Rahul Charles C M | Engineering | Best Researcher Award

Published on by Academic Excellence

Best Researcher Award

Rahul Charles C M
College of Engineering Muttathara, India

Rahul Charles C M
Affiliation College of Engineering Muttathara
Country India
Google Scholar Profile rpc75fsAAAAJ
Documents 3
Citations 32
h-index 2
Subject Area Engineering
Event International Academic Excellence Awards

Rahul Charles C M is an engineering researcher affiliated with the College of Engineering Muttathara, India. The supplied academic record identifies three publications, 32 citations and an h-index of 2. His documented research includes work on doubly fed induction generators, field-oriented control and battery energy storage in wind-energy systems. These publications place his research within the broader engineering fields of renewable-energy conversion, electrical-machine control and energy-storage integration. [1]

Abstract

This academic recognition profile summarizes the supplied research record of Rahul Charles C M. His publication activity focuses on renewable-energy systems involving doubly fed induction generators, field-oriented control and battery energy storage. The available scholarly record indicates an engineering research trajectory concerned with improving the control and operational integration of wind-energy conversion systems. [2]

Keywords

Renewable energy; wind energy; doubly fed induction generator; field-oriented control; battery energy storage; electrical engineering; energy conversion.

Introduction

Wind-energy systems require coordinated control of electrical machines, converters and storage technologies to maintain reliable operation under variable generation conditions. Research into doubly fed induction generators and associated control strategies addresses these engineering challenges and forms the principal theme of the publications supplied for this profile. [1]

Research Profile

The supplied bibliometric information records three documents, 32 citations and an h-index of 2. These indicators provide a quantitative description of scholarly visibility but should be interpreted in relation to career stage, publication chronology, authorship, field-specific citation patterns and the completeness of the underlying indexing record. [2]

Research Contributions

  • Investigation of field-oriented control for doubly fed induction generator-based wind-energy systems incorporating battery energy storage. [1]
  • Study of field-oriented control of doubly fed induction generators in wind-power applications. [2]
  • Contribution to engineering research concerning renewable-energy conversion, generator control and storage-assisted wind-energy operation.

Publications

Field oriented control of DFIG based wind energy system using battery energy storage system was published in Procedia Technology, volume 24, pages 1203–1210, in 2016, and is listed with 24 citations in the supplied Google Scholar record. [1] Field oriented control of Doubly Fed Induction Generator in wind power system appeared in the 2015 IEEE International Conference on Computational Intelligence and Computing Research and is listed with eight citations. [2]

Research Impact

The supplied record reports 32 citations across three documents, with the 2016 wind-energy publication accounting for a substantial portion of the listed citations. The work addresses technically relevant challenges in renewable-energy generation and electrical-machine control, while the incorporation of battery storage connects generator control with broader energy-management considerations. [1]

Award Suitability

Based on the information supplied, Rahul Charles C M has a focused engineering publication record with identifiable contributions to wind-energy systems and generator-control technologies. The reported citation activity provides an additional indicator of scholarly use. Eligibility and final selection for the International Academic Excellence Awards should, however, be determined using the award’s official criteria and independently verified academic records.

Conclusion

The available record presents Rahul Charles C M as an engineering researcher whose documented work concerns doubly fed induction generators, field-oriented control and battery-supported wind-energy systems. His publications and reported citation record provide a measurable basis for academic recognition within renewable-energy and electrical-engineering research. [1] [2]

References

  1. Charles, C. M. R., Vinod, V., & Jacob, A. (2016). Field oriented control of DFIG based wind energy system using battery energy storage system. Procedia Technology, 24, 1203–1210.
    Google Scholar record
  2. Charles, C. M. R., Vinod, V., & Jacob, A. (2015). Field oriented control of Doubly Fed Induction Generator in wind power system. 2015 IEEE International Conference on Computational Intelligence and Computing Research.
    Google Scholar record
  3. Google Scholar. (n.d.). Rahul Charles C M publication profile. Google Scholar.
    https://scholar.google.com/citations?hl=en&user=rpc75fsAAAAJ&view_op=list_works&sortby=title
  4. IEEE. (2015). 2015 IEEE International Conference on Computational Intelligence and Computing Research. Conference publication record.
    Publication record
  5. Procedia Technology. (2016). Field oriented control of DFIG based wind energy system using battery energy storage system. Volume 24, pages 1203–1210.
    Publication record
  6. International Academic Excellence Awards. (n.d.). Official award website.
    https://academicexcellenceawards.com/

Rahul Diwate | Engineering | Best Researcher Award

Published on by Academic Excellence

Best Researcher Award

Rahul Diwate
Vishwakarma Institute of Technology, India

Rahul Diwate
Affiliation Vishwakarma Institute of Technology
Country India
Scopus ID 57223038655
Documents 36
Citations 70
h-index 5
Subject Area Engineering
Event International Academic Excellence Awards
Google Scholar Profile A66xQuoAAAAJ

Rahul Diwate is an engineering researcher affiliated with Vishwakarma Institute of Technology whose supplied scholarly record includes work in pattern matching, data mining, computer vision, machine learning, flood prediction, and intelligent surveillance systems. The available profile reports 36 documents, 70 citations, and an h-index of 5. His publications demonstrate a progression from foundational computational methods toward applied machine learning and computer-vision problems, including object detection, fire detection, and predictive environmental modelling. [1] [3]

Abstract

Rahul Diwate’s supplied publication record reflects research across computer science and engineering applications, with particular emphasis on algorithms, data mining, machine learning, and computer vision. His work includes studies of pattern matching and association-rule mining as well as more recent investigations into YOLO-based object detection, flood prediction, and lightweight convolutional neural networks for fire detection. [1] [2] [4] Together, these publications indicate an applied research orientation toward computational methods capable of addressing practical engineering and information-processing challenges.

Keywords

Engineering; machine learning; data mining; pattern matching; computer vision; object detection; YOLO; convolutional neural networks; flood prediction; fire detection; intelligent systems.

Introduction

Engineering research increasingly uses computational intelligence to process complex data and support automated decision-making. Diwate’s publication record illustrates this development through research that moves from established algorithmic techniques toward machine-learning applications. Early work addressed pattern matching and association-rule mining, while later publications examined object detection, predictive modelling, and compact neural-network architectures. [1] [2] This trajectory places his research within a broader engineering effort to develop efficient computational solutions for real-world problems.

