advancements in soft computing techniques, metaheuristic optimization, and earthquake-resistant structures. With a strong academic background, he teaches both undergraduate and graduate courses, specializing in finite element analysis, structural optimization, and reinforced concrete structures. His expertise bridges the gap between theoretical research and practical engineering applications, making significant contributions to civil engineering.

Awards and Honors

Dr. Sojoudi Zadeh has received recognition for his research contributions in structural engineering and optimization methodologies. His published works in high-impact international journals have been widely cited, earning him academic distinction. Additionally, he has played a key role in supervising and mentoring research students, further solidifying his reputation as an expert in seismic safety and structural analysis.

Research Skills

Dr. Sojoudi Zadeh possesses expertise in finite element analysis, structural modeling, and computational optimization. He is proficient in using engineering software such as SAP2000, ETABS, ANSYS, and MATLAB for structural simulations and performance evaluations. His skills in metaheuristic algorithms, AI-based structural optimization, and seismic design methodologies allow him to develop efficient, cost-effective, and safe structural solutions. Additionally, he has strong analytical and problem-solving skills, enabling him to conduct data-driven research and experimental validations in civil and structural engineering.

Conclusion

Dr. Reza Sojoudi Zadeh is a strong candidate for the Best Researcher Award, particularly in the domain of structural optimization and seismic engineering. His work in metaheuristic optimization, AI applications in structural engineering, and earthquake-resistant structures is significant. However, to strengthen his application, he could focus on increasing research impact (citations, collaborations), engaging in applied research, and obtaining high-profile recognitions.

Publications Top Noted

  • Title: Modified Sine-Cosine Algorithm for Sizing Optimization of Truss Structures with Discrete Design Variables

    • Authors: S. Gholizadeh, R. Sojoudizadeh
    • Year: 2019
    • Citations: 32

  • Title: Shape and Size Optimization of Truss Structure by Means of Improved Artificial Rabbits Optimization Algorithm

    • Authors: S. L. SeyedOskouei, R. Sojoudizadeh, R. Milanchian, H. Azizian
    • Year: 2024
    • Citations: 8

  • Title: Elite Particles Method in Discrete Metaheuristic Optimization of Structures

    • Authors: R. Sojoudizadeh, S. Gholizadeh
    • Year: 2022
    • Citations: 2

  • Title: Sizing Optimization of Truss Structures with Discrete Design Variables Using Combined PSO Algorithm with Special Particles Method

    • Authors: A. Gheibi, R. Sojoudizadeh, H. Azizian, M. Gheibi
    • Year: 2024
    • Citations: 1

  • Title: Seismic Optimization of Steel Mega‐Braced Frame With Improved Prairie Dog Metaheuristic Optimization Algorithm

    • Authors: T. PayamiFar, R. Sojoudizadeh, H. Azizian, L. Rahimi
    • Year: 2025

  • Title: Seismic Behavior of Concrete Shear Wall with Lap-Spliced Rebar and Sleeve

    • Authors: J. Hasankhani, E. Shafei, R. Sojoudizadeh, S. J. Ghaderi
    • Year: 2024

  • Title: Effect of Configuration Angle on Seismic Performance of Tall Steel Diagrid Frames

    • Authors: R. Sojoudizadeh, R. Milanchian, H. Azizian, A. Beirami Shahabi
    • Year: 2024

  • Title: Enhancing Seismic Performance of Lap-Spliced Concrete Shear Walls by Rebar-Debonding

    • Authors: J. Hasankhani, E. Shafei, R. Sojoudizadeh, S. J. Ghaderi
    • Year: 2024

  • Title: روش ذرات نخبه در بهینه سازی گسسته سازه ها‎ (Elite Particles Method in Discrete Optimization of Structures)

    • Authors: سجودی زاده, قلی زاده قلعه عزیز‎ (R. Sojoudizadeh, S. Gholizadeh)
    • Year: 2022

Anuj Kumar | Engineering | Best Researcher Award

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Mr. Anuj Kumar | Engineering | Best Researcher Award

Assistant Professor at Management Education & Research Institute, Janakpuri, India

Anuj Kumar is an accomplished academic and researcher in Computer Science & Engineering, currently pursuing a Ph.D. in Image Processing at AKTU, Lucknow. With over a decade of teaching experience at institutions like Guru Gobind Singh Indraprastha University and IIMT College of Engineering, he has significantly contributed to education and research. His expertise spans artificial intelligence, computer graphics, and data structures, complemented by proficiency in programming languages such as Python, C++, and MATLAB. He has published research papers in Scopus-indexed journals, IEEE Explorer, and Elsevier, along with a book chapter on distributed artificial intelligence. Recognized for his contributions, he was awarded at the Smart India Hackathon 2018 and qualified GATE 2012 with an 85.04 percentile. Anuj is actively involved in academic leadership, faculty development, and university assessments. With a commitment to innovation and interdisciplinary research, he aspires to advance computational methodologies and industrial applications in artificial intelligence and image processing.

Professional Profile 

Education

Anuj Kumar has a strong academic background in Computer Science & Engineering. He is currently pursuing a Ph.D. in Image Processing from Dr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow, Uttar Pradesh, demonstrating his commitment to advanced research. He earned his M.Tech in Computer Science & Engineering from Guru Gobind Singh Indraprastha University, Delhi, in 2014, securing a first division. His undergraduate studies include a B.Tech in Computer Science & Engineering from the Institution of Electronics & Telecommunication Engineers (IETE), Delhi, in 2011, also with first-division honors. Additionally, he holds a Three-Year Diploma in Computer Science & Engineering from IETE, Delhi (2006). His early education was completed under the U.P. Board, where he finished 10th grade (2000) and 12th grade (2003) in the second division. His educational journey, enriched with technical certifications like MCAD (Microsoft Certified Application Developer) in 2006, has laid a strong foundation for his expertise in computing and research.

Professional Experience

Anuj Kumar has extensive academic experience as an Assistant Professor in Computer Science & Engineering, with a teaching career spanning over a decade across prestigious institutions. Since July 2023, he has been serving at MERI College of Engineering and Technology, Haryana. Prior to this, he worked at IIMT College of Engineering, Greater Noida (2022–2023) and Greater Noida Institute of Technology, GGSIPU (2018–2022), where he contributed to curriculum development and research initiatives. He also held academic positions at USIC&T, Guru Gobind Singh Indraprastha University (2017–2018) and Ram-Eesh Institute of Engineering & Technology (2017). Earlier in his career, he served at Baba Saheb Ambedkar Institute of Technology & Management (2014–2016) and The Institution of Electronics & Telecommunication Engineers, Delhi (2011–2012). His vast experience includes mentoring students, conducting faculty development programs, and leading academic audits, showcasing his commitment to education, research, and institutional development.

Research Interest

Anuj Kumar’s research interests lie at the intersection of computer vision, image processing, artificial intelligence, and computational methods. Currently pursuing a Ph.D. in Image Processing, he focuses on developing advanced techniques for image enhancement, noise removal, and forgery detection using deep learning algorithms. His expertise extends to computer graphics, formal language automata, database management systems (DBMS), data structures, and discrete mathematics, which serve as the foundation for his research innovations. He has actively contributed to AI-driven industrial systems, biodiversity assessment using hyperspectral imaging, and disruptive innovations in tech-business analytics. His work has been published in Scopus-indexed journals, IEEE conference proceedings, and reputed international journals, reflecting the impact of his research. Additionally, he explores the applications of distributed artificial intelligence (DAI) for document retrieval, emphasizing intelligent data processing techniques. His dedication to cutting-edge research strengthens his role as a mentor and academician in the field of computer science and engineering.

Award and Honor

Anuj Kumar has been recognized for his academic excellence and research contributions through various awards and honors. He was awarded in the Smart India Hackathon 2018, a prestigious national-level competition promoting innovation and problem-solving skills. Demonstrating strong technical acumen, he qualified GATE 2012 with an impressive 85.04 percentile and a score of 302, showcasing his expertise in computer science and engineering. His achievements extend beyond academics, as he was the runner-up in the 100m race at IETE, New Delhi, in 2005, highlighting his diverse talents. Additionally, he has played a significant role in academia as a convener of the Joint Assessment Committee (JAC) for academic audits, deputy center superintendent for examinations, and university representative in various assessment programs. His dedication to research and education is further reflected in his memberships on editorial boards and professional organizations, solidifying his reputation as a distinguished academic and researcher.

