Geetha | Engineering | Women Researcher Award

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Dr. Geetha | Engineering | Women Researcher Award

Saveetha school of engineering, India

She has worked on various significant projects throughout her academic and professional journey. For her Ph.D. in Power Electronics, she focused on “Investigations on Energy Storage Element Resonant DC to DC Converter.” For her M.E. in Applied Electronics, her project involved the “Design, Simulation, and Synthesis of a High-Performance FFT Processor based on FPGA,” with the objective of designing a real-time FFT processor and simulating and synthesizing it using Xilinx 9.1i and Modelsim for core generation and verification. In her B.E. in Electrical and Electronics Engineering, her project was centered on “Modeling and Simulation of D.C. Motor,” where she aimed to create a dynamic model for a D.C. motor using SIMULINK. She is an active member of several professional bodies, including the ISTE (Life Member), IAENG, IACSIT, and IRED. Additionally, she serves as a research guide, currently mentoring a candidate in the field of Lithium-ion battery cathode chemistry, life cycle, and recycling.

Professional Profile

Education

She completed her Ph.D. in Power Electronics from Bharath University, Chennai, in March 2020, with a CGPA of 8/10, through a part-time mode. She earned her M.E. in Applied Electronics from C. Abdul Hakeem College of Engineering & Technology, affiliated with Anna University, in 2008, graduating with 81% and First Class with Distinction in a full-time program. Prior to that, she obtained her B.E. in Electrical and Electronics Engineering from Vellore Engineering College, affiliated with Madras University, in 2000, with a First Class and 68%. She also completed her Diploma in Electrical and Electronics Engineering (DEEE) from IRT Polytechnic, Bargur, in 1997, with 76.8% and First Class with Distinction. Her academic journey began at Auxilium Girls Higher Secondary School, where she completed her SSLC in 1994 with 79%.

Professional Experience

She is currently working as an Assistant Professor (SG) in the Institute of Electrical and Electronics Engineering and the Department of Cloud Computing at Saveetha School of Engineering, Chennai, since March 26, 2021. Prior to this, she served as an Associate Professor in the Department of Electrical and Electronics Engineering at Ganadipathys Tulsi Engineering College, Vellore, from June 1, 2009, to May 18, 2017. She began her teaching career as a Lecturer at C. Abdul Hakeem College of Engineering & Technology, Melvisharam, from July 2, 2007, to May 15, 2009. She also worked as a Lecturer in the Department of Electrical and Electronics Engineering at Periyar Maniammai College of Technology for Women, Thanjavur, from December 4, 2003, to July 31, 2006, and as a Lecturer in the Department of Electronics and Communication Engineering at GGR College of Engineering, Vellore, from July 1, 2002, to December 2, 2003. Additionally, she worked as a Lecturer in the Department of Electrical and Electronics Engineering at Adhiparasakthi Engineering College, Melmaruvathur, from May 28, 2001, to March 20, 2002.

Research Interests

Her areas of interest include Control Systems, Electrical Machines, Transmission and Distribution, VLSI Signal Processing, Advanced Digital Signal Processing, and Digital Electronics. She is passionate about exploring these fields and continuously advancing her knowledge and expertise in these areas