Research Profile

The supplied profile shows a multidisciplinary computational focus. Pattern matching provides a foundation for identifying structures within data, while association-rule mining supports the discovery of relationships among variables. More recent studies apply machine learning to visual recognition and environmental prediction. The work on YOLO v3 addresses object detection, whereas the flood-prediction study applies machine-learning techniques to an environmental forecasting problem. [3] [4]

Research Contributions

  • Research into algorithmic approaches for pattern matching, addressing fundamental computational search and recognition problems. [1]
  • Review-oriented research on association-rule data mining and its applications in information analysis. [2]
  • Application of YOLO v3 for object detection, demonstrating the use of deep-learning methods in computer-vision systems. [3]
  • Development and evaluation of machine-learning approaches for flood occurrence prediction and lightweight CNN-based fire detection. [4] [5]

Publications

  1. Study of different algorithms for pattern matching. MRB Diwate and SJ Alaspurkar, International Journal, 2013. The supplied record reports 23 citations. [1]
  2. Data mining techniques in association rule: A review. RB Diwate and A Sahu, International Journal of Computer Science and Information Technologies, 2014. The supplied record reports 16 citations. [2]
  3. Optimization in object detection model using YOLO v3. RB Diwate, A Zagade, MR Khodaskar and VR Dange, 2022 International Conference on Emerging Smart Computing and Informatics. The supplied record reports 9 citations. [3]
  4. A predictive model for occurrence of floods using machine learning techniques. A Sarkar, AM Kulkarni, MR Khodaskar, SP Tidake and RB Diwate, resmilitaris, 2023, 13(2), 5054–5072. [4]
  5. Lower complex CNN model for fire detection in surveillance videos. RB Diwate, LV Patil, MR Khodaskar and NP Kulkarni, 2021 International Conference on Emerging Smart Computing and Informatics. [5]

Research Impact

The supplied bibliometric profile reports 36 documents, 70 citations, and an h-index of 5. Individual publications have also accumulated measurable citations, with the pattern-matching study listed at 23 citations and the data-mining review at 16 citations in the supplied Google Scholar record. [1] [2] These figures indicate scholarly visibility within the relevant computational and engineering literature. Bibliometric measures, however, are best interpreted together with research quality, methodological contribution, authorship responsibility, and practical significance.

Award Suitability

The supplied evidence provides a suitable basis for considering Rahul Diwate for a Best Researcher Award in Engineering. His record demonstrates sustained engagement with computational research, progressing from algorithmic methods and data mining to machine learning, object detection, environmental prediction, and intelligent surveillance. The combination of 36 reported documents and 70 citations provides quantitative support for an established scholarly record. Final award evaluation should additionally consider verified publication records, originality, individual research contribution, technical rigor, and practical or scientific outcomes.

Conclusion

Rahul Diwate’s supplied academic profile reflects a coherent engineering research trajectory centered on computational intelligence and applied machine learning. His publications cover pattern matching, data mining, object detection, flood prediction, and fire detection, demonstrating applications across information processing, computer vision, and engineering problem-solving. The reported scholarly indicators and publication record provide relevant evidence for consideration within the Best Researcher Award category.

References

  1. Diwate, M. R. B., and Alaspurkar, S. J. (2013). Study of different algorithms for pattern matching. International Journal, 3(3). Google Scholar record.
    Publication record
  2. Diwate, R. B., and Sahu, A. (2014). Data mining techniques in association rule: A review. International Journal of Computer Science and Information Technologies. Google Scholar record.
    Publication record
  3. Diwate, R. B., Zagade, A., Khodaskar, M. R., and Dange, V. R. (2022). Optimization in object detection model using YOLO v3. 2022 International Conference on Emerging Smart Computing and Informatics.
    Publication record
  4. Sarkar, A., Kulkarni, A. M., Khodaskar, M. R., Tidake, S. P., and Diwate, R. B. (2023). A predictive model for occurrence of floods using machine learning techniques. resmilitaris, 13(2), 5054–5072.
    Publication record
  5. Diwate, R. B., Patil, L. V., Khodaskar, M. R., and Kulkarni, N. P. (2021). Lower complex CNN model for fire detection in surveillance videos. 2021 International Conference on Emerging Smart Computing and Informatics.
    Publication record
  6. Elsevier. (n.d.). Scopus author details: Rahul Diwate, Author ID 57223038655. Scopus.
    https://www.scopus.com/pages/authors/57223038655

Asma Mahgoub | Engineering | Innovative Research Award

Published on by Academic Excellence

 

Innovative Research Award

Asma Mahgoub
Affiliation Qatar University
Country Qatar
Scopus ID 57207733885
Documents 11
Citations 106
h-index 4
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0002-6469-9039

Asma Mahgoub
Qatar University,Qatar

Asma Mahgoub is affiliated with Qatar University and has developed an emerging research profile in engineering with particular emphasis on semantic communication, artificial intelligence, machine learning, image understanding, and next-generation wireless systems. Her scholarly publications investigate methods that improve communication efficiency while maintaining semantic fidelity across modern digital networks.[1]

Abstract

This article summarizes the academic profile of Asma Mahgoub in recognition of her nomination for the Innovative Research Award. Her research combines semantic communication, explainable artificial intelligence, image captioning, transformer models, and intelligent networking to improve data transmission efficiency and communication quality. The body of work demonstrates interdisciplinary engineering research addressing future communication infrastructures, including 6G and edge intelligence, while contributing practical methodologies for semantic-aware information exchange.[2]

Keywords

Semantic Communication, Engineering, Artificial Intelligence, Transformer Models, Image Captioning, Edge Learning, 6G Networks, Explainable AI, Deep Learning, Machine Learning.

