Hwasun Park | Engineering | Best Researcher Award

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Prof. Hwasun Park | Engineering | Best Researcher Award

 An Industry-Academic Professor | Sungkyunkwan University | South Korea 

Prof. Hwasun Park is an Industry-Academic Professor at the School of Advanced Materials Science and Engineering, Sungkyunkwan University (SKKU), South Korea, where he leads cutting-edge research in semiconductor packaging and advanced materials processing. He earned his Ph.D. in Materials Science and Engineering from Sungkyunkwan University, building a strong foundation in thin-film and electronic materials that bridge academic innovation and industrial application. Prior to his current academic appointment, Prof. Park accumulated extensive professional experience at the Samsung Electro-Mechanics Central Research Institute, where he led several R&D initiatives in packaging materials and process development, and at the CUOS Center, University of Michigan, enhancing his global collaboration and research insight. His primary research interests include microbump materials and processes, embedded printed circuit boards (PCBs) for semiconductor integration, thin-film technologies for high-frequency applications, anisotropic etching mechanisms using electrostatic phenomena, and optical packaging technologies for 2.5D data-center systems. Prof. Park’s research skills encompass semiconductor process optimization, materials characterization, high-frequency electrical analysis, and integration of optical and electronic components. He has published influential work in IEEE and Scopus-indexed journals, contributing to both the academic and industrial advancement of semiconductor technology. His dedication to innovation and collaboration has earned him recognition for excellence in research and technology transfer, fostering productive ties between academia and industry. Prof. Park actively mentors students, participates in joint research programs, and holds memberships in leading professional organizations such as IEEE and materials-science societies. In conclusion, Prof. Hwasun Park exemplifies a scholar-engineer who bridges theory and practice; his pioneering work in semiconductor materials, international collaborations, and commitment to nurturing future scientists position him as a leader driving technological innovation and sustainable growth in the global semiconductor field. 5 Citations | 1 Document | 1 h-index

Profiles: Scopus | ResearchGate

Featured Publications

  • Oh, P. C., Koh, K. K., Kim, J. H., Kim, S. J., & Park, H. (2014). Life-threatening severe hyperkalemia presenting typical electrocardiographic changes—Rapid recovery following medical, temporary pacing, and hemodialysis treatments. November 2014. Citations: 5

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

 

Babatunde Ogunbayo | Engineering | Best Researcher Award

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Mr. Babatunde Ogunbayo | Engineering | Best Researcher Award

Research Student at aof Engineering and Built Environment, University of Johannesburg, South Africa

Mr. Babatunde Ogunbayo is an accomplished professional specializing in Quantity Surveying and Construction Management with a robust academic and industry background. His expertise spans project cost management, budgeting, contract administration, and construction project planning, making him an essential contributor to his field. Known for his analytical approach, Ogunbayo has played key roles in various construction projects, ensuring efficient resource allocation and cost control. He is also actively engaged in academia, providing guidance to students and participating in research to advance construction management practices. Through his work, he bridges the gap between theory and practice, enabling future industry professionals to gain insights grounded in real-world applications. Mr. Ogunbayo’s contributions, marked by a strong commitment to quality and precision, have positioned him as a respected figure in the field, impacting both industry standards and educational practices in construction management.

Professional Profile

Education

Mr. Babatunde Ogunbayo has a strong academic foundation in Quantity Surveying and Construction Management, which underpins his expertise and professional contributions. His educational journey includes advanced studies in these fields, equipping him with critical skills in cost estimation, budgeting, and contract management. Through rigorous training, he has developed a keen analytical perspective essential for project planning and resource allocation. His academic qualifications not only reflect his commitment to excellence but also support his active involvement in research and teaching, where he imparts valuable knowledge to emerging professionals in construction management. Mr. Ogunbayo’s educational background aligns seamlessly with his hands-on experience, allowing him to effectively bridge theoretical concepts with practical applications. This blend of education and practical experience makes him a knowledgeable resource in Quantity Surveying, enabling him to uphold high standards of precision and efficiency in his field.

Professional Experience

Mr. Babatunde Ogunbayo brings extensive professional experience in Quantity Surveying and Construction Management, marked by his roles in cost management, budgeting, and contract administration on diverse projects. Known for his expertise in efficient resource allocation and cost control, Ogunbayo has overseen various stages of construction projects, from planning and estimation to project execution and post-completion review. His hands-on approach and attention to detail ensure that projects adhere to budget and quality standards, while his strategic insights contribute to optimizing workflows and minimizing waste. Alongside his industry roles, Ogunbayo is active in academia, where he mentors students and contributes to research in construction management, furthering best practices in the field. His combination of technical skills and project oversight experience has earned him a reputation as a reliable and effective leader in the industry, making a lasting impact on both practical and academic circles in construction management.

