Tharindu Madhushanka | Engineering | Best Researcher Award

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

Babatunde Ogunbayo | Engineering | Best Researcher Award

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

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].