Introduction

Modern communication systems increasingly focus on semantic information rather than conventional bit-level transmission. This paradigm supports efficient utilization of bandwidth while preserving contextual meaning. Asma Mahgoub’s publications contribute to this evolving discipline by integrating natural language processing, vision-language models, and engineering optimization into semantic communication frameworks suitable for intelligent wireless environments.[3]

Research Profile

According to the provided scholarly indicators, the researcher has authored 11 indexed publications with 106 citations and an h-index of 4. The publication record reflects consistent engagement in emerging engineering topics including semantic text communication, image semantic transmission, explainable metrics, BERT embeddings, and transformer-based communication architectures. These contributions indicate sustained participation in internationally recognized engineering research.[4]

Research Contributions

  • Advanced transformer-based semantic communication systems.
  • Developed explainable metrics for semantic image communication.
  • Integrated image captioning with intelligent communication models.
  • Investigated semantic communication for future 6G and edge learning platforms.
  • Applied BERT embeddings to improve text semantic transmission.

Publications

  • Document-Level Transformer-Based Text Semantic Communication System (2026).
  • Efficient Explainable Metric for Semantic Communication of Images Using Image Captioning (2026).
  • Metaverse Unbound: Semantic Communication, 6G and Edge Learning (2025).
  • Semantic Communication of Images Using Image Generation and Image Captioning Models (2025).
  • On Using BERT Embeddings for Text Semantic Communication (2024).

Research Impact

The published work contributes to efficient information exchange in intelligent communication systems through semantic-aware methodologies. Research on explainability, multimodal learning, and transformer architectures supports future developments in engineering applications including smart networks, autonomous systems, and next-generation wireless communication technologies.[5]

Award Suitability

The Innovative Research Award recognizes researchers demonstrating originality, scholarly quality, and measurable academic contribution. Based on the documented publication record, citation performance, and interdisciplinary engineering research, Asma Mahgoub’s work aligns with these objectives through meaningful contributions to semantic communication research and advanced intelligent networking technologies.

Conclusion

Asma Mahgoub has established an active research portfolio focused on semantic communication and intelligent engineering systems. Her publications address practical and theoretical challenges relevant to future communication technologies while demonstrating continued scholarly development. The combination of research productivity, citation influence, and innovation supports recognition within international academic award programs.

External Links

References

  1. Mahgoub A. Document-Level Transformer-Based Text Semantic Communication System. Machine Learning and Knowledge Extraction. 2026. DOI: 10.3390/make8080225
  2. Mahgoub A. Efficient Explainable Metric for Semantic Communication of Images Using Image Captioning. IEEE Access. 2026. DOI: 10.1109/ACCESS.2026.3654009
  3. Mahgoub A. Metaverse Unbound: A Survey on Synergistic Integration Between Semantic Communication, 6G, and Edge Learning. IEEE Access. 2025. DOI: 10.1109/ACCESS.2025.3555753
  4. Mahgoub A. Semantic Communication of Images Using Image Generation and Image Captioning Models. 2025. DOI: 10.1007/978-981-96-1483-7_11
  5. Mahgoub A. On Using BERT Embeddings for Text Semantic Communication. HONET 2024. DOI: 10.1109/HONET63146.2024.10822884

 

Oluwole Famoriji | Engineering | Innovative Research Award

Published on by Academic Excellence

 

Innovative Research Award

Oluwole Famoriji
Affiliation Federal University of Technology and Environmental Sciences, Iyin-Ekiti, Nigeria
Country Nigeria
Scopus ID 57193136350
Documents 64
Citations 472
h-index 15
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0003-1357-3935

Oluwole Famoriji
Federal University of Technology and Environmental Sciences, Iyin-Ekiti, Nigeria

Oluwole Famoriji is an engineering researcher whose scholarly work emphasizes power systems, renewable energy integration, antenna technologies, electromagnetic analysis, and machine learning applications for intelligent electrical engineering. His publication portfolio demonstrates sustained contributions to advanced engineering research while addressing practical challenges involving energy optimization, communication systems, and computational prediction methods. The combination of peer-reviewed publications, measurable citation impact, and interdisciplinary collaborations reflects continued academic engagement within internationally recognized journals and conferences.[1]

Abstract

The academic profile of Oluwole Famoriji illustrates continued research activity in electrical and electronic engineering with a strong emphasis on intelligent systems, renewable energy, machine learning, and electromagnetic modelling. His work integrates theoretical development with engineering applications to improve prediction accuracy, voltage regulation, wireless communication performance, and sustainable energy management. The available publication record and citation indicators demonstrate consistent scientific productivity and international collaboration across multiple engineering disciplines.[2]

Keywords

  • Engineering
  • Machine Learning
  • Power Systems
  • Renewable Energy
  • Electromagnetic Radiation
  • Antenna Arrays
  • Artificial Intelligence

Introduction

Modern engineering increasingly depends on intelligent computational approaches to address energy efficiency, communication reliability, and infrastructure resilience. Oluwole Famoriji’s research aligns with these priorities by combining advanced analytical techniques with practical engineering solutions. His investigations contribute to renewable energy coordination, machine learning prediction, electromagnetic modelling, and wireless system optimization, supporting technological development within rapidly evolving engineering environments.[3]

Research Profile

The researcher has produced 64 indexed scholarly documents with 472 citations and an h-index of 15, reflecting measurable scientific influence. His publications span internationally recognized journals including IEEE Access, Applied Sciences, Energies, and other peer-reviewed engineering outlets. Research themes consistently focus on machine learning, intelligent power systems, antenna technologies, and computational engineering methods.[4]

Research Contributions

Major contributions include intelligent photovoltaic energy coordination under uncertainty, machine learning estimation of electromagnetic radiation near 5G infrastructure, multiclass support vector machine methods for direction-of-arrival estimation, systematic reviews of artificial intelligence in power system prediction, and structural electromagnetic modelling for millimeter-wave antenna performance. Collectively these studies advance engineering knowledge through computational innovation and practical system analysis.[5]

Publications

  • An Intelligent Technique for Coordination and Control of PV Energy and Voltage-Regulating Devices in Distribution Networks Under Uncertainties (2025).
  • Machine Learning Approach for Ground-Level Estimation of Electromagnetic Radiation in the Near Field of 5G Base Stations (2025).
  • A Multiclass Support Vector Machine Based Direction-of-Arrival Estimation Technique using Spherical Antenna Array (2024).
  • Machine Learning Approaches for Power System Parameters Prediction: A Systematic Review (2024).
  • Modeling of Coupled Structural Electromagnetic Statistical Concept for Examining Performance Sensitivity of Antenna Array to Distortion at Millimeter-Wave (2024).