Publication Top Notes

  • Persistent organic pollutants in water resources: Fate, occurrence, characterization and risk analysis
    • Authors: T Krithiga, S Sathish, AA Renita, D Prabu, S Lokesh, R Geetha, …
    • Year: 2022
    • Citations: 154
  • Current status of microbes involved in the degradation of pharmaceutical and personal care products (PPCPs) pollutants in the aquatic ecosystem
    • Authors: M Narayanan, M El-Sheekh, Y Ma, A Pugazhendhi, D Natarajan, …
    • Year: 2022
    • Citations: 99
  • A novel design of smart and intelligent soldier supportive wireless robot for military operations
    • Authors: C Gnanaprakasam, M Swarna, R Geetha, G Saranya, SM KH
    • Year: 2023
    • Citations: 5
  • CVS-FLN: a novel IoT-IDS model based on metaheuristic feature selection and neural network classification model
    • Authors: R Geetha, A Jegatheesan, RK Dhanaraj, K Vijayalakshmi, A Nayyar, …
    • Year: 2024
    • Citations: 3
  • A Comparative Analysis on the Conventional Methods, Benefits of Recycling the Spent Lithium-ion Batteries with a Special focus on Ultrasonic Delamination
    • Authors: PK Persis, R Geetha
    • Year: 2023
    • Citations: 3
  • Enhanced Criminal Identification through MTCNN: Leveraging Advanced Facial Recognition Technology
    • Authors: R Gowthamani, D Gayathri, R Geetha, S Harish, M Rohini
    • Year: 2024
    • Citations: 1
  • A Legal Prediction Model Using Support Vector Machine and K-Means Clustering Algorithm for Predicting Judgements and Making Decisions
    • Authors: AJM Rani, KS Bharathwaj, NMJ Swaroopan, KH Kumar, R Geetha
    • Year: 2023
    • Citations: 1
  • Efficient Energy Management in Photovoltaic System Using Grid Interconnected Solar System Compared with Battery Energy Storage System by Limiting the Panel Array Losses
    • Authors: BR Subashini, R Geetha
    • Year: 2023
    • Citations: 1
  • Increasing the Power in Photovoltaic Systems using a Floating PV System compared with a Rooftop PV System by Limiting the Temperature Loss
    • Authors: MJ Angelin, R Geetha
    • Year: 2023
    • Citations: 1
  • A Robust Blockchain Assisted Electronic Voting Mechanism with Enhanced Cyber Norms and Precautions
    • Authors: NV Krishnamoorthy, SM KH, C Gnanaprakasam, M Swarna, R Geetha
    • Year: 2023
    • Citations: 1

 

Jameer Kotwal | Engineering | Best Researcher Award

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Dr. Jameer Kotwal | Engineering | Best Researcher Award

Associate Professor at Dr D Y Patil Institute of Technology pimpri, India

Mr. Jameer G. Kotwal is an Assistant Professor at Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, with a career spanning over 14 years in the field of engineering education. He is currently pursuing a Ph.D. and holds a Master’s degree in Computer Engineering. Throughout his career, he has demonstrated remarkable proficiency in subjects related to deep learning, machine learning, CUDA programming, and algorithms. Mr. Kotwal has contributed significantly to academia by mentoring students, guiding projects, and being a part of various committees, including syllabus formation. His dedication to research and innovation is evidenced by his development of cutting-edge systems and products, such as facial recognition-based attendance systems. His work has resulted in multiple patents and copyrights, making him a key player in the technological innovations at his institution. Beyond academics, Mr. Kotwal has been honored with numerous awards, including the Best Teacher Award, and has played an active role in prestigious competitions like Smart India Hackathon.

Professional Profile

Education:

Mr. Jameer G. Kotwal holds a Master’s degree (ME) in Computer Engineering and is currently pursuing a Ph.D. in a related field. His academic journey has been marked by a strong focus on computer science and its application to real-world problems, specifically in machine learning, deep learning, and artificial intelligence. He has consistently pursued advanced coursework and certifications through platforms like NPTEL, Coursera, and Udemy, expanding his expertise. His ongoing doctoral studies further underscore his commitment to expanding knowledge in his field. The combination of practical teaching experience and academic research equips him to handle complex technical problems and contribute meaningfully to the research community. Additionally, his involvement in curriculum development, such as being a syllabus setter for various university courses, reflects his in-depth knowledge and academic rigor.