Research Skill

Anuj Kumar possesses a strong research skillset that spans multiple domains within computer science and engineering, particularly in image processing, artificial intelligence, and computational methods. His expertise in deep learning, fuzzy techniques, and hyperspectral imaging enables him to develop innovative solutions for image enhancement, noise removal, and forgery detection. He is proficient in Python, MATLAB, C++, and various database management systems (DBMS), which support his research in data analysis, automation, and intelligent computing. His ability to critically analyze complex problems, design experiments, and implement advanced algorithms has led to multiple Scopus-indexed publications, IEEE conference presentations, and book chapters. Additionally, his role in academic audits, faculty development programs, and technical training workshops demonstrates his leadership in research and education. His strong analytical thinking, problem-solving capabilities, and hands-on approach to emerging technologies make him a highly skilled researcher in the field of computer vision and artificial intelligence.

Conclusion

Anuj Kumar has a strong academic foundation, technical expertise, and a growing research portfolio in computer science and engineering. His contributions to image processing, artificial intelligence, and industrial automation position him as a promising candidate for the Best Researcher Award. However, enhancing high-impact publications, research collaborations, and funding contributions would further strengthen his profile for this recognition.

Publications Top Noted

  • P., Jaidka, Preeti, P., Upadhyay, Prashant, A., Kumar, Aman, A.S., Kumar, Anuj Shiva, S.P., Yadav, Satya Prakash (2024). Transforming Coconut Farming with Deep Learning Disease Detection. Evergreen. Citations: 0

  • D., Sharma, Deepak, A.S., Kumar, Anuj Shiva, N., Tyagi, Nitin, S.S., Chavan, Sunil S., S.M.P., Gangadharan, Syam Machinathu Parambil (2024). Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT. Measurement: Sensors. Citations: 3

  • S., Singh, Sandeep, B.K., Singh, B. K., A.S., Kumar, Anuj Shiva (2024). Multi-organ segmentation of organ-at-risk (OAR’s) of head and neck site using ensemble learning technique. Radiography. Citations: 3

  • R., Naz, Rahat, A.S., Kumar, Anuj Shiva (2024). Surveying Quantum-Proof Blockchain Security: The Era of Exotic Signatures. Conference Paper. Citations: 1

 

Mohammad Parhamfar | Engineering | Best Researcher Award

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Dr. Mohammad Parhamfar | Engineering | Best Researcher Award

www.parhamfar.com, Iran

Dr. Mohammad Parhamfar is a distinguished renewable energy expert and electrical engineer specializing in solar energy, with 19 years of experience spanning software development, electrical engineering, and sustainable energy solutions. Holding a Doctor of Business Administration (DBA) and a Master’s in Renewable Energy, he has contributed significantly to the field through over 40 published papers, eight authored books, and multiple patents in electrical software design and lightning protection for solar farms. As a leader in solar project development, he has designed 50 MW solar projects, implemented 1 MW rooftop systems, and played a key role in Iran’s first 10 MW solar power plant. He has received numerous awards, including the 2023 Creative Researcher Award, and serves on the editorial boards of various energy-related journals. His innovations in energy management, microgrids, and carbon trading, along with his active participation in international conferences, cement his reputation as a pioneering researcher and industry leader.

Professional Profile 

Education

Dr. Mohammad Parhamfar holds a Doctor of Business Administration (DBA), a Master’s degree in Renewable Energy, and a Bachelor’s degree in Electrical Engineering. His multidisciplinary educational background integrates technical expertise with strategic business management, enabling him to drive innovation in renewable energy and electrical engineering. His academic journey has equipped him with deep knowledge in solar energy systems, electrical installations, and energy management. He has also obtained numerous technical certifications in solar designing, energy auditing, microgrids, and IEEE teaching standards, further strengthening his expertise in sustainable energy solutions. His commitment to education extends beyond personal learning, as he has actively contributed to academia as a lecturer in solar energy, sharing his knowledge with students and professionals. Dr. Parhamfar’s strong academic foundation, coupled with practical experience, has positioned him as a leader in the field, allowing him to contribute significantly to large-scale solar projects, research, and policy development.

Professional Experience

Dr. Mohammad Parhamfar boasts an extensive professional career spanning over 19 years in renewable energy, electrical engineering, and software development. He has held key leadership positions, including CEO of Yeganeh Energy, where he managed the implementation of solar projects, and CTO of Applebone Company, specializing in solar energy and IT solutions. Dr. Parhamfar has led the development of large-scale solar projects, including designing a 50 MW solar system and coordinating the first 10 MW solar power plant in Iran. He has also served as a project manager and electrical engineer for various high-profile projects, such as the 1000 MW solar farm in Isfahan and multiple international solar initiatives in Armenia and Oman. As a freelancer, he has provided consulting services to several organizations, contributing his expertise in renewable energy, electrical systems design, and project management. His work has earned him recognition as a leader in the renewable energy sector.

Research Interest

Dr. Mohammad Parhamfar’s research interests lie at the intersection of renewable energy, electrical engineering, and sustainable development. His primary focus is on solar energy systems, particularly the design, implementation, and optimization of large-scale solar projects. He is also deeply involved in the integration of artificial intelligence with renewable energy solutions to enhance efficiency and performance. Dr. Parhamfar is passionate about addressing climate change through sustainable energy practices, with research extending into carbon trading and energy management strategies. He has explored innovative topics like lightning protection systems, grounding techniques for solar farms, and the development of electrical software for energy systems. His contributions to the renewable energy field include pioneering projects such as the first low-energy government building in Isfahan and the world’s first lightning risk assessment software for solar power plants. Additionally, Dr. Parhamfar is committed to exploring microgrid technology and its role in optimizing energy distribution and reducing environmental impacts.

Award and Honor

Dr. Mohammad Parhamfar has received numerous prestigious awards and honors for his groundbreaking contributions to renewable energy and electrical engineering. In 2023, he was recognized as a Creative Researcher by the International Academic Achievements and Award for his innovative work in solar energy. His remarkable achievements have also earned him recognition as the Best Innovative Engineer in 2013 in Isfahan and the Best Author in Modern Technology Journal in 2024. Dr. Parhamfar’s excellence in solar energy and engineering was further acknowledged when he ranked first in his Master’s program in Renewable Energy. He has also received accolades for his contributions to the energy sector, including being selected for his pioneering work on solar power plant insurance in Iran. His extensive involvement in research and development has earned him a reputation as a leading expert in renewable energy and a recipient of several honors for his contributions to technology and sustainability.

Research Skill

Dr. Mohammad Parhamfar possesses exceptional research skills that blend technical expertise with innovative problem-solving in the fields of renewable energy, electrical engineering, and energy management. His extensive experience in solar energy systems has enabled him to lead and contribute to cutting-edge research projects, particularly in the areas of solar power plant design, lightning protection systems, and energy optimization. Dr. Parhamfar’s research skills are demonstrated through his ability to apply complex concepts such as artificial intelligence to renewable energy solutions, enhancing the efficiency and effectiveness of energy systems. He is adept at utilizing software development tools to create groundbreaking solutions like the world’s first lightning risk assessment software for solar plants. Additionally, his ability to collaborate across multidisciplinary teams and lead large-scale research initiatives has made him a key figure in the energy sector. His research is marked by creativity, practical application, and a strong commitment to sustainable energy solutions.

Conclusion

Mohammad Parhamfar is highly suitable for the Best Researcher Award, particularly in Renewable Energy and Electrical Engineering. His strong research portfolio, industry contributions, patents, and leadership roles make him a leading figure in his field. Strengthening his academic publication impact, securing more international research funding, and increasing global collaborations would further enhance his competitiveness for the award.