Research Impact

The research demonstrates relevance to sustainable energy, smart electrical networks, telecommunications, and intelligent engineering systems. Citation performance and publication consistency indicate recognition by the academic community. The interdisciplinary nature of the work supports technological advancement through data-driven engineering methodologies and computational optimization.[6]

Award Suitability

Based on the documented scholarly record, Oluwole Famoriji demonstrates qualities associated with the Innovative Research Award, including sustained publication activity, interdisciplinary engineering research, international collaboration, and measurable scientific impact. His contributions to intelligent energy systems and computational engineering align with the objectives of recognizing innovation that advances engineering knowledge and practical applications.

Conclusion

The academic achievements of Oluwole Famoriji reflect a balanced combination of research productivity, engineering innovation, and scholarly influence. His investigations in renewable energy, machine learning, electromagnetic systems, and intelligent power networks contribute to contemporary engineering research while supporting future developments in sustainable and computational technologies.

External Links

References

  1. Scopus Author Profile. Research metrics and indexed publications. https://www.scopus.com/pages/authors/57193136350
  2. Famoriji O.J. et al. An Intelligent Technique for Coordination and Control of PV Energy and Voltage-Regulating Devices in Distribution Networks Under Uncertainties. Energies (2025). DOI: 10.3390/en18133481
  3. Famoriji O.J. Machine Learning Approach for Ground-Level Estimation of Electromagnetic Radiation in the Near Field of 5G Base Stations. Applied Sciences (2025). DOI: 10.3390/app15137302
  4. Famoriji O.J. A Multiclass Support Vector Machine Based Direction-of-Arrival Estimation Technique using Spherical Antenna Array. Indonesian Journal of Electrical Engineering and Informatics (2024).
  5. Makanju T.D., Shongwe T., Famoriji O.J. Machine Learning Approaches for Power System Parameters Prediction: A Systematic Review. IEEE Access (2024). DOI: 10.1109/ACCESS.2024.3397676
  6. Famoriji O.J. Modeling of Coupled Structural Electromagnetic Statistical Concept for Examining Performance Sensitivity of Antenna Array to Distortion at Millimeter-Wave. Applied Sciences (2024). DOI: 10.3390/app14167111

 

KARTHIK M | Engineering | Research Excellence Award

Published on by Academic Excellence

Dr. KARTHIK M | Engineering | Research Excellence Award

SRM Madurai College for Engineering and Tchnology | India

Dr. M. Karthik is a dedicated academician and researcher in the field of Electrical and Electronics Engineering, with a strong specialization in High Voltage Engineering. He currently serves as a Senior Grade Assistant Professor in the Department of Electrical and Electronics Engineering at SRM Madurai College for Engineering and Technology, Tamil Nadu. With over nine years of teaching experience across reputed engineering institutions, he has consistently contributed to academic excellence, curriculum delivery, and student mentorship. Dr. Karthik earned his Ph.D. (Part-Time) in High Voltage Engineering from Anna University, Chennai, completing his doctoral coursework at the Government College of Technology, Coimbatore, with outstanding academic performance. He also holds an M.E. degree in High Voltage Engineering, graduating as a university topper with distinction, and a B.E. degree in Electrical and Electronics Engineering. His strong academic foundation reflects his commitment to technical rigor and continuous learning. His primary research interests include liquid and solid dielectrics, high voltage insulation, and related reliability studies in power systems. Dr. Karthik has actively disseminated his research through multiple national-level conference paper presentations, covering interdisciplinary themes such as biomedical signal processing, intrusion detection systems, SCADA technology, energy conservation, fuel cell technologies, and advanced power electronics applications. An active contributor to the research community, Dr. Karthik maintains profiles on ORCID, Scopus, Google Scholar, Publons, and Vidwan, highlighting his scholarly engagement and research impact. Through his teaching, research, and academic service, he remains committed to advancing knowledge in high voltage engineering and fostering innovation in electrical engineering education.

Citation Metrics (Scopus)

300
100
50
10
0

Citations
262

Documents
40

h-index
10

Citations

Documents

h-index


View Scopus Profile  View Google Scholar Profile

Featured Publications

An efficient waste management technique with IoT based smart garbage system
– Materials Today: Proceedings, 2023
Frequency control of PV-connected micro grid system using fuzzy logic controller
– Materials Today: Proceedings, 2021
Visualization of virtual environment through LabVIEW platform
– Materials Today: Proceedings, 2021
Studies on critical properties of vegetable oil based insulating fluids
– IEEE INDICON, 2015
Appropriate analysis on properties of various compositions on fluids with and without additives for liquid insulation in power system transformer applications
– Scientific Reports, 2024

Peter Anyin | Engineering | Research Excellence Award

Published on by Academic Excellence

Dr. Peter Anyin | Engineering | Research Excellence Award

Institute for Intermodal Transports and Logistics Systems | Germany

Anyin, Peter Betianabeshe, Ph.D., is a transportation engineer and researcher specializing in traffic planning, simulation, and quantitative modeling of complex mobility systems. His academic and professional work is centered on developing data-driven and system-oriented approaches to improve traffic operations, urban mobility, and infrastructure planning, particularly in rapidly growing metropolitan regions. He is currently engaged in advanced research at Technische Universität Braunschweig, Germany, where his doctoral studies focus on transportation planning and traffic simulation, with a strong emphasis on designing quantitative metrics for evaluating microscopic traffic simulators and systemic planning frameworks. His Ph.D. research addresses the systemic planning of traffic in Lagos, Nigeria, integrating simulation-based methodologies with real-world mobility challenges. Dr. Anyin’s research expertise spans microscopic traffic simulation, queueing theory, statistical traffic data analysis, and computational modeling. He has extensive experience working with industry-standard simulation tools such as VISSIM, SUMO, Aimsun, and MATSim, alongside programming and analytical platforms including Python, MATLAB, Simulink, and SQL. His interdisciplinary research also extends into machine learning applications, such as generative adversarial networks and physics-informed neural networks, applied to traffic systems and pavement modeling. He has authored multiple peer-reviewed journal articles and conference papers on traffic simulation comparison, queueing models, sustainable transportation systems, and computational methodologies. His work has been published in reputable international journals and presented at global conferences. In addition to research, he actively supervises graduate students, contributes to collaborative urban planning projects, and engages with stakeholders to translate simulation research into practical transportation solutions.