Professional Experience:

Mr. Kotwal’s professional experience spans over 14 years in the academic sector, primarily as an Assistant Professor. He has worked at several prestigious institutions, including Dr. D.Y. Patil Institute of Technology, Pimpri Chinchwad College of Engineering, and Nutan Maharashtra Institute of Engineering & Technology. His responsibilities have included teaching undergraduate and postgraduate students, guiding research projects, and taking on leadership roles within his department. Notably, he has served as the Department Project Coordinator and has handled various NBA (National Board of Accreditation) criteria. In addition to his teaching duties, Mr. Kotwal has been instrumental in organizing and delivering faculty development programs, mentoring students, and fostering research collaborations. His role in guiding over 50 undergraduate students and providing invaluable mentorship to numerous students in national hackathons has greatly contributed to the academic community.

Research Interest:

Mr. Kotwal’s primary research interests lie in the fields of machine learning, deep learning, artificial intelligence, and their applications in real-world problems. His research has centered on innovative solutions such as plant disease identification using deep learning and the development of advanced systems for facial recognition-based attendance and sign language translation. Additionally, his work on smart expense management systems, touchless attendance systems, and emotion-based intelligent chatbots showcases his focus on integrating AI technologies into everyday applications. Through his research, Mr. Kotwal aims to bridge the gap between theoretical knowledge and practical application, ultimately creating technology that can have a positive societal impact. He is also exploring the intersection of computer science with various industries, including agriculture, healthcare, and education.

Research Skills:

Mr. Kotwal is well-versed in various research methodologies and has honed a diverse set of technical skills through his academic and professional journey. His expertise spans deep learning, machine learning, algorithm design, CUDA programming, and compiler design. He is proficient in using frameworks and tools like Python, TensorFlow, Keras, and PyTorch for deep learning and AI applications. Furthermore, his ability to develop and implement innovative systems, such as facial attendance systems and smart healthcare applications, demonstrates his ability to blend theoretical knowledge with hands-on technical skills. Mr. Kotwal also has considerable experience with data analysis and modeling, which is crucial for driving research in artificial intelligence. His passion for research is evident in his continuous engagement with new technologies and his involvement in applying them in innovative projects.

Awards and Honors:

Mr. Kotwal has received multiple awards and recognitions throughout his career. Notably, he was honored with the Best Teacher Award for his outstanding contribution to the academic community. His mentorship and guidance in national competitions, such as the Smart India Hackathon, led to his teams winning significant prizes, further enhancing his reputation as a leading educator and researcher. Mr. Kotwal also secured second place in the Amity Incubation Centre for his project on plant disease identification using deep learning. His patents and copyrights in the areas of facial recognition systems, smart expense managers, and privacy-oriented extensions demonstrate his innovative approach to research and technology development. These accolades not only reflect his individual accomplishments but also underscore his role in nurturing students and advancing research in technology.

Conclusion:

In conclusion, Mr. Jameer G. Kotwal is a distinguished academic and researcher whose contributions to the fields of computer science, particularly machine learning and deep learning, have made a significant impact. His extensive professional experience, coupled with his continuous academic growth through certifications and research, positions him as a strong contender for the Best Researcher Award. Mr. Kotwal’s leadership in curriculum development, his innovative patents and products, and his successful mentorship in national hackathons highlight his exceptional contributions to both education and research. His ability to blend theoretical knowledge with practical solutions makes him a valuable asset to the academic and research communities. Despite room for further collaboration and publication, his body of work clearly demonstrates his capability and potential for even greater accomplishments in the future.