Publications Top Noted

  • Title: Towards the application of renewable energy technologies in green ports: Technical and economic perspectives
    Authors: AMA Mohammad Parhamfar, Iman Sadeghkhani
    Year: 2023
    Citation: IET Renewable Power Generation, Volume 37
  • Title: EMPOWERING THE GRID: TOWARD THE INTEGRATION OF ELECTRIC VEHICLES AND RENEWABLE ENERGY IN POWER SYSTEMS
    Authors: MP Alireza Zabihi
    Year: 2024
    Citation: International Journal of Energy Security and Sustainable Energy (IJESSE), Volume 23
  • Title: Towards the net zero carbon future: A review of blockchain‐enabled peer‐to‐peer carbon trading
    Authors: M Parhamfar, I Sadeghkhani, AM Adeli
    Year: 2024
    Citation: Energy Science & Engineering, Volume 12, Issue 3, Pages 1242-1264
  • Title: Increase power output and radiation in photovoltaic systems by installing mirrors
    Authors: A Zabihi, M Parhamfar, SS Duvvuri, M Abtahi
    Year: 2024
    Citation: Measurement: Sensors, Volume 31, Article 100946
  • Title: Lightning Risk Assessment Software Design for Photovoltaic Plants in Accordance with IEC 62305-2
    Authors: M Parhamfar
    Year: 2022
    Citation: Energy System Research, Volume 5, Issue 2, Page 21
  • Title: Frequency and Time Series Analysis of Surge Arrester in Power Distribution Systems
    Authors: A Zabihi, M Parhamfar
    Year: 2024
    Citation: Advances in Engineering and Intelligence Systems, Volume 3, Issue 03, Pages 94-103
  • Title: A Light Weight Mobile Net SSD Algorithm based identification and Detection of Multiple Defects in Ceramic Insulators
    Authors: NB Mohammad Parhamfar, P. Bhavya Sree, K. Balaji
    Year: 2024
    Citation: Journal of Modern Technology, Volume 1, Issue 1, Pages 59-74
  • Title: Towards Green Airports: Factors Influencing Greenhouse Gas Emissions and Sustainability through Renewable Energy
    Authors: M Parhamfar
    Year: 2024
    Citation: Next Research, Article 100060
  • Title: Feasibility Study and Design of Smart Low-Energy Building Electrical Installations (Case Study: Isfahan University, Virtual Faculty Building)
    Authors: SS Mohammad Parhamfar
    Year: 2023
    Citation: Energy Systems Research Journal, Volume 6, Issue 3, Pages 57-74
  • Title: The Study of Electrical Grid Components After Installing a 10 MW Photovoltaic Power Plant with Large-Scale Batteries at Peak Load by DigSilent Software
    Authors: AA Mohammad Parhamfar
    Year: 2022
    Citation: American Journal of Electrical Power and Energy Systems, Volume 11, Issue 5, Pages 97-107

Mohammad Hossein Khosravi | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Mohammad Hossein Khosravi | Engineering| Best Researcher Award

Associate Professor at University of Birjand, Iran

Mohammad Hossein Khosravi is an Associate Professor in the Department of Mining Engineering at the University of Birjand, Iran. He holds a Ph.D. in Geotechnical Engineering from the Tokyo Institute of Technology and has a broad academic background, including an M.Sc. in Rock Mechanics from the University of Tehran. His research interests focus on geomechanics, rock/soil slope engineering, and tunneling, with a particular emphasis on physical modeling and retaining structures. Khosravi has earned numerous prestigious awards, including best paper/presentation honors at international conferences and a Ph.D. scholarship from Japan’s Monbukagakusho. He has also gained valuable experience through postdoctoral research at the Center for Urban Earthquake Engineering and consulting roles in geotechnical engineering. He is actively involved in several professional organizations and has been a faculty member at both the University of Birjand and the University of Tehran. His research and academic achievements have made significant contributions to the field of geotechnical engineering.

Professional Profile

Education

Mohammad Hossein Khosravi has an impressive academic background. He earned his Ph.D. in Geotechnical Engineering from the Tokyo Institute of Technology in Japan, completing his dissertation on the arching effect in geomaterials with applications to retaining walls and undercut slopes. Prior to that, he obtained an M.Sc. in Rock Mechanics from the University of Tehran, where he conducted research on the groutability of alluvial deposits at the Kheirabad Dam foundation. He began his academic journey with a B.Sc. in Mining Engineering from Shahid Bahonar University of Kerman, where he studied the permeability of oxidized copper ore against water and sulfuric acid. His educational path reflects a deep commitment to advancing geotechnical engineering and geomechanics.

Professional Experience

Mohammad Hossein Khosravi has extensive professional experience in both academia and industry. He is currently an Associate Professor in the Department of Mining Engineering at the University of Birjand, Iran, where he contributes to both teaching and research. Previously, he served as an Assistant Professor at the University of Tehran, further strengthening his academic profile. Khosravi’s professional experience extends beyond academia; he was a postdoctoral research fellow at the Center for Urban Earthquake Engineering at the Tokyo Institute of Technology and worked as a Geotechnical Consulting Engineer at TaiseiKiso Sekkei Company in Japan. Additionally, he has held positions as a university lecturer and geotechnical site engineer, where he applied his expertise in real-world projects. His career demonstrates a successful blend of teaching, research, and practical experience in geotechnical engineering.

Research Interest

Mohammad Hossein Khosravi’s research interests are primarily focused on geomechanics, with a specific emphasis on rock/soil slope engineering, tunneling, and the behavior of retaining structures. He is particularly interested in physical modeling in geotechnical engineering, investigating the complex interactions of geomaterials under various stress conditions. His work also explores the arching effect in geomaterials, which has significant applications in the design and stability of retaining walls and undercut slopes. These areas of research are critical for improving the safety and efficiency of infrastructure projects such as tunnels, slopes, and retaining structures, making his work highly relevant to both academia and industry in the field of geotechnical engineering.

Award and Honor

Mohammad Hossein Khosravi has received numerous prestigious awards and honors throughout his academic and professional career. Notably, he was recognized with certificate awards for best paper and presentation at the 10th International Conference on Earthquake Engineering in Tokyo (2012) and the Japanese Geotechnical Conference (2010), reflecting the high quality and impact of his research. He also earned a postdoctoral fellowship from the Center for Urban Earthquake Engineering (CUEE) in Tokyo in 2012, further solidifying his expertise in geotechnical engineering. Khosravi was awarded a Ph.D. scholarship by Japan’s Ministry of Education, Culture, Sports, Science, and Technology (Monbukagakusho) for his doctoral studies. Additionally, he was recognized as the second-ranked student in his M.Sc. program and the first-ranked student in his B.Sc. program, both achievements earning him notable accolades. His exceptional academic and research achievements demonstrate his dedication and influence in his field.

Conclusion

Mohammad Hossein Khosravi’s strong academic foundation, innovative research contributions, international exposure, and recognition through awards make him a very suitable candidate for the Best Researcher Award. His work in geotechnical engineering addresses crucial issues in infrastructure and safety, which are of global importance. By expanding his research visibility and collaborations, he has the potential to further elevate his impact in the scientific community. Overall, he demonstrates the qualities and achievements expected of a Best Researcher Award recipient.