Citation Metrics (Google Scholar)

15
10
5
1
0

Citations
2

Documents
8

h-index
1

Citations

Documents

h-index


View Google Scholar Profile

Featured Publications

Analytical Determination of Queueing System Performance for Sustainable Economic Development
– Arid Zone Journal of Engineering, Technology and Environment, 2022
MATLAB SimEvent for Traffic Queue Model
– Arid Zone Journal of Engineering, Technology and Environment, 2024
Simplified Octahedral Shear Stress Theory for Plane Elements
– Nnamdi Azikiwe University Journal of Civil Engineering, 2025
Formulation of Limit State Deflection Equation for Thin Rectangular Steel Plates Analysis
– Nnamdi Azikiwe University Journal of Civil Engineering, 2025
Pertuzumab Overcomes Chemotherapy/Trastuzumab Resistance in ER+/HER2+ Tumors Classified as Luminal Functional Subtype
– Cancer Research (Supplement), 2016

Farzin Naghibalsadati | Engineering | Best Researcher Award

Published on by Academic Excellence

Mr. Farzin Naghibalsadati | Engineering | Best Researcher Award

Mr. Farzin Naghibalsadati, University of Regina, Canada

Farzin Sadati, PMP®, is a highly accomplished Civil Engineer with over a decade of expertise in large-scale industrial, commercial, and institutional construction. Currently based in Regina, Saskatchewan, he holds a Master’s degree in Environmental Systems Engineering and specializes in sustainable construction practices and project management. With strong technical proficiency in NBC codes, risk management, budgeting, and quality control, Farzin has led multi-million-dollar construction projects with notable success. He combines academic excellence, demonstrated by scholarships and awards, with real-world impact through roles in top construction firms and research initiatives. As a committed leader and effective communicator, he excels in coordinating interdisciplinary teams and optimizing project timelines and costs. His work bridges hands-on field experience and research innovation, with a recent focus on modular construction waste analytics. Farzin is affiliated with prominent engineering and project management organizations and is recognized for his leadership in promoting sustainable development goals (SDGs).

Professional Profile

Scopus

Orcid

Google Scholar

Suitability Summary for Research for Best Researcher Award

Farzin Sadati is a highly qualified candidate for the Research for Best Researcher Award, demonstrating a strong blend of academic excellence, professional experience, and impactful research contributions. His educational background is robust, with a Master’s in Environmental Systems Engineering from the University of Regina, supported by a full NSERC scholarship, underscoring his academic merit and research potential. Additionally, his prior Master’s in Structural Engineering and Bachelor’s in Civil Engineering provide a comprehensive foundation in both theory and practice.

Professionally, Farzin brings over 10 years of leadership in large-scale construction projects exceeding $100 million, showcasing his capability to manage complex, multidisciplinary efforts successfully. His hands-on experience in project management, site supervision, regulatory compliance, and sustainability reflects a practical understanding of real-world engineering challenges. His PMP certification and expertise with construction management software such as Procore and Primavera P6 further highlight his competence in bridging management and technical domains.

Education 🎓 

Farzin Sadati’s academic journey reflects a commitment to excellence and sustainability. He is currently pursuing a MASc in Environmental Systems Engineering at the University of Regina, Canada, with a CGPA of 83.80. His research, supported by a prestigious Natural Sciences and Engineering Research Council of Canada (NSERC) scholarship, explores sustainable construction practices and modular waste management. Prior to this, he earned a MASs in Structural Engineering (CGPA: 95.45) and a BASc in Civil Engineering (CGPA: 88.65) from Azad University, Iran. Throughout his studies, Farzin demonstrated academic prowess, earning multiple nominations and awards, including a top-three ranking among graduate peers. His academic background combines technical rigor in structural systems with contemporary approaches to environmental engineering. This foundation equips him to tackle challenges at the intersection of infrastructure and sustainability, laying the groundwork for his contributions to research, practice, and policy. His education underpins his holistic perspective on engineering and environmental responsibility.

Professional Experience 💼

Farzin Sadati brings over 10 years of progressive experience across various sectors including residential, commercial, and infrastructure projects. Currently serving as Construction Project Manager at ISAD Construction, he has led complex developments like a 144-unit concrete structure valued at $34M, and successfully managed stakeholder coordination and risk mitigation strategies. His tenure at the University of Regina as a Researcher further honed his expertise in construction waste analytics and compliance with NBC. Previously, at Imen Sazan Faradezh Inc., he contributed to structural design and feasibility assessments, increasing project efficiency. Farzin began his career as a Superintendent with Saman Gostar Jame Inc., managing large-scale HVAC and residential projects. He has a proven record in applying data analytics, BIM, and sustainable methods across all project phases. His leadership style, problem-solving approach, and proficiency with tools like Procore, Primavera P6, and Microsoft Project enable him to consistently deliver high-quality outcomes on time and under budget.

Awards and Recognition 🏅

Farzin Sadati has been recognized for both his academic excellence and impactful professional contributions. In 2024, he received the RCE Saskatchewan Award, presented by Lieutenant Governor Russell Mirasty, for a sustainable construction and demolition project that aligns with the UN Sustainable Development Goals (SDGs). This project leveraged BIM technologies to promote green practices in the construction sector. In 2023, Farzin’s research was awarded full funding by the Natural Sciences and Engineering Research Council of Canada (NSERC), highlighting its relevance and innovation. Earlier, in 2018, he was honored as one of the top three graduate students at Azad University with a remarkable CGPA of 95. His certifications include PMP, WHMIS, and specialized training in AI for energy management, carbon emission analysis, and life cycle assessment. These recognitions underscore his leadership in driving sustainability and performance excellence in engineering projects, positioning him as a forward-thinking leader in the construction industry.