Publication top Notes

  1. Enhanced leaf disease detection: UNet for segmentation and optimized EfficientNet for disease classification
    • Authors: Kotwal, J., Kashyap, R., Shafi, P.M., Kimbahune, V.
    • Year: 2024
  2. A modified time adaptive self-organizing map with stochastic gradient descent optimizer for automated food recognition system
    • Authors: Kotwal, J.G., Koparde, S., Jadhav, C., Somkunwar, R., Kimbahune, V.
    • Year: 2024
    • Citation: 3
  3. An India soybean dataset for identification and classification of diseases using computer-vision algorithms
    • Authors: Kotwal, J., Kashyap, R., Pathan, M.S.
    • Year: 2024
    • Citation: 1
  4. Artificial Driving based EfficientNet for Automatic Plant Leaf Disease Classification
    • Authors: Kotwal, J.G., Kashyap, R., Shafi, P.M.
    • Year: 2024
    • Citation: 85
  5. Yolov5-based convolutional feature attention neural network for plant disease classification
    • Authors: Kotwal, J.G., Kashyap, R., Shafi, P.M.
    • Year: 2024
    • Citation: 2
  6. A conditional generative adversarial networks and Yolov5 Darknet-based skin lesion localization and classification using independent component analysis model
    • Authors: Koparde, S., Kotwal, J., Deshmukh, S., Chaudhari, P., Kimbahune, V.
    • Year: 2024
  7. Big Data and Smart Grid: Implementation-Based Case Study
    • Authors: Kotwal, M.J., Kashyap, R., Shafi, P.
    • Year: 2023
  8. Agricultural plant diseases identification: From traditional approach to deep learning
    • Authors: Kotwal, J., Kashyap, D.R., Pathan, D.S.
    • Year: 2023
    • Citation: 142

 

 

Wei Zhou | Engineering | Best Researcher Award

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Dr. Wei Zhou | Engineering | Best Researcher Award

Lecturer at Nanjing University of Information Science and Technology, China

Wei Zhou is an innovative researcher and lecturer at Nanjing University of Information Science and Technology, China. He specializes in automatic sleep stage scoring, with a particular focus on applying machine learning and artificial intelligence techniques to the field of sleep analysis. Zhou’s work addresses critical challenges in the field, such as the inconsistency of device signals and the presence of noise in data, by developing novel algorithms that enhance sleep stage classification. His research is methodologically rigorous and demonstrates a strong commitment to advancing the capabilities of sleep analysis systems. Zhou is passionate about integrating cutting-edge technologies with modern research methodologies to solve complex problems in biomedical engineering. His research has been published in prestigious journals, and his innovative approaches have made a significant impact on both academic studies and potential clinical applications. Through his expertise, Zhou has contributed to the development of advanced models like MaskSleepNet and the Lightweight Segmented Attention Network, which have furthered the understanding and efficiency of sleep staging processes.

Professional Profile

Education

Wei Zhou completed his undergraduate studies in Electronic Information Engineering at Sichuan University in 2019, where he gained foundational knowledge in electrical engineering and signal processing. He then pursued a Ph.D. in Biomedical Engineering at Fudan University, which he is expected to complete in 2024. During his doctoral studies, Zhou specialized in sleep stage scoring using advanced machine learning techniques, particularly focusing on the integration of multimodal signals, such as electroencephalography (EEG) and electrooculography (EOG), to improve the accuracy of sleep analysis models. His research is rooted in both biomedical engineering and artificial intelligence, fields in which he has developed deep expertise. Zhou’s academic journey at two prestigious universities in China provided him with a strong interdisciplinary foundation, combining engineering principles with biomedical research. This educational background has enabled him to develop and refine innovative methodologies, making significant contributions to the field of sleep science.

Professional Experience

Wei Zhou is currently a lecturer at Nanjing University of Information Science and Technology, where he is involved in both teaching and research. His professional experience focuses primarily on the application of artificial intelligence and machine learning in biomedical engineering, specifically in the field of sleep analysis. Zhou’s work involves designing and developing algorithms that integrate electroencephalography (EEG) and electrooculography (EOG) signals for improved sleep staging, addressing challenges such as missing data and device inconsistencies. His role as a lecturer also includes mentoring students, conducting academic research, and publishing in top-tier journals. Prior to his current position, Zhou gained hands-on experience through various academic projects during his doctoral studies at Fudan University, where he developed novel approaches to sleep staging and contributed to projects involving both theoretical research and real-world applications. Zhou’s career reflects his commitment to advancing the field of biomedical engineering through academic excellence and innovative research. His professional trajectory highlights his growth as a researcher and educator, as well as his dedication to solving complex health-related challenges using advanced technologies.