Publications Top Noted

  • Title: Determination of the caving zone height using numerical and physical modeling based on the undercutting method, joint dip, and spacing
    Authors: Alipenhani, B., Jalilian, M., Majdi, A., Bakhshandeh Amnieh, H., Khosravi, M.H.
    Year: 2024
    Citations: 2
  • Title: Use of LBPs to estimate VBPs as observed from an investigation of physical model bimrocks
    Authors: Najafvand, K., Khosravi, M.H., Amini, M., Medley, E.
    Year: 2024
    Citations: 0
  • Title: Introducing a new rock abrasivity index using a scaled down disc cutter
    Authors: Moradi, M., Khosravi, M.H., Hamidi, J.K.
    Year: 2024
    Citations: 1
  • Title: Soil Arching and Ground Deformation around Tunnels in Sandy Grounds: Review and New Insights
    Authors: Khandouzi, G., Khosravi, M.H.
    Year: 2024
    Citations: 2
  • Title: Numerical modelling of cohesive-frictional soil behind inclined retaining wall under passive translation mode
    Authors: Sarfaraz, H., Khosravi, M.H., Pipatpongsa, T.
    Year: 2024
    Citations: 0
  • Title: Performance Evaluation of Artificial Neural Networks and Support Vector Regression in Tunneling-Induced Settlement Prediction Incorporating Umbrella Arch Method Characteristics
    Authors: Varjovi, M.A., Rahmanpour, M., Khosravi, M.H., Majdi, A., Le, B.T.
    Year: 2024
    Citations: 1
  • Title: A review on the buried pipeline responses to tunneling-induced ground settlements
    Authors: Mahmoudi, H., Khandouzi, G., Khosravi, M.H.
    Year: 2024
    Citations: 0
  • Title: Mobilization of Cohesion and Friction Angle of Intact Rocks in the Shearing Process
    Authors: Alidaryan, M., Khosravi, M.H., Bahaaddini, M., Moosavi, M., Roshan, H.
    Year: 2023
    Citations: 3
  • Title: An analytical investigation of soil arching induced by tunneling in sandy ground
    Authors: Khandouzi, G., Khosravi, M.H.
    Year: 2023
    Citations: 10
  • Title: Theoretical and Numerical Analysis of Cohesive-Frictional Backfill against Battered Retaining Wall under Active Translation Mode
    Authors: Sarfaraz, H., Khosravi, M.H., Pipatpongsa, T.
    Year: 2023
    Citations: 7

Arash Yazdanpanah Goharrizi | Engineering | Best Innovation Award

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Prof. Arash Yazdanpanah Goharrizi | Engineering | Best Innovation Award

Shahid Beheshti University, Iran

Dr. Arash Yazdanpanah Goharrizi is a distinguished professor in electrical engineering at Shahid Beheshti University, Tehran, Iran. His research focuses on nanotechnology, semiconductor devices, and electronic transport properties, with contributions to optimizing transistor performance, nanoribbon-based sensors, and first-principles calculations of novel materials. He has published extensively in high-impact journals, collaborating with international researchers to advance the field of microelectronics and nanostructures. In addition to research, Dr. Goharrizi actively reviews scientific manuscripts and contributes to academic peer-review processes.

Professional Profile

Education

Dr. Arash Yazdanpanah Goharrizi earned his academic qualifications from Shahid Beheshti University, Tehran, Iran. He initially served as an assistant professor in electrical engineering at the same institution, where he developed expertise in semiconductor physics, nanomaterials, and device modeling. His academic training provided him with a strong foundation in theoretical and applied aspects of electronic devices, paving the way for his contributions to advanced semiconductor research.

Professional Experience

Dr. Goharrizi currently serves as a professor at Shahid Beheshti University, where he leads research in electrical engineering, with a focus on micro- and nanostructures. Over the years, he has conducted groundbreaking studies on electronic and transport properties of advanced materials like phosphorene, antimonene, and germanene. His work has led to numerous publications in esteemed journals such as ACS Applied Electronic Materials, IEEE Transactions on Electron Devices, and Physica E. Beyond research, he contributes to academia through peer reviewing and mentoring graduate students in semiconductor device physics and nanoelectronics.

Research Interests

Dr. Arash Yazdanpanah Goharrizi’s research interests lie in the fields of nanoelectronics, semiconductor devices, and computational materials science. He focuses on the electronic, optical, and transport properties of low-dimensional materials such as phosphorene, antimonene, graphene, and germanene nanoribbons, utilizing first-principles calculations and device modeling to optimize their performance. His studies contribute to advancements in transistor design, Bragg grating-based sensors, and tunneling field-effect transistors (TFETs). Additionally, he explores strain engineering and doping control to enhance device efficiency and scalability. His interdisciplinary research integrates physics, electrical engineering, and material science, aiming to develop next-generation electronic and optoelectronic devices for high-performance computing and sensing applications.

Awards and Honors

Dr. Goharrizi has been recognized for his contributions to semiconductor research and nanoelectronics through various academic and professional honors. His high-impact publications in prestigious journals and collaborations with international researchers reflect his standing in the scientific community. As a peer reviewer for leading journals, he has contributed to the advancement of materials science and electrical engineering. He has also received recognition for his mentorship and guidance of graduate students in advanced semiconductor device research. His work on nanostructured materials and electronic transport properties continues to earn him accolades within the academic and research communities, further establishing his reputation as a leading expert in the field.

Publications Top Noted

  1. Modeling of lightly doped drain and source graphene nanoribbon field effect transistors
    • Authors: M Saremi, M Saremi, H Niazi, AY Goharrizi
    • Journal: Superlattices and Microstructures
    • Year: 2013
    • Citations: 94
  2. Armchair graphene nanoribbon resonant tunneling diodes using antidote and BN doping
    • Authors: AY Goharrizi, M Zoghi, M Saremi
    • Journal: IEEE Transactions on Electron Devices
    • Year: 2016
    • Citations: 93
  3. Band gap tuning of armchair graphene nanoribbons by using antidotes
    • Authors: M Zoghi, AY Goharrizi, M Saremi
    • Journal: Journal of Electronic Materials
    • Year: 2017
    • Citations: 77
  4. A numerical study of line-edge roughness scattering in graphene nanoribbons
    • Authors: A Yazdanpanah, M Pourfath, M Fathipour, H Kosina, S Selberherr
    • Journal: IEEE Transactions on Electron Devices
    • Year: 2011
    • Citations: 71
  5. Device performance of graphene nanoribbon field-effect transistors in the presence of line-edge roughness
    • Authors: AY Goharrizi, M Pourfath, M Fathipour, H Kosina
    • Journal: IEEE Transactions on Electron Devices
    • Year: 2012
    • Citations: 67
  6. Tuning electronic, magnetic, and transport properties of blue phosphorene by substitutional doping: a first-principles study
    • Authors: F Safari, M Fathipour, A Yazdanpanah Goharrizi
    • Journal: Journal of Computational Electronics
    • Year: 2018
    • Citations: 44
  7. An analytical model for line-edge roughness limited mobility of graphene nanoribbons
    • Authors: AY Goharrizi, M Pourfath, M Fathipour, H Kosina, S Selberherr
    • Journal: IEEE Transactions on Electron Devices
    • Year: 2011
    • Citations: 41
  8. SOI LDMOSFET with up and down extended stepped drift region
    • Authors: M Saremi, M Saremi, H Niazi, M Saremi, AY Goharrizi
    • Journal: Journal of Electronic Materials
    • Year: 2017
    • Citations: 40
  9. A new method for classification and identification of complex fiber Bragg grating using the genetic algorithm
    • Authors: A Rostami, A Yazdanpanah-Goharriz
    • Journal: Progress In Electromagnetics Research
    • Year: 2007
    • Citations: 31
  10. Strain-induced armchair graphene nanoribbon resonant-tunneling diodes
  • Authors: M Zoghi, AY Goharrizi
  • Journal: IEEE Transactions on Electron Devices
  • Year: 2017
  • Citations: 30

Miroslav Kelemen | Engineering | Best Researcher Award

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Prof. Dr. Miroslav Kelemen | Engineering | Best Researcher Award

Vice-Rector for Education at TECHNICAL UNIVERSITY OF KOSICE, FACULTY OF AERONAUTICS , Slovakia

Miroslav Kelemen is an experienced aviation professional with over 22 years of expertise as a pilot, flight instructor, and air traffic controller. With a solid background in managerial roles, including his time as an Air Force Base Commander, Kelemen has developed a deep understanding of aviation education, flight training, aeronautical engineering, and air transport systems. His research interests encompass interdisciplinary topics such as decision-making processes, risk assessment, human performance, and safety in transportation. He has also contributed to studies on the impact of aviation activities on the environment and health, small and medium enterprises in transport and tourism, and innovations in aviation education. Kelemen holds key academic positions, including Vice-Rector for Education at the Technical University of Košice, where he continues to shape the future of aviation education.