Research Skills On Engineering 🌍 

Farzin Sadati’s research skills span environmental systems engineering, construction waste analytics, and sustainable design. At the University of Regina, his work integrated statistical data from agencies like Statistics Canada with practical construction metrics to assess compliance with the National Building Code and identify opportunities for waste reduction. He effectively utilizes tools like Power BI, Excel, and BIM to visualize performance indicators and propose cost-effective solutions. Farzin’s expertise extends to life cycle analysis, carbon emissions monitoring, and the deployment of AI in green building energy management. His research not only advances academic knowledge but also informs best practices on job sites, particularly in modular and digital construction. With a pragmatic and data-driven approach, he bridges academic insights and field application, delivering strategies that enhance LEED compliance, sustainability, and energy performance. His collaborative projects and published papers reflect his commitment to innovation and environmental stewardship in engineering.

📖  Publication Top Notes

1. Title: Temporal evolution and thematic shifts in sustainable construction and demolition waste management through building information modeling technologies: A text-mining analysis

Authors: F. Naghibalsadati, A. Gitifar, S. Ray, A. Richter, K.T.W. Ng
Journal: Journal of Environmental Management
Volume: 369, Article ID: 122293
Citations: 7
Year: 2024

2. Title: Management Assessment of Used Oil, Filters, and Containers in the Canadian Automotive Sector Using Resource Recovery Metrics

Authors: A. Tasnim, A.T. Abha, F. Naghibalsadati, E. Tam, K.T.W. Ng
Journal: Waste Management
Volume: 191, Pages: 284–293
Citations: 2
Year: 2025

3. Title: Quantification of construction and demolition waste disposal behaviors during COVID-19 using satellite imagery

Authors: S. Ray, K.T.W. Ng, T.S. Mahmud, A. Richter, F. Naghibalsadati
Journal: Environmental and Sustainability Indicators
Volume: 24, Article ID: 100502
Citations: 2
Year: 2024

4. Title: Uncovering key themes in modular construction waste management and exploring their impact and centrality

Authors: F. Naghibalsadati, A. Gitifar, A. Richter, A. Tasnim, K.T.W. Ng
Journal: Results in Engineering
Volume: 25, Article ID: 104550
Citations: 1
Year: 2025

5. Title: Landfill footprint geometrical design evolution and land surface thermal heterogeneity

Authors: A. Gitifar, N. Karimi, S.J. Mim, F. Naghibalsadati, K.T.W. Ng
Journal: Journal of Cleaner Production
Article ID: 145763
Year: 2025

6. Title: The Role of Modular Construction and BIM Technologies in Sustainable Construction and Demolition Waste Management

Author: F. Naghibalsadati
Institution: University of Regina
Type: Thesis/Dissertation
Year: 2024

7. Title: Experimental and Numerical Evaluation on Yielding Damper to Upgrade the Seismic Behavior of Concentrically Braced Frames

Authors: F. Naghibalsadati, S.M. Zahrai, M. Jamshidi
Conference: International Congress of Sciences and Innovative Technologies (ICESIT)
Volume: 270, Page: 133
Year: 2018

8. Title: Experimental and Numerical Investigation of Angle Performance as a Structural Fuse

Authors: F. Naghibalsadati, S.M. Zahrai, M. Jamshidi
Conference: International Congress of Sciences and Innovative Technologies (ICESIT)
Volume: 270, Page: 118
Year: 2018

9.Title: Experimental Study on Cyclic Performance of Diagonal Brace with Slit and Angle to Improve Ductility

Author: F. Naghibalsadati
Institution: Islamic Azad University
Type: Thesis/Dissertation
Year: 2018

 

Md. Kamrul Islam | Engineering | Best Researcher Award

Published on by Academic Excellence

Assoc. Prof. Dr. Md. Kamrul Islam | Engineering | Best Researcher Award

Assoc. Prof. Dr. Md. Kamrul Islam, King Faisal University, Saudi Arabia 

Dr. Md. Kamrul Islam, an Australian national, currently serves as an Associate Professor at King Faisal University, KSA. With over two decades of experience in civil and transportation engineering, he holds a PhD from the University of New South Wales, Australia, and advanced degrees from the University of Tokyo and DUET, Bangladesh. Dr. Islam’s research focuses on stochastic modeling, asphalt performance, and public transport systems. He has successfully led more than 50 research projects funded by Deanship of Scientific Research and collaborated with premier institutions like University of Illinois and Texas A&M. His excellence has been recognized with prestigious awards such as the Furuichi Kimitake Prize and Institute Gold Medal. Dr. Islam is also a proactive academic mentor, guiding numerous undergraduate projects and contributing to international academic collaborations. His technical, analytical, and conceptual skills have made a significant impact on the field of engineering.

Professional Profile

Scopus

Orcid

Google Scholar

Summary of Suitability for the Research for Best Researcher Award – Md. Kamrul Islam

Dr. Md. Kamrul Islam, affiliated with King Faisal University, Saudi Arabia, and an Australian citizen, presents a promising profile for the Research for Best Researcher Award. As a faculty member at a reputed institution in the Gulf region, he is likely engaged in cutting-edge research and academic collaboration, contributing significantly to his field. His dual academic and cultural experience, having connections in both Australia and the Middle East, potentially strengthens his international outreach and research dissemination impact.

Given the rigorous environment of King Faisal University, which emphasizes innovation and scholarly contributions, Dr. Islam’s ongoing involvement likely includes authoring peer-reviewed articles, mentoring postgraduate researchers, and participating in international conferences. If his work spans applied or interdisciplinary domains, it would further align with the award’s emphasis on impactful and forward-looking research contributions.

🎓 Education 

Dr. Md. Kamrul Islam’s academic journey showcases his deep-rooted expertise in transportation and civil engineering. He earned his PhD in Transportation Engineering from the University of New South Wales, Australia, in 2014. His doctoral thesis focused on stochastic modeling of public transit performance, leading to several high-impact journal publications. Prior to this, he obtained his Master’s in Engineering with a major in Transportation Planning from the University of Tokyo, Japan, in 2006. His master’s research on urban systems and consumption behavior across East Japan equipped him with advanced simulation and data analysis skills. Dr. Islam began his academic pursuit with a B.Sc. in Civil Engineering from DUET, Bangladesh, in 2002, where he graduated with top honors and was later accredited by Engineers Australia as meeting professional engineer standards. His educational background has laid the foundation for his exceptional contributions to engineering research and teaching.

