Asma Mahgoub | Engineering | Innovative Research Award

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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

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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

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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.

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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

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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)

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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

Sumaraj S | Engineering | Academic Excellence Award

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Dr. Sumaraj S | Engineering | Academic Excellence Award

Dr. Sumaraj is a Civil and Environmental Engineer with over a decade of academic and research experience, specializing in water and environmental sustainability. He holds a Ph.D. in Civil and Environmental Engineering from the University of Auckland, New Zealand, where his doctoral research contributed to advancing sustainable approaches in water and wastewater treatment systems. His strong academic foundation also includes a Master of Technology in Environmental Engineering and Management from the Indian Institute of Technology Kharagpur, where he graduated with distinction, and a Bachelor of Engineering in Civil Engineering from the National Institute of Engineering, Mysore. Dr. Sumaraj’s research interests span water and wastewater treatment engineering, sustainable technologies, nutrient contaminant remediation, carbon-based materials such as biochar and activated carbon, adsorption mechanisms, surface chemistry, analytical chemistry, and air pollution monitoring. His work reflects an interdisciplinary approach that integrates environmental science, engineering solutions, and sustainability-driven innovation, leading to peer-reviewed publications, conference presentations, and award-winning student research projects. Currently serving as an Assistant Professor in the Department of Civil Engineering at Nitte Meenakshi Institute of Technology, Bengaluru, Dr. Sumaraj is actively involved in teaching, mentoring, and academic leadership. He has designed and delivered courses in green technology, environmental sustainability, wastewater treatment, water supply engineering, and research methodology. Beyond the classroom, he plays a key role in industry–academia collaboration, skill development initiatives, and sustainability-focused training programs. A recipient of multiple scholarships and honors, including the University of Auckland Doctoral Scholarship and recognition under national and international sustainability programs, Dr. Sumaraj is also a certified Green-Belt Career and Higher Education Counsellor. His professional journey reflects a strong commitment to research excellence, environmental stewardship, and the development of future-ready engineers.

Citation Metrics (Google Scholar)

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Featured Publications

Eddy Chevallier | Engineering | Best Researcher Award

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Dr. Eddy Chevallier | Engineering | Best Researcher Award

LAMIH – UPHF/CNRS 8201 | France

Dr. Eddy Chevallier is a distinguished researcher in Engineering Sciences, specializing in electromechanical systems that utilize static or dynamic electrical contact as a channel for information or power transmission. Currently serving as an Ingénieur de Recherche at the LAMIH Laboratory (UMR CNRS 8201, UPHF) in Famars, France, he focuses on understanding how surface topography influences multi-physical phenomena occurring at interfaces. His work spans electrical, thermal, and mechanical properties, integrating experimental measurement, numerical programming, and theoretical modeling to advance industrial applications that rely on surface-dependent interactions. His research aims to identify and quantify the relationships between topographic parameters and functional surface behavior, enabling the development of hybrid methodologies for optimizing surface designs based on precise performance requirements. Dr. Chevallier is qualified in the French national academic sections 28 (Physics of Materials), 60 (Mechanics), and 63 (Electrical Engineering), reflecting the interdisciplinary breadth of his expertise. He earned his Doctorate in 2014 from the Université de Picardie Jules Verne, where his thesis, supervised by Jérôme Fartin and co-advised by Robert Rouzereau and Valéry Bourny, focused on defining quality indices for metallic sliding contact using electrical signatures of surface condition. His doctoral work received the distinction of “Très Honorable.” He also holds a Master’s degree in physical characterization and modeling of complex materials from the same institution. Dr. Chevallier has contributed to leading scientific journals such as Tribology International, Journal of Tribology, Journal of Applied Physics, and has presented his work at numerous international and national conferences, reinforcing his role as a key contributor to tribology and electromechanical interface research.

Profile: Google Scholar

Featured Publications

Chevallier, E., Bourny, V., Bouzerar, R., Fortin, J., Durand-Drouhin, O., & others. (2014). Voltage noise across a metal/metal sliding contact as a probe of the surface state. Journal of Applied Physics, 115(15).

Chevallier, E. (2014). Définition d’indices de qualité du contact glissant métallique: Signatures électriques de l’état de surface (Doctoral dissertation, Université de Picardie Jules Verne). Université de Picardie Jules Verne.

Chevallier, E. (2020). Mechanical model of the electrical response from a ring–wire sliding contact. Tribology Transactions, 63(2), 215–221.