Professional Profile

Education

Kelemen’s educational journey is distinguished by numerous advanced degrees and specialized training. He holds a DrSc. from Slovenská komisia pre vedecké hodnosti, Bratislava, and a Ph.D. from the Air Force Academy Košice in flight training. Additionally, Kelemen obtained his Associate Professorship at the University of Žilina, Slovakia. His academic qualifications are complemented by his professorship at the Academy of the Police Force in Bratislava, focusing on public administration and crisis management. His rigorous education laid the foundation for his multifaceted expertise in aviation, air transport, and safety, influencing both academic curricula and industry standards.

Professional Experience

Kelemen’s professional experience spans across various roles in aviation and academia. Since 2018, he has served as a Professor at the Faculty of Aeronautics, Technical University of Košice, where he specializes in flight training. In August 2023, he became the Vice-Rector for Education at the university, overseeing educational reforms and initiatives. Kelemen’s previous leadership role as an Air Force Base Commander allowed him to hone his managerial skills in high-pressure environments. His career also includes significant work in air traffic control, aviation safety, and flight training, contributing to both military and civil aviation sectors.

Research Interests

Miroslav Kelemen’s research interests are broad and interdisciplinary, with a strong focus on aviation education, flight training, and air transport systems. His work delves into decision-making processes, risk assessment, and human performance in transportation, particularly in aviation. He is deeply invested in understanding the environmental and health impacts of aviation activities, exploring sustainable practices and innovations in aviation. Kelemen also studies small and medium enterprises in transport, logistics, and tourism, with an emphasis on their role in economic development. His research is grounded in applying advanced methodologies, including fuzzy decision support models and artificial intelligence, to address complex challenges in aviation and related fields. Through these studies, Kelemen contributes to the improvement of aviation safety, security, and overall operational efficiency.

Awards and Honors

Throughout his career, Miroslav Kelemen has received numerous accolades for his academic and professional contributions to aviation and transport. He has been recognized for his pioneering work in flight training, risk assessment, and aviation education, earning him a reputation as a leader in these fields. His involvement in interdisciplinary research has garnered recognition from various academic and industry bodies. Kelemen’s achievements extend beyond the classroom, with contributions to publications in respected journals and books, further solidifying his influence in academia. His expertise in aviation safety and the impact of aviation on human health and the environment has earned him prestigious awards and honors, reflecting his commitment to advancing both the academic and practical aspects of aviation.

Publications Top Noted

  • A fuzzy model of risk assessment for environmental start-up projects in the air transport sector
    Authors: V. Polishchuk, M. Kelemen, B. Gavurová, C. Varotsos, R. Andoga, M. Gera, …
    Year: 2019
    Citation Count: 76
  • Fuzzy model for quantitative assessment of environmental start-up projects in air transport
    Authors: M. Kelemen, V. Polishchuk, B. Gavurová, S. Szabo, R. Rozenberg, M. Gera, …
    Year: 2019
    Citation Count: 67
  • Expert model of risk assessment for the selected components of smart city concept: From safe time to pandemics as COVID-19
    Authors: B. Gavurova, M. Kelemen, V. Polishchuk
    Year: 2022
    Citation Count: 59
  • The suitability of UAS for mass movement monitoring caused by Torrential Rainfall—A study on the Talus Cones in the Alpine Terrain in High Tatras, Slovakia
    Authors: R. Urban, M. Štroner, P. Blistan, Ľ. Kovanič, M. Patera, S. Jacko, I. Ďuriška, …
    Year: 2019
    Citation Count: 53
  • Monitoring of low-level wind shear by ground-based 3D lidar for increased flight safety, protection of human lives and health
    Authors: P. Nechaj, L. Gaál, J. Bartok, O. Vorobyeva, M. Gera, M. Kelemen, …
    Year: 2019
    Citation Count: 46
  • Patterns of interdependence between financial development, fiscal instruments, and environmental degradation in developed and converging EU countries
    Authors: M. Zioło, K. Kluza, J. Kozuba, M. Kelemen, P. Niedzielski, P. Zinczak
    Year: 2020
    Citation Count: 36
  • Technology improving safety of crowdfunding platforms functioning in the context of the protection of the start-up investors in the financial and transport sectors
    Authors: V. Polishchuk, M. Kelemen, J. Kozuba
    Year: 2019
    Citation Count: 30
  • Enhancing of security on critical accident locations using telematics support
    Authors: R. Dvorak, Z. Cekerevac, Z. Kelemen, M. Sousek
    Year: 2010
    Citation Count: 30
  • Security Management Education and Training of Critical Infrastructure Sectors’ Experts
    Authors: M. Kelemen, J. Jevčák
    Year: 2018
    Citation Count: 29
  • Assessing the contribution of data mining methods to avoid aircraft run-off from the runway to increase the safety and reduce the negative environmental impacts
    Authors: O. Vorobyeva, J. Bartok, P. Šišan, P. Nechaj, M. Gera, M. Kelemen, …
    Year: 2020
    Citation Count: 28

Prof. Dr. Gholamreza Asadollahfardi | Engineering | Best Paper Award

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Prof. Dr. Gholamreza Asadollahfardi | Engineering | Best Paper Award

Professor at Kharazmi University, Iran

Prof. Dr. Gholamreza Asadollahfardi is an Emeritus Professor in Environmental Engineering at Kharazmi University, Tehran, Iran, with a distinguished academic and professional career. He holds a Ph.D. in Environmental Engineering from London University, UK, and has extensive experience in water quality monitoring, wastewater treatment, environmental impact assessment, and sustainable construction practices. Dr. Asadollahfardi has contributed significantly to numerous research projects, including water quality analysis, soil remediation modeling, and the application of artificial neural networks in environmental engineering. He has published over 100 journal papers, showcasing his expertise in environmental sustainability and green technologies. In addition to his academic achievements, Dr. Asadollahfardi has worked as an environmental consultant and served in various academic positions, including guest professorships at the University of British Columbia. His research continues to impact the fields of environmental engineering, sustainable construction, and water resource management globally.

Professional Profile 

Education

Prof. Dr. Gholamreza Asadollahfardi completed his higher education with a strong focus on environmental engineering. He earned his Bachelor’s degree in Civil Engineering from Sharif University of Technology in Tehran, Iran, followed by a Master’s degree in Environmental Engineering from the same institution. His academic journey reached its pinnacle with a Ph.D. in Environmental Engineering from London University, UK. During his doctoral studies, Dr. Asadollahfardi specialized in water quality monitoring and sustainable engineering practices, which laid the foundation for his long and successful career in academia and research. His extensive education in environmental engineering equipped him with the necessary skills to address complex challenges in water treatment, wastewater management, and sustainable construction. Through his rigorous academic background, Dr. Asadollahfardi has contributed significantly to the development of sustainable technologies and practices in the field of environmental engineering, both in Iran and internationally.

Professional Experience

Prof. Dr. Gholamreza Asadollahfardi has an extensive and distinguished professional career in environmental engineering, contributing significantly to both academia and industry. He has held various academic positions, including faculty roles at prestigious universities in Iran, where he has taught and mentored numerous students. Throughout his career, he has been involved in cutting-edge research in the areas of water treatment, wastewater management, and sustainable engineering solutions. Dr. Asadollahfardi has also worked as a consultant for various governmental and non-governmental organizations, advising on environmental impact assessments, water resource management, and policy development. His expertise has led to collaborations with international research teams and institutions. As a recognized leader in his field, he has published extensively in peer-reviewed journals and participated in various environmental engineering conferences worldwide. Prof. Dr. Asadollahfardi continues to influence the field through his academic teachings, research projects, and contributions to sustainable development practices.

Research Interest

Prof. Dr. Gholamreza Asadollahfardi’s research interests focus on environmental engineering, with a particular emphasis on water treatment, wastewater management, and sustainable resource management. He is dedicated to developing innovative technologies and strategies for improving water quality, addressing pollution challenges, and promoting environmental sustainability. His work explores advanced treatment methods for industrial effluents, the use of renewable energy in wastewater treatment, and the development of efficient systems for managing water resources. Dr. Asadollahfardi is also deeply involved in studying the environmental impacts of various industries and developing solutions to mitigate these effects. His research extends to the modeling and optimization of water treatment processes, aiming to enhance efficiency while minimizing costs and environmental harm. Additionally, he is interested in the application of nanotechnology and bioengineering in environmental management. His interdisciplinary approach contributes to both the scientific community and practical applications in improving environmental sustainability.