💼 Professional Experience

Dr. Md. Kamrul Islam has extensive academic and industry experience. He is currently an Associate Professor (since September 2024) and was formerly an Assistant Professor (2015–2024) at the Department of Civil and Environmental Engineering, King Faisal University (KFU), KSA. At KFU, he spearheaded multi-institutional research collaborations and managed projects under the Saudi Aramco Chair on Asphalt Pavement. Before joining KFU, he held faculty positions at DUET, Bangladesh, from 2003 to 2015, progressing from Lecturer to Assistant Professor. His international experience includes roles as a Casual Graduate Academic at UNSW, Australia, and as a Civil Engineer at Pacific Consultant International in Japan, where he contributed to deep-sea port planning. Earlier, he worked as a Project Implementation Officer for the Ministry of Food and Disaster Management, Bangladesh. Throughout his career, he has balanced rigorous academic teaching, research leadership, and field-level infrastructure planning with exceptional professionalism.

🏅 Awards and Recognition

Dr. Md. Kamrul Islam’s outstanding academic and research contributions have earned him multiple prestigious accolades. In 2006, he received the Furuichi Kimitake Prize from the University of Tokyo for excellence in engineering graduation, recognizing his innovative thesis and academic merit. Earlier, in 2002, he was honored with the Institute Gold Medal by the Board of Governors of DUET, Bangladesh, for securing top marks in his undergraduate studies. His research success is further exemplified by securing and completing over 50 research projects sponsored by the Deanship of Scientific Research (DSR) at King Faisal University. These achievements are a testament to his commitment to advancing engineering through research, innovation, and academic collaboration. Additionally, his role in fostering international research networks and mentoring undergraduate students highlights his dedication to academic excellence and leadership in civil and transportation engineering.

🌍 Research Skill On Engineering

Dr. Md. Kamrul Islam exhibits a dynamic portfolio of advanced research skills. He specializes in transportation engineering, stochastic modeling, and asphalt material performance. His PhD research demonstrated his ability to analyze complex transit systems using computational techniques and large-scale algorithms in MATLAB. At KFU, he led multidisciplinary projects addressing sulfur-extended asphalt, pavement benchmarking, and life-cycle assessments. Dr. Islam has developed significant expertise in analytical modeling, data simulation, and numerical approximation, often applied to real-world transport networks. His work involves integrating academic theory with field-based applications, allowing for policy-relevant insights and innovations in civil infrastructure. He has also mastered collaborative research management, coordinating with leading institutions in the USA and Japan. With strong technical acumen, conceptual clarity, and problem-solving approaches, he continues to contribute to academic advancement and sustainable engineering solutions.

📖  Publication Top Notes

  • Title: A review of the evolution of technologies to use sulphur as a pavement construction material
    Authors: N. Sakib, A. Bhasin, M.K. Islam, K. Khan, M.I. Khan
    Journal: International Journal of Pavement Engineering, 22(3), 392-403
    Citations: 40
    Year: 2021

  • Title: Towards sustainable road safety in Saudi Arabia: Exploring traffic accident causes associated with driving behavior using a Bayesian belief network
    Authors: M.M. Rahman, M.K. Islam, A. Al-Shayeb, M. Arifuzzaman
    Journal: Sustainability, 14(10), 6315
    Citations: 33
    Year: 2022

  • Title: Climate change in Bangladesh: Temperature and rainfall climatology of Bangladesh for 1949–2013 and its implication on rice yield
    Authors: E. Alam, A.E.E. Hridoy, S.M.S.H. Tusher, A.R.M.T. Islam, M.K. Islam
    Journal: PLOS ONE, 18(10), e0292668
    Citations: 29
    Year: 2023

  • Title: Predicting road crash severity using classifier models and crash hotspots
    Authors: M.K. Islam, I. Reza, U. Gazder, R. Akter, M. Arifuzzaman, M.M. Rahman
    Journal: Applied Sciences, 12(22), 11354
    Citations: 28
    Year: 2022

  • Title: Coupling of machine learning and remote sensing for soil salinity mapping in coastal area of Bangladesh
    Authors: S.K. Sarkar, R.R. Rudra, A.R. Sohan, P.C. Das, K.M.M. Ekram, S. Talukdar, …
    Journal: Scientific Reports, 13(1), 17056
    Citations: 24
    Year: 2023

  • Title: A bulk queue model for the evaluation of impact of headway variations and passenger waiting behavior on public transit performance
    Authors: M.K. Islam, U. Vandebona, V.V. Dixit, A. Sharma
    Journal: IEEE Transactions on Intelligent Transportation Systems, 15(6), 2432-2442
    Citations: 23
    Year: 2014

  • Title: Reliability analysis of public transit systems using stochastic simulation
    Authors: M.K. Islam, U. Vandebona
    Journal: Not specified
    Citations: 21
    Year: 2010

  • Title: Greenhouse gas emissions in the industrial processes and product use sector of Saudi Arabia—An emerging challenge
    Authors: M.M. Rahman, M.S. Rahman, S.R. Chowdhury, A. Elhaj, S.A. Razzak, …
    Journal: Sustainability, 14(12), 7388
    Citations: 20
    Year: 2022

  • Title: A critical, temporal analysis of Saudi Arabia’s initiatives for greenhouse gas emissions reduction in the energy sector
    Authors: M.M. Rahman, M.A. Hasan, M. Shafiullah, M.S. Rahman, M. Arifuzzaman, …
    Journal: Sustainability, 14(19), 12651
    Citations: 19
    Year: 2022

  • Title: Flood hazard mapping using GIS-based statistical model in vulnerable riparian regions of sub-tropical environment
    Authors: A. Ghosh, U. Chatterjee, S.C. Pal, A.R.M. Towfiqul Islam, E. Alam, M.K. Islam
    Journal: Geocarto International, 38(1), 2285355
    Citations: 18
    Year: 2023

keerthana G | Engineering | Best Researcher Award

Published on by Academic Excellence

Mrs. keerthana G | Engineering | Best Researcher Award

Shagufta Riaz | Engineering | Women Researcher Award

Published on by Academic Excellence

Dr. Shagufta Riaz | Engineering | Women Researcher Award

Dr. Shagufta Riaz, National Textile University, Pakistan 

Dr. Shagufta Riaz is an Assistant Professor in the Department of Textile Engineering at National Textile University, Faisalabad, Pakistan. With a Ph.D. in Textile Engineering, she specializes in functional textiles, focusing on the use of nanomaterials for textile development. Dr. Riaz has authored several influential publications and has completed various high-impact research projects. She has worked as a researcher at the Wilson School of Textiles in the USA and is actively involved in advancing textile innovations. A member of prestigious international organizations like the Textile Institute and the Pakistan Engineering Council, Dr. Riaz is committed to sustainable textile solutions.