Jonckheere, B., Bouzerar, R., Bourny, V., Bausseron, T., Foy, N., & Chevallier, E. (2017). Assessment of the real contact area of a multi-contact interface from electrical measurements. In 23ème Congrès Français de Mécanique (CFM), France.

Guessasma, M., Bourny, V., Haddad, H., Machado, C., Chevallier, E., Tekaya, A., & others. (2018). Multi-scale and multi-physics modeling of the contact interface using DEM and coupled DEM-FEM approach. In Advances in Multi-Physics and Multi-Scale Couplings in Geo-Environmental Engineering.

Moulya H.V | Engineering | Women Researcher Award

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Mrs. Moulya H.V | Engineering | Women Researcher Award

Nitte Meenakshi Institute Of Technology | India

Moulya Hosagadhe Venkataramana is an accomplished academic and construction engineering professional with extensive experience in Concrete Technology, Construction Management, and Quality Assurance and Quality Control (QA/QC). With over nine years of combined teaching and industry exposure, she has significantly contributed to engineering education, laboratory development, project execution, and applied research in sustainable construction materials. Her academic tenure includes impactful roles at Nitte Meenakshi Institute of Technology, Dayananda Sagar College of Engineering, and BTL Institute of Technology and Management, where she strengthened curriculum delivery, advanced laboratory infrastructure, and supported institutional development. Her research focuses on Geopolymer Concrete, sustainable materials, and modern construction technologies, reflecting her commitment to environmental responsibility and innovative engineering practices. She has published ten research papers, including contributions in Q2, Q3, and Q4 journals, and presented her work at eight national and international conferences. Her scholarly excellence has been recognized through multiple awards, including Best Paper Presentation at ICCSI 2024 and a Research Award for Journal Publications at NMIT. In the engineering domain, she has served in QA/QC and site engineering roles, managing material procurement, batching, testing, safety compliance, and process optimization for major construction projects. She contributed to the execution of large-scale works such as building facilities and commercial complexes, demonstrating precision in quality oversight and project coordination. She has also guided numerous student projects in geopolymer concrete and sustainable construction technologies, fostering innovation among emerging engineers. With expertise spanning project management, engineering design, laboratory establishment, and academic leadership, she continues to advance research and teaching in civil engineering.

Profile: Google Scholar

Featured Publications

  • Moulya, H. V., & Chandrashekhar, A. (2022). Experimental investigation of effect of recycled coarse aggregate properties on the mechanical and durability characteristics of geopolymer concrete. Materials Today: Proceedings, 59, 1700–1707.

  • Moulya, H. V., Vasu, V. K., Praveena, B. A., Rajesh, M., Ruthuparna, S. A., & Rahul, K. (2022). Study on acoustic properties of polyester–fly ash cenosphere/nanographene composites. Materials Today: Proceedings, 52, 1272–1277.

  • Choudhari, R. M., Kharche, N. A., Shekokar, S. R., Kharche, Y. A., Kharat, D. P., … Moulya, H. V. (2025). Examining dielectric constant improvement techniques for ferroelectric applications using PVDF-HFP/TFO composite films. Journal of Materials Science: Materials in Engineering, 20(1), 137.

  • Moulya, M. H. V. (2025). Self-healing concrete using nanomaterials to extend infrastructure longevity.

  • Moulya, M. H. V., Chandrashekhar, A., & Angadi, S. V. (2024). Geopolymer recycling process for sustainable construction materials management. B. Nitte Meenakshi Institute of Technology.

Yakshansh Kumar | Engineering | Best Researcher Award

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Mr. Yakshansh Kumar | Engineering | Best Researcher Award

Mr. Yakshansh Kumar, Delhi Technological University, India

Yakshansh Kumar is a highly motivated researcher and academician in the field of Civil Engineering, with a specialization in Pavement-Soil Dynamics. Currently pursuing his PhD at Delhi Technological University, he focuses on dynamic response analysis of pavement-soil systems using piezo sensors. He has actively contributed to several publications and international conferences, establishing himself as a promising expert in geotechnical engineering. Passionate about advancing knowledge and fostering innovation, Yakshansh is also involved in mentoring students and advancing research projects. His dedication and commitment are evident in his academic achievements and research pursuits.

Professional Profile

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Summary of Suitability for the “Research for Best Researcher Award”

Yakshansh Kumar is a promising and dedicated researcher with a strong academic foundation and a demonstrated commitment to advancing the field of civil and geotechnical engineering, particularly in pavement-soil dynamics. Currently pursuing a Ph.D. at Delhi Technological University, his research focus on dynamic response analysis of pavement-soil systems using piezo sensors exemplifies his innovative approach to solving complex engineering challenges. His research is not only theoretically robust but also applied, with funding from the university’s IRD and the use of experimental testing and finite element analysis in his investigations.