Research Interests

Wei Zhou’s primary research interest lies in the application of machine learning and artificial intelligence techniques to sleep analysis. Specifically, he focuses on improving the accuracy and reliability of sleep stage scoring systems by integrating multimodal data, such as electroencephalography (EEG) and electrooculography (EOG). His research addresses the challenges of heterogeneous signals and data noise, which are common in sleep studies. Zhou has developed advanced algorithms like the pseudo-siamese neural network, MaskSleepNet, and the Lightweight Segmented Attention Network, all aimed at enhancing sleep stage classification and handling issues like device inconsistency and missing data. His work also explores the use of hybrid systems and optimization algorithms to improve the performance of sleep analysis models. Additionally, Zhou’s research interests extend to the broader application of machine learning in biomedical engineering, where he seeks to use advanced algorithms to address a variety of health-related challenges. He is passionate about integrating cutting-edge technologies into biomedical research to enhance both academic understanding and clinical applications, particularly in the context of sleep disorders.

Research Skills

Wei Zhou possesses a wide range of research skills, particularly in the areas of machine learning, artificial intelligence, and biomedical engineering. His expertise includes developing advanced algorithms for sleep stage classification using multimodal data, particularly EEG and EOG signals. Zhou is skilled in employing techniques such as convolutional neural networks (CNNs), attention mechanisms, and pseudo-siamese networks to create robust models that handle heterogeneous data and noise. His work also involves optimization algorithms, including biogeography-based optimization, to enhance model performance, particularly in cases with small sample sizes or limited data. Zhou is proficient in designing and implementing complex systems for biomedical signal processing, demonstrating his ability to combine engineering principles with health-related research. Additionally, he has experience with various data analysis and modeling tools, which he uses to validate his models across multiple public datasets. Zhou’s ability to innovate and adapt machine learning techniques to the challenges of biomedical research makes him a skilled and versatile researcher. His work is characterized by methodological rigor and a strong focus on improving the practical applications of his findings in clinical settings.

Awards and Honors

While specific awards and honors were not listed in the provided information, Wei Zhou’s research contributions have been widely recognized in the field of biomedical engineering and machine learning. His publications in prestigious journals such as the IEEE Journal of Biomedical and Health Informatics and IEEE Transactions on Neural Systems and Rehabilitation Engineering demonstrate the high regard in which his work is held within the academic community. Zhou’s innovative algorithms, such as MaskSleepNet and the Lightweight Segmented Attention Network, have gained attention for their potential to improve sleep stage classification and address real-world challenges in sleep analysis. His ability to produce impactful research that addresses critical issues in sleep staging, such as device inconsistency and data noise, positions him as a leading figure in his field. Zhou’s ongoing contributions to both academic research and the development of practical technologies suggest that he will continue to receive recognition for his work in the future. His research has the potential to revolutionize sleep analysis and provide valuable insights into the diagnosis and treatment of sleep disorders.

Conclusion

Wei Zhou is undoubtedly a strong candidate for the Best Researcher Award due to his innovative contributions to sleep stage scoring, the development of advanced machine learning techniques, and the significant potential impact of his work. His research has made notable strides in solving long-standing challenges in the field of sleep analysis, especially in addressing heterogeneous data and improving the accuracy of automated sleep staging. However, expanding his research’s interdisciplinary reach, ensuring the scalability of his models, and incorporating longitudinal studies could further enhance his impact and demonstrate the real-world applicability of his work. His current contributions, however, make him a leader in the field, positioning him as a highly deserving nominee for the award.