Award and Honor

Prof. Dr. Gholamreza Asadollahfardi has received numerous awards and honors throughout his career, recognizing his outstanding contributions to environmental engineering and water treatment research. His innovative work in wastewater management and sustainable resource development has earned him prestigious accolades, both nationally and internationally. Among his notable honors are several research excellence awards from renowned academic institutions, reflecting his significant impact in the field of environmental science. Additionally, he has been recognized for his leadership in advancing water treatment technologies and his efforts to address global environmental challenges. Dr. Asadollahfardi has also been invited to serve on the editorial boards of prominent environmental engineering journals, further cementing his reputation as a leading expert in the field. His dedication to research, teaching, and sustainable environmental solutions has made him a respected figure in both academic and professional circles, earning him widespread recognition for his academic achievements and contributions to the betterment of society.

Conclusion

Gholamreza Asadollahfardi’s career demonstrates exemplary contributions to environmental engineering, particularly in water resources, waste management, and sustainable construction. His substantial publication record and high citation count underscore his research’s academic value. Asadollahfardi’s ability to apply advanced modeling techniques and focus on sustainability makes him an outstanding candidate for the Best Paper Award. However, to further elevate his impact, a stronger focus on interdisciplinary research, practical implementation of his findings, and expansion into emerging global challenges could enhance his already impressive body of work. Overall, his academic achievements and research innovations make him highly deserving of this prestigious award.

Publications Top Noted

  • Title: Use of treated domestic wastewater before chlorination to produce and cure concrete
    Authors: G Asadollahfardi, M Delnavaz, V Rashnoiee, N Ghonabadi
    Year: 2016
    Citations: 127
  • Title: Experimental and statistical studies of using wash water from ready-mix concrete trucks and a batching plant in the production of fresh concrete
    Authors: Gholamreza Asadollahfardi, Mohsen Asadi, Hamidreza Jafari
    Year: 2015
    Citations: 117
  • Title: Investigation of cadmium absorption and accumulation in different parts of some vegetables
    Authors: B Yargholi, AA Azimi, A Baghvand, AM Liaghat, GA Fardi
    Year: 2008
    Citations: 104
  • Title: Evaluating and improving the construction and demolition waste technical properties to use in road construction
    Authors: G Tavkoli Mehrjardi, Gholamhosien, Azizi, Alireza, Haji-aziz, Amanj …
    Year: 2020
    Citations: 91
  • Title: The Influence of Safety Training on Safety Climate Factors in a Construction Site
    Authors: GRAF MOHAMMAD JAVAD JAFARI, MEHDI GHARARI, MOHTASHAM GHAFARI, LEILA OMIDI …
    Year: 2014
    Citations: 83
  • Title: Application of Artificial Neural Network to Predict TDS in Talkheh Rud River
    Authors: G Asadollahfardi, A Taklify, A Ghanbari
    Year: 2012
    Citations: 81
  • Title: The feasibility of using treated industrial wastewater to produce concrete
    Authors: G Asadollahfardi, AR Mahdavi
    Year: 2019
    Citations: 71
  • Title: The difference in chloride ion diffusion coefficient of concrete made with drinking water and wastewater
    Authors: MS Hassani, G Asadollahfardi, SF Saghravani, S Jafari, …
    Year: 2020
    Citations: 61
  • Title: Environmental life cycle assessment of concrete with different mixed designs
    Authors: G Asadollahfardi, A Katebi, P Taherian, A Panahandeh
    Year: 2021
    Citations: 57
  • Title: The effects of using treated wastewater on the fracture toughness of the concrete
    Authors: FS Peighambarzadeh, G Asadollahfardi, J Akbardoost
    Year: 2020
    Citations: 52
  • Title: The influence of safety training on improvement in safety climate in construction sites of a firm
    Authors: Mohammad Javad Jafari, Mehdi Ghafari, Saba Kalantari, Leila Omidi, Mohtasham Ghafari, …
    Year: 2015
    Citations: 52
  • Title: Comparison of different extracting agents for the recovery of Pb and Zn through electrokinetic remediation of mine tailings
    Authors: G Asadollahfardi, MS Sarmadi, M Rezaee, A Khodadadi-Darban, …
    Year: 2021
    Citations: 51

Tharindu Madhushanka | Engineering | Best Researcher Award

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Mr. Tharindu Madhushanka | Engineering | Best Researcher Award

Engineer at Browns Engineering and Construction, Sri Lanka

Mr. Tharindu Indunil Madhushanka is a promising researcher and civil engineering professional from the University of Moratuwa, Sri Lanka. He holds a Master of Science in Civil Engineering, with a focus on using artificial intelligence for flood forecasting, specifically in the Polonnaruwa region. His research integrates machine learning techniques such as LSTM, ANN, and Transformer models to predict water levels using meteorological and hydrological data. Tharindu has also contributed to sustainable construction through his undergraduate research on the thermal performance and embodied energy of precast panel buildings. His academic achievements include a GPA of 3.54 in Civil Engineering and notable publications, including a paper in the Journal of Hydrologic Engineering. He has gained hands-on experience in both teaching and industry, having worked as an instructor and research assistant at the University of Moratuwa and a trainee civil engineer. Tharindu is dedicated to advancing AI applications in civil engineering for disaster management and sustainability.

Professional Profile

Education

Mr. Tharindu Indunil Madhushanka has a strong educational background in civil engineering, having completed his Bachelor of Science in Civil Engineering (Honors) from the University of Moratuwa, Sri Lanka, where he graduated with a second-class upper division and a GPA of 3.54 out of 4.2. His undergraduate studies provided him with a solid foundation in engineering principles and practices. He further pursued a Master of Science at the same university, beginning in November 2022, with a research focus on utilizing artificial intelligence to forecast floods, particularly in the Polonnaruwa region of Sri Lanka. Under the guidance of Prof. M.T.R. Jayasinghe, his postgraduate research aims to develop machine learning models for predicting water levels using meteorological and hydrological data. This interdisciplinary approach bridges civil engineering and AI, reflecting his commitment to advancing both fields. His studies are set to culminate in July 2024, contributing valuable insights to flood risk management.

Professional Experience

Mr. Tharindu Indunil Madhushanka has gained valuable professional experience through both academic and industry roles. As a research assistant at the Department of Civil Engineering, University of Moratuwa, he contributed to various engineering modules, including Mechanics, Structural Mechanics, and the Design of Large Structures. His responsibilities included assisting in teaching and providing support for courses such as Building Construction & Materials and Design of Masonry and Timber Structures. Additionally, Tharindu worked as an instructor in the Department of Computer Science Engineering, teaching Programming Fundamentals from June to September 2024. His industry experience includes serving as a trainee civil engineer at RR Construction (Pvt) Ltd, where he was involved in significant projects such as the Mahaweli Water Security Investment Program. These projects, including the Minipe Left Bank Canal Rehabilitation and North-Western Province Canal Project, provided him with hands-on experience in large-scale civil engineering works, enhancing his practical skills.

Research Interest

Mr. Tharindu Indunil Madhushanka’s research interests lie at the intersection of civil engineering and artificial intelligence, with a focus on disaster risk management and sustainable construction. His primary research area is the use of machine learning techniques, particularly deep learning models like LSTM, ANN, and Transformer, to forecast floods and predict water levels in flood-prone regions, such as Polonnaruwa, Sri Lanka. By utilizing meteorological and hydrological data, Tharindu aims to enhance flood prediction systems, providing valuable insights for mitigating the impacts of natural disasters. Additionally, he is interested in sustainable building practices, as demonstrated by his undergraduate research on the thermal performance and embodied energy of precast panel buildings. Tharindu’s work seeks to improve the environmental efficiency of construction materials and methods, making buildings more energy-efficient over their life cycles. His research reflects his commitment to advancing both AI applications and sustainability within the civil engineering field.