Kumar’s publication record is impressive, with multiple articles in high-impact journals such as International Journal of Non-Linear Mechanics (SCIE, Q1) and Journal of Vibration Engineering and Technologies (SCIE, Q2). He has contributed to the scientific community with key insights on dynamic load vibrations, piezo-dynamics, and the role of machine learning in geotechnical analysis. His research has garnered attention on both national and international platforms, demonstrated by his active participation in numerous conferences, where he has won awards for best technical papers.

🎓  Education

Yakshansh Kumar holds a PhD in Civil Engineering from Delhi Technological University (DTU), where he is conducting research on the dynamic analysis of pavement-soil systems. He earned his Master’s degree in Geotechnical Engineering from DTU, achieving a CGPA of 7.49. He completed his Bachelor’s degree in Civil Engineering at Hindu College of Engineering (affiliated with DCRUSTM) with a CGPA of 6.37. Throughout his academic career, Yakshansh has demonstrated a strong foundation in engineering principles, with a specific interest in soil dynamics and pavement systems. His rigorous research work has led to multiple scholarly contributions in well-regarded journals and international conferences.

💼 Professional Experience

Yakshansh Kumar has an extensive academic and research background. He is currently working on his PhD project, funded by the IRD-DTU, which focuses on pavement-soil dynamics using piezo sensors for experimental testing and finite element analysis. As part of his professional journey, Yakshansh has contributed to several research papers, conferences, and has collaborated with experts in geotechnical engineering. He has also participated as a reviewer in esteemed journals such as Transportation Infrastructure Geotechnology. In addition to his research, he has attended workshops and seminars, including a national seminar on Science Day and faculty development programs, showcasing his dedication to continuous learning. His involvement in teaching and research continues to shape his career path.

🏅  Awards and Recognition

Yakshansh Kumar has been recognized for his outstanding contributions to research and academic excellence. He was awarded the Best Technical Paper Award for his work on “Velocity Induced Post Elastic Response of Pavements” presented at the Sustainable Infrastructure: Innovations, Opportunities, and Challenges (SIIOC 2024). In addition, his paper on “Post Elastic Response of Pavement Subjected to Moving Load” received the Best Paper Award at the International Online Conference on Energy Science (ICES 2021). His work has been published in high-impact journals such as the International Journal of Non-Linear Mechanics and Journal of Vibration Engineering and Technologies. He has also been recognized as a reviewer for journals and international conferences, reflecting his academic credibility and recognition in the field of geotechnical engineering.

🌍 Research Skills On Engineering

Yakshansh Kumar possesses strong research skills, particularly in the areas of pavement-soil dynamics, finite element analysis, and piezo-dynamics of geomaterials. His expertise lies in dynamic response analysis using experimental testing and numerical modeling. His ongoing PhD project focuses on piezo sensors and their application to pavement systems, supported by funding from IRD-DTU. Yakshansh has demonstrated his proficiency in using advanced software for computational modeling and simulations, as well as conducting real-world experimental tests. His research contributes to understanding the behavior of pavements under dynamic loads, which is vital for improving infrastructure performance. His skills are complemented by his ability to collaborate with peers, present research at conferences, and publish in well-regarded journals.

📖 Publication Top Notes

  • Damage evaluation in pavement-geomaterial system using finite element-scaled accelerated pavement testing

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2023). Damage evaluation in pavement-geomaterial system using finite element-scaled accelerated pavement testing. Transportation Infrastructure Geotechnology, 11(3), 922-933.
    • Year: 2023

  • Damage evaluation in pavement-geomaterial system using finite element-scaled accelerated pavement testing

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2024). Damage evaluation in pavement-geomaterial system using finite element-scaled accelerated pavement testing. Transportation Infrastructure Geotechnology, 11(3), 922-933.
    • Year: 2024

  • Deflections governed by the cyclic strength of rigid pavement subjected to structural vibration due to high-velocity moving loads

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2024). Deflections governed by the cyclic strength of rigid pavement subjected to structural vibration due to high-velocity moving loads. Journal of Vibration Engineering & Technologies, 12(3), 3543-3562.
    • Year: 2024

  • Investigating the Influence of Frequency on Piezo-dynamics of Polyvinylidene Fluoride (PVDF) Films Embedded in Confined Geomaterials