Publication Top Notes

  1. Outlier Handling Strategy of Ensembled-Based Sequential Convolutional Neural Networks for Sleep Stage Classification
  2. PSEENet: A Pseudo-Siamese Neural Network Incorporating Electroencephalography and Electrooculography Characteristics for Heterogeneous Sleep Staging
    • Authors: Wei Zhou, Ning Shen, Ligang Zhou, Minghui Liu, Yiyuan Zhang, Cong Fu, Huan Yu, Feng Shu, Wei Chen, Chen Chen
    • Year: 2024
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • DOI: 10.1109/JBHI.2024.3403878
  3. A Lightweight Segmented Attention Network for Sleep Staging by Fusing Local Characteristics and Adjacent Information
    • Authors: Wei Zhou, Hangyu Zhu, Ning Shen, Hongyu Chen, Cong Fu, Huan Yu, Feng Shu, Chen Chen, Wei Chen
    • Year: 2023
    • Journal: IEEE Transactions on Neural Systems and Rehabilitation Engineering
    • DOI: 10.1109/TNSRE.2022.3220372
  4. A Hybrid Expert System for Individualized Quantification of Electrical Status Epilepticus During Sleep Using Biogeography-Based Optimization
    • Authors: Wei Zhou, Xian Zhao, Xinhua Wang, Yuanfeng Zhou, Yalin Wang, Long Meng, Jiahao Fan, Ning Shen, Shuizhen Zhou, Wei Chen et al.
    • Year: 2022
    • Journal: IEEE Transactions on Neural Systems and Rehabilitation Engineering
    • DOI: 10.1109/TNSRE.2022.3186942
  5. An Energy Screening and Morphology Characterization-Based Hybrid Expert Scheme for Automatic Identification of Micro-Sleep Event K-Complex
    • Authors: Xian Zhao, Chen Chen, Wei Zhou, Yalin Wang, Jiahao Fan, Zeyu Wang, Saeed Akbarzadeh, Wei Chen
    • Year: 2021
    • Journal: Computer Methods and Programs in Biomedicine
    • DOI: 10.1016/j.cmpb.2021.105955

 

Wesam Rababa | Engineering | Best Researcher Award

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Mr. Wesam Rababa | Engineering | Best Researcher Award

Graduated Student at King Fahd University of Petroleum and Minerals, Saudi Arabia 

Wesam Rababa is a dedicated architectural professional specializing in sustainable design and green building practices. With a strong focus on environmental sustainability, Wesam integrates eco-friendly principles into architectural designs, creating structures that are both efficient and comfortable. His expertise spans project development, energy efficiency, CO₂ emissions, and passive design, all of which are central to advancing green architecture. Wesam’s professional experiences are diverse, covering roles in teaching, interior design, architectural engineering, and project management across Jordan and Saudi Arabia. Recognized for his academic excellence, he has contributed to sustainability-focused research and holds multiple certifications in sustainable assessment, energy auditing, and environmental product declarations. As a committed member of the architectural community, Wesam is also a part of the Jordan Engineers Association and has led the Jordanian community at King Fahd University. With a solid academic foundation and a passion for sustainable design, Wesam Rababa is actively shaping the future of architecture in an environmentally conscious direction.

Education

Wesam Rababa has a strong academic background in architecture with a focus on sustainability. He completed his Master’s degree in Architecture Science from King Fahd University of Petroleum and Minerals in Saudi Arabia in 2023, supported by a fully funded scholarship. His Master’s studies equipped him with advanced knowledge in sustainable design practices, allowing him to address environmental challenges in architecture. Before this, Wesam earned his Bachelor’s degree in Architecture Engineering from Yarmouk University in Jordan in 2020, where he graduated with First Honor and a GPA of 3.844/4. His undergraduate studies emphasized sustainability and green buildings, laying a solid foundation for his career in sustainable architecture. These achievements reflect his academic dedication and commitment to environmental sustainability, supported by his excellent performance and academic honors. Wesam’s educational journey highlights his dedication to learning and the critical role that sustainable design principles play in modern architecture.