Award and Honor

Mr. Tharindu Indunil Madhushanka has achieved notable academic recognition throughout his educational journey. He graduated with a second-class upper division in his Bachelor of Science in Civil Engineering (Honors) from the University of Moratuwa, Sri Lanka, with a commendable GPA of 3.54 out of 4.2. This achievement underscores his strong academic performance and dedication to his studies. Tharindu has also earned recognition for his research contributions, particularly in the field of flood forecasting using artificial intelligence. His publication, “Multiple-Day-Ahead Flood Prediction in the South Asian Tropical Zone Using Deep Learning,” in the Journal of Hydrologic Engineering, demonstrates the impact of his work on flood management. Although his H-index is currently 1, it reflects his emerging influence in the research community. Tharindu’s research on sustainable building practices, including the thermal performance of precast panel buildings, has been presented at international conferences, further highlighting his growing recognition within the civil engineering and AI research communities.

Conclusion

Tharindu Indunil Madhushanka demonstrates a strong foundation in innovative, interdisciplinary research, particularly in leveraging artificial intelligence for flood forecasting and sustainable building practices. His academic achievements, technical expertise, and impactful research in disaster management are highly commendable.

Publications Top Noted

  • Title: Multi Day Ahead Flood Prediction in South Asian Tropical Zone Using Deep Learning
    Authors: T Madhushanka, T Jayasinghe, R Rajapakse
    Year: 2024
    Cited by: 1
  • Title: Multiple-Day-Ahead Flood Prediction in the South Asian Tropical Zone Using Deep Learning
    Authors: G Madhushanka, MTR Jayasinghe, RA Rajapakse
    Journal: Journal of Hydrologic Engineering 30 (1), 04024054
    Year: 2025
    Cited by: Not available
  • Title: Behavior of LSTM and Transformer Deep Learning Models in Flood Simulation Considering South Asian Tropical Climate
    Authors: G Madhushanka, MTR Jayasinghe, RA Rajapakse
    Year: 2024
    Cited by: Not available
  • Title: Transformer & LSTM Based Models for Multi-Day Ahead Flood Prediction in Tropical Climates
    Authors: T Madhushanka, T Jayasinghe, R Rajapakse
    Year: 2024
    Cited by: Not available
    Available at: SSRN 4746297
  • Title: Flood Prediction for Tropical Climates Using LSTM and Transformer Machine Learning Models
    Authors: T Madhushanka, T Jayasinghe, R Rajapakse
    Year: 2024
    Cited by: Not available
    Available at: SSRN 4736261
  • Title: LONG SHORT-TERM MEMORY (LSTM) & FEEDFORWARD ARTIFICIAL NEURAL NETWORK (ANN) FOR FLOOD PREDICTION
    Authors: G.W.T.I. Madhushanka, M.T.R. Jayasinghe, R.A. Rajapakse
    Event: Proceedings of the 14th International Conference on Sustainable Built …
    Year: 2023
    Cited by: Not available
  • Title: Thermal Performance of Precast Panel Buildings
    Authors: G Madhushanka, SS Bandaranayaka, MTR Jayasinghe, H Herath
    Event: University of Ruhuna
    Year: 2023
    Cited by: Not available

Xiaotian Wang | Engineering Award | Excellence in Research

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Mr. Xiaotian Wang | Engineering Award | Excellence in Research

Associate Professor at Northwestern Polytechnical University, China

Xiaotian Wang, an Associate Professor at Northwestern Polytechnical University, holds both a Master’s and a Ph.D. degree, earned in 2016 and 2020, respectively, from the same institution. His academic background and current position within a renowned university are strong indicators of his expertise and commitment to research. His specialized focus on computer vision and remote sensing image processing, particularly in object detection and tracking, aligns with cutting-edge technological advancements in these fields. Wang’s contributions to unmanned systems research further highlight his alignment with contemporary research trends and his potential to lead innovative projects.

Professional Profile

Education

Dr. Xiaotian Wang completed his Master’s degree and Ph.D. in the field of Computer Vision and Remote Sensing from Northwestern Polytechnical University, Xi’an, China. He earned his Master’s in 2016 and his Ph.D. in 2020, both from the same prestigious institution. Throughout his education, Dr. Wang developed a deep understanding of machine learning, artificial intelligence, and their applications in unmanned systems. His academic journey involved rigorous research in object detection and tracking algorithms, which he continued to develop through various academic and practical projects. His research contributions were shaped by the rigorous training and mentorship he received during his graduate studies. Dr. Wang’s education provided him with a strong theoretical foundation and the technical expertise necessary to conduct pioneering research in remote sensing image processing and computer vision, making him a recognized expert in his field.

Experience

Dr. Xiaotian Wang is currently an Associate Professor at Northwestern Polytechnical University, where he has made significant contributions to research and development in unmanned systems and remote sensing. His primary focus is on computer vision, particularly object detection and tracking technologies that have important applications in surveillance, robotics, and unmanned vehicles. Prior to his current position, Dr. Wang has been actively involved in several key research projects, collaborating with national and international researchers in the development of cutting-edge technologies for unmanned systems. His expertise in integrating computer vision algorithms with remote sensing has led to several innovative solutions in the field. Additionally, he actively mentors graduate students and early-career researchers, guiding them in advancing their knowledge and research skills in these high-tech domains. His academic and research experience provides a foundation for developing practical, scalable solutions in remote sensing and unmanned technologies.

Research Focus

Dr. Xiaotian Wang’s research primarily revolves around computer vision and remote sensing image processing, with a particular emphasis on object detection and tracking technologies. His work has a significant focus on unmanned systems, where he explores innovative approaches for navigating and processing data from remote sensing devices. Dr. Wang’s research aims to enhance the capabilities of unmanned vehicles, such as drones, through improved object detection and tracking algorithms that enable these systems to interpret and respond to their environments autonomously. This work is crucial for applications in fields like autonomous vehicles, surveillance, and environmental monitoring. By advancing the integration of computer vision with remote sensing, Dr. Wang seeks to bridge the gap between real-time decision-making and automated systems. His research plays a key role in advancing the field of unmanned systems, which are becoming increasingly vital in many industries, including defense, transportation, and agriculture.

Conclusion

Xiaotian Wang demonstrates a strong research profile with a clear focus on advancing unmanned systems and remote sensing technology, which are highly relevant to both scientific and practical applications. His academic and research contributions make him an excellent candidate for the Excellence in Research Award.

Publications Top Noted

Cross-Attention-Driven Adaptive Graph Relational Network for Multilabel Remote Sensing Scene Classification”

Authors: Bi, H., Chang, H., Wang, X., Hong, D.

Citations: 0

Year: 2024

Journal: IEEE Transactions on Geoscience and Remote Sensing

Volume: 62

Article ID: 5224414

“Complexity Evaluation of Aerial Infrared Countermeasure Scenes”

Authors: Xie, F., Dong, M., Wang, X., Yang, D., Yan, J.

Citations: 0

Year: 2024

Journal: IEEE Transactions on Aerospace and Electronic Systems

“Can Rumor Detection Enhance Fact Verification? Unraveling Cross-Task Synergies Between Rumor Detection and Fact Verification”

Authors: Jin, W., Jiang, M., Tao, T., Zhao, B., Yang, G.

Citations: 0

Year: 2024

Journal: IEEE Transactions on Big Data

“A Research on Rapid Assessment of Cross-Domain Perceptual Fidelity for Practical Applications”

Authors: Tao, W., Wang, X., Yan, T., Zeng, Q., Lu, R.

Citations: 0

Year: 2024

Conference: Proceedings of the 3rd Conference on Fully Actuated System Theory and Applications (FASTA 2024)

“An Improved Small Infrared Target Detection Algorithm Based on Yolov5”

Authors: Wang, X., Yang, Z., Sun, Y., Qian, C., Zhao, Y.

Citations: 0

Year: 2024

Conference: Lecture Notes in Electrical Engineering (LNEE), 1175, pp. 405–413

“Detection of Occlusion-Resistant Based on Improved YOLOv7”

Authors: Tao, W., Wang, K., Li, Y., Yan, T., Wang, X.

Citations: 0

Year: 2024

Conference: Lecture Notes in Electrical Engineering (LNEE), 1173, pp. 430–439

“ESF-YOLO: an accurate and universal object detector based on neural networks”

Authors: Tao, W., Wang, X., Yan, T., Liu, Z., Wan, S.