Research Interests

Mr. Babatunde Ogunbayo’s research interests center on advancing construction management practices, with a particular focus on cost control, project efficiency, and sustainable building solutions. He is deeply invested in exploring methods to optimize resource allocation and reduce waste, aiming to improve the financial and environmental impact of construction projects. His work emphasizes the integration of innovative cost-estimation models and advanced budgeting techniques, providing frameworks for more accurate financial forecasting in large-scale projects. Additionally, Ogunbayo is interested in sustainable construction, investigating materials and methods that minimize ecological footprints without compromising quality. His research also includes developing strategies for effective contract management and exploring digital tools to streamline project management processes. Through these efforts, Ogunbayo contributes to building industry knowledge, fostering practices that support both economic efficiency and environmental responsibility, and positioning him as a forward-thinking leader in construction research.

Awards and Honors

Mr. Babatunde Ogunbayo has received notable awards and honors that underscore his contributions and commitment to excellence in Quantity Surveying and Construction Management. His accolades highlight both his technical skills and leadership qualities in the field. Recognized for his expertise in cost management, budgeting, and resource optimization, Ogunbayo has been celebrated for his role in enhancing project efficiency and precision in construction practices. His dedication to advancing sustainable and innovative construction solutions has also earned him industry acknowledgment. Additionally, his academic achievements and involvement in mentoring emerging professionals have been commended by his peers, reflecting his influence in both educational and professional circles. These awards underscore Ogunbayo’s impact on construction management, recognizing his contributions to developing high standards in cost control and contract administration, as well as his commitment to fostering growth and knowledge within the industry.

Conclusion

Bamgbose is a strong candidate for the Research for Excellence in Best Researcher Award based on his extensive experience, academic achievements, and contributions to construction management and building technology. His impact on the field is evident through his hands-on project management roles and commitment to industry standards. Addressing areas like research publications and international certifications would further enhance his qualifications and elevate his standing in the competitive landscape for research awards.

Publication Top Noted

  • Title: Inhibiting Factors to the Implementation of Preferential Procurement Policy in the South African Construction Industry
    Authors: Tau, L.J., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 0
  • Title: A Systematic Review of the Applications of AI in a Sustainable Building’s Lifecycle
    Authors: Adewale, B.A., Ene, V.O., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 1
  • Title: Barriers to Building Information Modelling Adoption in Small and Medium Enterprises: Nigerian Construction Industry Perspectives
    Authors: Bamgbose, O.A., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 2
  • Title: A Principal Component Analysis of Corporate Dispositions for Sustainable Building Construction in South Africa
    Authors: Emere, C.E., Aigbavboa, C.O., Oguntona, O.A., Ogunbayo, B.F.
    Year: 2024
    Citations: 0
  • Title: Assessing Monitoring and Evaluation Effectiveness for Projects in the Construction Industry
    Authors: Ogunbayo, B.F., Aigbavboa, C.O., Ahmed, S., Stevens, M.
    Year: 2024
    Citations: 0
  • Title: A Review of Applicable Approaches to Safety Incentive Schemes Design in the Construction Industry
    Authors: Ogundipe, K.E., Aigbavboa, C.O., Ogunbayo, B.F.
    Year: 2024
    Citations: 0
  • Title: Strategies for Successful Monitoring and Evaluation Practices in Construction Projects
    Authors: Ogunbayo, B.F., Ramabodu, M.S., Adewale, B.A., Ogundipe, K.E.
    Year: 2024
    Citations: 0
  • Title: Encumbrances to Social Media Applications in the South African Construction Industry
    Authors: Oguntona, O.A., Ndoda, U., Akinradewo, O., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 0
  • Title: Assessing Current Health and Safety Practices in the Construction Industry in the Fourth Industry Revolution
    Authors: Abina, O.G., Ogunbayo, B.F., Aigbavboa, C.
    Year: 2024
    Citations: 0
  • Title: A Review of Barriers to Safety Incentives Design and Implementation in the Construction Industry
    Authors: Ogundipe, K.E., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 0

Mohammadreza Esmaeilidehkordi | Engineering | Best Researcher Award

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Mr. Mohammadreza Esmaeilidehkordi | Engineering | Best Researcher Award

Author at Isfahan University of Technology, Iran

Mohamadreza Esmaeilidehkordi is an accomplished electrical engineer and researcher with expertise in control systems, machine learning, and nonlinear observation. He has a strong technical background and extensive hands-on experience in control systems and artificial intelligence, which he applies in interdisciplinary research projects. Known for his innovative approach to problem-solving, he has made notable contributions to fields like control system design, tumor detection, and fault detection in industrial systems. With a drive for academic excellence, Mohamadreza has authored impactful research publications and actively seeks to push the boundaries of his field through advanced techniques and new applications.