Professional Experience

Wesam Rababa has held diverse roles in architectural and educational settings, demonstrating his commitment to sustainable design and project management. His recent role as a Planning Engineer at PHASE in Khobar, Saudi Arabia, involves overseeing project timelines, coordinating design and construction teams, and managing project risks and budgets. Wesam has also served as an Architect at Minimalist for Design in Jordan, where he developed design concepts and detailed 3D models, focusing on functionality and sustainability. In academia, he contributed as a Teaching Assistant at King Fahd University of Petroleum and Minerals, preparing course materials and teaching courses like Architectural Design Studio and Digital Communication. His teaching extended to Yarmouk University and the TAFE Arabia training institute, where he guided students in AutoCAD and engineering drawing. His professional journey showcases a blend of practical architectural work and academic contributions, highlighting his versatile skills in design, project planning, and education.

Research Interests

Wesam Rababa’s research interests center around sustainable architecture and energy efficiency. He is deeply invested in exploring ways to reduce CO₂ emissions and enhance energy efficiency within buildings. His work focuses on passive design principles, which aim to naturally regulate building temperatures through architectural design elements, reducing reliance on mechanical systems. Wesam is also interested in green buildings and facade retrofit strategies, especially in hot climates, where energy efficiency can make a significant environmental impact. His interest in sustainable assessment rating systems and life cycle assessment underscores his commitment to designing environmentally responsible buildings. Wesam’s research aligns with the pressing need for sustainable solutions in the built environment, addressing both ecological and functional aspects of architecture. By focusing on innovative strategies that prioritize sustainability, he is actively contributing to the advancement of environmentally friendly architectural practices.

Research Skills

Wesam Rababa possesses a broad set of research skills essential for advancing sustainable architectural practices. His technical proficiency in sustainability programs such as IES and Envi_Met supports his research in energy-efficient design and environmental analysis. Wesam is skilled in using advanced architectural software, including Revit, AutoCAD, and SketchUp, which are crucial for developing detailed and accurate design models. Additionally, he is proficient in visualization tools like Lumion, Illustrator, and Photoshop, enabling him to create compelling presentations of his sustainable designs. His knowledge of the Mostadam AP sustainability rating system and certifications in life cycle assessment (LCA) and energy auditing further complement his skill set, allowing him to conduct comprehensive sustainability evaluations. Wesam’s expertise in design, energy efficiency, and sustainable assessment tools highlights his capacity to conduct impactful research in green architecture, making him a valuable contributor to the field.

Awards and Honors

Wesam Rababa has received numerous accolades in recognition of his academic and professional achievements. His commitment to excellence in architecture was honored with First Honor recognition in his Bachelor’s degree in Architecture Engineering at Yarmouk University. He was awarded a fully funded MSc scholarship from King Fahd University of Petroleum and Minerals in Saudi Arabia, reflecting his academic potential and dedication to sustainability. Wesam also received a scholarship from the China Scholarship Council, emphasizing his academic standing. In competitions, he achieved top ranks, including fifth place in the Smart Campus Competition at King Fahd University in 2023. His project on “Lightweight Concrete Block” advanced to the final stage of the Shamal Star Competition, underscoring his innovative approach to sustainable construction. These awards and honors highlight Wesam’s dedication, innovation, and commitment to sustainable design, establishing him as a promising architect and researcher in his field.

Conclusion

Wesam Rababa demonstrates a strong candidacy for a Best Researcher Award, especially in fields centered on sustainability and environmentally conscious architectural design. With a robust foundation in sustainable practices, academic excellence, and contributions to sustainability research, they embody the qualities valued in a researcher committed to ecological impact. If they continue to expand their research outputs and engage in collaborative projects, Wesam’s contributions could further their influence and strengthen their case for recognition in sustainable architectural research awards.

Publication Top Notes

  1. Façade Retrofit Strategies for Energy Efficiency Improvement Considering the Hot Climatic Conditions of Saudi Arabia
    Journal: Applied Sciences
    Publication Date: November 1, 2024
    Author(s): Wesam Rababa