Professional Profile

Scopus

Google Scholar

Suitability of Dr. Shagufta Riaz for the Research for Women Researcher Award

Dr. Shagufta Riaz is a highly accomplished researcher in textile engineering, specializing in functional textiles and nanotechnology applications. Her extensive academic background, including a Ph.D. in Textile Engineering and international research experience at the Wilson School of Textiles, NCSU, USA, demonstrates her expertise in the field. She has significantly contributed to the advancement of sustainable textile innovations, textile finishing, and the development of nanomaterials for multifunctional textile applications. As an HEC Ph.D. Approved Supervisor and a Fellow of the Textile Institute, UK, she has played a crucial role in mentoring young researchers and advancing academic excellence in textile engineering.

Her research portfolio includes several high-impact projects funded at both national and international levels, focusing on crucial areas such as RF-shielding maternity garments, recycling of cellulosic waste for graphene quantum dots, and sustainable bio-processing in textile manufacturing. Additionally, her collaborations with industry highlight her ability to bridge the gap between academic research and practical industrial applications. Notable projects include the development of antibacterial medical gauze, pesticide-resistant clothing, and UV-shielding protective garments, which showcase her commitment to improving textile functionality for real-world challenges.

🎓 Education

Dr. Shagufta Riaz holds a Ph.D. in Textile Engineering from National Textile University, Faisalabad, Pakistan, where she also completed her M.Sc. in Textile Advanced Materials Engineering and B.Sc. in Textile Engineering with distinctions. She further honed her skills as a researcher at the Wilson School of Textiles, North Carolina State University, USA. This educational foundation, coupled with her hands-on research experience, forms the backbone of her expertise in nanotechnology, textile finishing, and sustainable textile innovations.

💼 Professional Experience

Dr. Shagufta Riaz is an Assistant Professor at National Textile University, Faisalabad. She has led and collaborated on multiple research projects, including those in partnership with international institutions and the textile industry. Her professional experience spans research in textile engineering, focusing on nanomaterials and sustainable solutions. Dr. Riaz has consulted on industry projects to optimize processes in textile production, such as designing protective garments and improving fabric properties. Her role as a Ph.D. supervisor and her recognition as a Fellow of the Textile Institute, UK, highlight her significant contribution to academia and industry.

🏅 Awards and Recognition

Dr. Shagufta Riaz’s academic excellence is evidenced by her recognition as a Fellow of the Textile Institute, UK, and a Lifetime Member of the Pakistan Engineering Council. She has received multiple accolades for her contributions to textile engineering, including a significant number of awards for her research in nanotechnology and textile innovations. Her work, recognized internationally, is reflected in numerous high-impact publications and the completion of major research and consultancy projects in collaboration with the textile industry.

🌍 Research Skills On Engineering

Dr. Riaz is an expert in nanotechnology applications in textile engineering, particularly for the development of multifunctional textiles. Her research focuses on the integration of nanomaterials to enhance textile properties such as antimicrobial, UV resistance, and electrical shielding. She has completed several research projects under government and industry funding, contributing valuable advancements in sustainable textiles, functional finishes, and eco-friendly processes. Dr. Riaz’s skills extend to guiding doctoral research and publishing in prestigious journals, marking her as a leading researcher in textile engineering.

📖 Publication Top Notes

  • Fabrication of robust multifaceted textiles by application of functionalized TiO₂ nanoparticles

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Younus
    • Citations: 95
    • Year: 2019

  • Functional finishing and coloration of textiles with nanomaterials

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Rehman, A. Javid, K. Iqbal, …
    • Citations: 77
    • Year: 2018

  • Modification of silica nanoparticles to develop highly durable superhydrophobic and antibacterial cotton fabrics

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain
    • Citations: 58
    • Year: 2019

  • Electrospun nanofiber-based viroblock/ZnO/PAN hybrid antiviral nanocomposite for personal protective applications

    • Authors: A. Salam, T. Hassan, T. Jabri, S. Riaz, A. Khan, K.M. Iqbal, S. Khan, M. Wasim, …
    • Citations: 41
    • Year: 2021

  • Cationization of TiO₂ nanoparticles to develop highly durable multifunctional cotton fabric

    • Authors: S. Riaz, M. Ashraf, H. Aziz, A. Younus, M. Umair, A. Salam, K. Iqbal, …
    • Citations: 31
    • Year: 2022

  • Layer by layer deposition of PEDOT, silver and copper to develop durable, flexible, and EMI shielding and antibacterial textiles

    • Authors: S. Riaz, S. Naz, A. Younus, A. Javid, S. Akram, A. Nosheen, M. Ashraf
    • Citations: 26
    • Year: 2022

  • Multifunctional formaldehyde-free finishing of cotton by using metal oxide nanoparticles and eco-friendly cross-linkers

    • Authors: N. Sarwar, M. Ashraf, M. Mohsin, A. Rehman, A. Younus, A. Javid, K. Iqbal, …
    • Citations: 24
    • Year: 2019

  • In situ development and application of natural coatings on non-absorbable sutures to reduce incision site infections

    • Authors: R. Masood, T. Hussain, M. Umar, Azeemullah, T. Areeb, S. Riaz
    • Citations: 21
    • Year: 2017

  • Selection and Optimization of Silane Coupling Agents to Develop Durable Functional Cotton Fabrics Using TiO₂ Nanoparticles

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Younus, M. Raza, A. Nosheen
    • Citations: 20
    • Year: 2021

  • Simultaneous fixation of wrinkle-free finish and reactive dye on cotton using response surface methodology

    • Authors: S. Abid, T. Hussain, A. Nazir, Z.A. Raza, A. Siddique, A. Azeem, S. Riaz
    • Citations: 16
    • Year: 2018