Citations: 0

Year: 2024

Journal: Frontiers in Neuroscience

Volume: 18

Article ID: 1371418

“An Infrared Small Target Detection Method Based on Attention Mechanism”

Authors: Wang, X., Lu, R., Bi, H., Li, Y.

Citations: 3

Year: 2023

Journal: Sensors (Basel, Switzerland)

Volume: 23

Issue: 20

“SiamCAR-Kal: anti-occlusion tracking algorithm for infrared ground targets based on SiamCAR and Kalman filter”

Authors: Fu, G., Zhang, K., Yang, X., Tian, X., Wang, X.T.

Citations: 0

Year: 2023

Journal: Machine Vision and Applications

Volume: 34

Issue: 3

Article ID: 43

“Robust small infrared target detection using multi-scale contrast fuzzy discriminant segmentation”

Authors: Wang, X., Xie, F., Liu, W., Tang, S., Yan, J.

Citations: 5

Year: 2023

Journal: Expert Systems with Applications

Volume: 212

Article ID: 118813

 

 

Xu Zhang | Engineering Award | Best Scholar Award

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Dr. Xu Zhang | Engineering Award | Best Scholar Award

Associate professor at Hubei University of Technology, China

Xu Zhang is a distinguished scholar specializing in intelligent non-destructive testing (NDT) technologies. With a solid academic foundation in Acoustics, her expertise spans sensor design, guided wave testing, and the integration of artificial intelligence in NDT systems. Zhang has been the principal investigator on several prestigious projects, including National Natural Science Foundation of China and National Key Research and Development Plan projects. She has made significant contributions to the fields of electromagnetic acoustic transducers (EMATs), guided wave detection methods, and corrosion imaging. Her research is not only innovative but also highly relevant to critical industries such as aerospace, automotive, and infrastructure.

Professional Profile

Education

Xu Zhang’s academic journey began with a Bachelor’s degree in Acoustics from Nanjing University in 2010. She furthered her education with a Master’s and PhD in Acoustics from the prestigious Chinese Academy of Sciences, where she honed her research focus on non-destructive testing technologies. In 2016, she became an Associate Professor in the Department of Mechanical Engineering at Hubei University of Technology. Xu is currently a Visiting Fellow at the University of Bristol, where she collaborates with global experts on advanced NDT methods. Her academic background has equipped her with a deep understanding of the complexities in material testing, structural health monitoring, and the application of electromagnetic and ultrasonic technologies in engineering.

Experience

Xu Zhang has extensive experience in the field of non-destructive testing and advanced materials inspection. Since 2016, she has served as an Associate Professor at Hubei University of Technology, specializing in intelligent NDT technologies. Zhang has been the Principal Investigator (PI) in numerous high-profile national and provincial projects, focusing on ultrasonic and electromagnetic testing techniques for stress corrosion cracking and high-temperature creep materials. Notable projects she has led include the development of an ultrasonic phased array detection system for automotive steering parts and the creation of technology for pipeline corrosion imaging. Her expertise spans sensor design, guided wave testing, and the integration of artificial intelligence into NDT systems. Zhang is also a Senior Member of the Chinese Mechanical Engineering Society and an active participant in global research discussions on intelligent testing methodologies.

Research Focus

Xu Zhang’s research is primarily focused on intelligent non-destructive testing (NDT) technologies, with a specific emphasis on ultrasonic and electromagnetic guided wave techniques. She is dedicated to the development of advanced sensor systems and diagnostic tools that can detect flaws and assess material integrity in complex engineering structures. One of her key areas of research is the integration of artificial intelligence into NDT methodologies, enabling more efficient and accurate defect detection. Zhang’s work has applications in diverse industries, including automotive, aerospace, and infrastructure, particularly in stress corrosion cracking detection, high-temperature material assessment, and pipeline monitoring. Additionally, her research explores the enhancement of testing systems with electromagnetic transducers and phased array technologies, which improve detection sensitivity and system reliability. Her contributions to NDT technology continue to shape the future of materials testing and structural health monitoring.

Awards and Honors

Xu Zhang has been recognized for her pioneering work in non-destructive testing, particularly in the application of electromagnetic and ultrasonic guided wave technologies. As a Principal Investigator (PI), she has secured several prestigious grants and awards, including the National Key Research and Development Plan Project and the National Natural Science Foundation of China Project. Her research on stress corrosion cracking detection, material assessment, and corrosion imaging has earned her numerous accolades. Zhang has also been honored with key research project leadership positions from the Provincial Science and Technology Department, reflecting her influence in advancing the state of engineering diagnostics. She continues to contribute to the scientific community, and her work in non-destructive testing systems is frequently recognized for its practical applications in the fields of materials science and engineering.

Conclusion

Xu Zhang is a leading figure in the field of intelligent non-destructive testing, with an impressive array of research accomplishments and leadership in cutting-edge projects. Her scholarly work in the development of advanced testing systems and her commitment to pushing the boundaries of engineering innovation make her an outstanding candidate for the Best Scholar Award. With a strong foundation in both academic research and practical applications, Zhang’s continued contributions to the field hold the promise of significant advancements in industrial safety and technology.

Publications Top Noted

A novel amplitude enhancement method of EMAT for High-frequency Rayleigh-like waves in Circumferential propagation

Authors: Zhang, X., Li, B., Niu, X., Song, X., Wu, Q.

Citations: 0

Year: 2024

Journal: NDT and E International, 148, 103231

Investigation of an Active Focusing Planar Piezoelectric Ultrasonic Transducer

Authors: Wu, Q., You, B., Zhang, X., Tu, J.

Citations: 0

Year: 2024

Journal: Sensors, 24(13), 4082

Characterization of Small Delamination Defects by Multilayer Flexible EMAT

Authors: Chen, T., Liu, S., Lv, C., Wu, Q., Zhang, X.

Citations: 1

Year: 2024

Journal: IEEE Sensors Journal, 24(12), pp. 19210–19219

Unidirectional focusing Rayleigh waves EMAT for plate surface defect Inspection

Authors: Chen, T., Lou, T., Lv, C., Wu, Q., Zhang, X.

Citations: 0

Year: 2024

Journal: Nondestructive Testing and Evaluation (Article in Press)

Design and experimental study of electromagnetic ultrasonic single-mode guided wave transducer for small-diameter stainless steel tubes

Authors: Tu, J., Zhan, X., Sun, H., Zhang, X., Song, X.

Citations: 3

Year: 2024

Journal: Nondestructive Testing and Evaluation (Article in Press)

Internal and External Pipe Defect Characterization via High-Frequency Lamb Waves Generated by Unidirectional EMAT

Authors: Zhang, X., Li, B., Zhang, X., Yuan, J., Wu, Q.

Citations: 3

Year: 2023

Journal: Sensors (Basel, Switzerland), 23(21)

Bolt Axial Stress Measurement Based on the Dual-Mode Electromagnetic Acoustic Transducer

Authors: Zhang, X., Li, W., Wu, Q., Cai, C., Song, X.

Citations: 2

Year: 2023

Journal: IEEE Sensors Journal, 23(13), pp. 13978–13986

Energy Transfer Efficiency Based Nonlinear Ultrasonic Testing Technique for Debonding Defects of Aluminum Alloy Foam Sandwich Panels

Authors: Tu, J., Yao, N., Ling, Y., Zhang, X., Song, X.

Citations: 0

Year: 2023

Journal: Sensors, 23(6), 3008

Optimized Design of Torsional Guided Wave Magnetostrictive Patch Transducer Based on Reversed Wiedemann Effect

Authors: Li, C., Yang, R., Gu, J., Wang, S., Zhang, X.

Citations: 5

Year: 2023

Journal: Journal of Nondestructive Evaluation, 42(1), 26

Enhancing the Lift-Off Performance of EMATs by Applying an Fe3O4 Coating to a Test Specimen

Authors: Liang, B., Li, Z., Zhai, G., Zhang, X., Dixon, S.

Citations: 5

Year: 2023

Journal: IEEE Transactions on Instrumentation and Measurement, 72, 9502104