Professional Profile

Education

Mohamadreza completed his Master’s in Electrical Engineering (Control Systems) at Isfahan University of Technology (IUT), one of Iran’s leading institutions. He achieved a high GPA (3.90/4), with a thesis on “Online Sequential Type-2 Fuzzy Wavelet Extreme Learning Machine” that applied advanced machine learning techniques to nonlinear observer problems. His academic journey began with a Bachelor’s degree in Electrical Engineering from the Islamic Azad University of Najafabad, where he worked on fuzzy systems to control twin rotor systems. His rigorous coursework in neuro-fuzzy networks, adaptive control, and system identification provided a foundation that has deeply informed his research trajectory and professional work.

Professional Experience

Mohamadreza has over five years of professional experience in electrical engineering and research roles. His career began with an internship and later a position as an electrical engineer at Pars Taban Zagros Engineering Technical Company, where he developed and maintained electrical control panels. Concurrently, he served as a teaching and research assistant at IUT, focusing on linear control and fault detection of three-phase motors using fuzzy wavelet algorithms. His project management experience within IUT’s Scientific Association, where he led a fault detection project, speaks to his organizational skills and ability to apply academic research in practical, industrial contexts.

Research Interests

Mohamadreza’s research interests are rooted in control systems, nonlinear control, and artificial intelligence. He is particularly drawn to the integration of machine learning algorithms in control systems, aiming to enhance fault detection accuracy and develop adaptive models for complex systems. His interdisciplinary pursuits have led him to apply AI-driven techniques, such as fuzzy wavelet algorithms, to medical fields like tumor detection, demonstrating the versatility of his expertise. With a focus on real-world applications, he actively explores innovative methods to improve system efficiency and reliability, contributing meaningful advancements to both engineering and health sciences.

Awards and Honors

Throughout his academic and professional journey, Mohamadreza has been recognized for his exceptional aptitude and dedication. Notably, he ranked in the top 0.1% on Iran’s National Graduate Entrance Exam for Electrical Engineering, securing a full-tuition scholarship at IUT. Additionally, he achieved top 0.5% placement in the national exam for his undergraduate program. His academic excellence has been consistently recognized, underscoring his standing as a leading figure among his peers. Complementing his awards, he has also completed high-impact certifications in machine learning and programming, showcasing his commitment to continuous improvement and leadership in his field.

Conclusion

Overall, Mohamadreza Esmaeilidehkordi possesses a robust profile suitable for consideration for the Best Researcher Award. His strong technical foundation, focused research contributions, and dedication to control systems and machine learning applications make him a promising candidate. Addressing areas such as international exposure and language skills could further enhance his standing in future award considerations.

Publication Top Noted

  • Online Sequential Type-2 Fuzzy Wavelet Extreme Learning Machine: A Nonlinear Observer Application
    Authors: M. Esmaeilidehkordi, M. Zekri, I. Izadi, F. Sheikholeslam
    Year: 2024
    Citation: Esmaeilidehkordi, M., Zekri, M., Izadi, I., & Sheikholeslam, F. (2024). Online Sequential Type-2 Fuzzy Wavelet Extreme Learning Machine: A Nonlinear Observer Application. Fuzzy Sets and Systems, 108897.
  • Attention U-net approach in predicting Intensity Modulated Radiation Therapy dose distribution in brain glioma tumor
    Authors: M. Naeemi, M. R. Esmaeili, I. Abedi
    Year: 2023
    Citation: Naeemi, M., Esmaeili, M. R., & Abedi, I. (2023). Attention U-net approach in predicting Intensity Modulated Radiation Therapy dose distribution in brain glioma tumor. arXiv preprint arXiv:2305.07033.
  • Utilizing Armchair and Zigzag Nanoribbons for Improved Detection of So2 Toxicity with Graphene Biosensor
    Authors: M. Ramezani Farani, M. Esmaeilidehkordi, I. Alipourfard, M. Azarian, …
    Year: 2023
    Citation: Ramezani Farani, M., Esmaeilidehkordi, M., Alipourfard, I., Azarian, M., & others. (2023). Utilizing Armchair and Zigzag Nanoribbons for Improved Detection of So2 Toxicity with Graphene Biosensor. Available at SSRN 4852941.
  • Fuzzy Wavelet Online Sequential Extreme Learning Machine Applied as an Observer for Nonlinear Systems
    Authors: [Author names not provided, but should be included]
    Year: [Year not provided, please specify if known]
    Citation: [Citation information not provided, please specify if known].