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2024). Investigating the Influence of Frequency on Piezo-dynamics of Polyvinylidene Fluoride (PVDF) Films Embedded in Confined Geomaterials. Journal of Vibration Engineering & Technologies, 1-20.
    • Year: 2024

  • Application of machine learning technique for dynamic analysis of confined geomaterial subjected to vibratory load

    • Authors: A Boban, P Pateriya, Y Kumar, K Gaur, A Trivedi
    • Citation: Boban, A., Pateriya, P., Kumar, Y., Gaur, K., & Trivedi, A. (2024). Application of machine learning technique for dynamic analysis of confined geomaterial subjected to vibratory load. AI in Civil Engineering, 3(1), 2.
    • Year: 2024

  • Influence of Jute Reinforcement on the Stiffness Capacity of Cohesionless Pavement Geomaterials

    • Authors: P Kumar, Y Kumar, A Trivedi
    • Citation: Kumar, P., Kumar, Y., & Trivedi, A. (2023). Influence of Jute Reinforcement on the Stiffness Capacity of Cohesionless Pavement Geomaterials. International Conference on Interdisciplinary Approaches in Civil Engineering.
    • Year: 2023

  • Numerical and Experimental Investigation of a Confined Geomaterial Subjected to Vibratory Load

    • Authors: A Boban, Y Kumar, A Trivedi
    • Citation: Boban, A., Kumar, Y., & Trivedi, A. (2023). Numerical and Experimental Investigation of a Confined Geomaterial Subjected to Vibratory Load. International Conference on Sustainable Infrastructure: Innovation.
    • Year: 2023

  • Impact of Moving Load Vibrations on Pavement Damage Supported by Flow-Controlled Geomaterials

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2024). Impact of Moving Load Vibrations on Pavement Damage Supported by Flow-Controlled Geomaterials. Available at SSRN 5002829.
    • Year: 2024

Karthik K | Engineering | Best Researcher Award

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Dr. Karthik K | Engineering | Best Researcher Award

Dr. Karthik K, Vellore Institute of Technology, Vellore, India

Karthik K is an accomplished academician and researcher specializing in computer vision, deep learning, and medical imaging. With over a decade of experience in teaching and research, he has contributed significantly to the field of artificial intelligence in healthcare applications. Currently serving as an Assistant Professor Sr Grade I at Vellore Institute of Technology, Vellore, he has previously worked at St. Joseph Engineering College and NITK, Surathkal. His research is backed by strong academic credentials, numerous publications, and active collaborations with esteemed institutions like NITK, NITPy, and VIT AP. Karthik has received the VIT Seed Grant for AI-driven cricket commentary generation and has applied for prestigious research grants. His contributions to automated medical scan quality enhancement and content-based medical image retrieval have been widely recognized. An active IEEE and IAENG member, he continues to drive innovation in AI and deep learning for intelligent healthcare applications.

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Evaluation of Dr. Karthik K for the Research for Best Researcher Award

Dr. Karthik K, currently an Assistant Professor Sr. Grade I at the Vellore Institute of Technology (VIT), has demonstrated strong research contributions in the fields of computer vision, deep learning, and medical imaging. His research spans content-based medical image retrieval, automated radiography report retrieval, and deep learning-based medical scan quality enhancement, which have direct applications in intelligent healthcare systems. With six journal publications in SCI and Scopus-indexed journals, along with 145 citations, his academic impact is notable.

In addition to his research, Dr. Karthik has published book chapters, submitted a patent, and collaborated with reputed institutions such as NITK, NITPy, and VIT AP. His contributions to AI-driven healthcare applications, particularly in medical image classification and enhancement, showcase his innovative approach to solving real-world medical challenges. Furthermore, his ongoing VIT Seed Grant project on AI-generated cricket commentary and a DST-SURE research grant under review indicate his continued commitment to advancing AI applications across multiple domains.

🎓 Education 

Karthik K has built a strong academic foundation in the fields of computer science and engineering. He pursued his Bachelor’s and Master’s degrees with a focus on artificial intelligence, deep learning, and medical imaging. His research interests led him to work as a Research Fellow at NITK Surathkal, where he contributed to the DST-ECR-funded project on deep learning frameworks for intelligent healthcare applications. During his tenure, he gained extensive expertise in content-based medical image retrieval and automated medical scan enhancements. His academic journey has been marked by continuous learning and contributions to research, with publications in renowned journals and conferences. Karthik’s passion for AI-driven innovations is evident in his scholarly work, patents, and ongoing research projects. His educational background has laid the foundation for his teaching and research career, equipping him with the knowledge and skills to drive advancements in AI, deep learning, and medical imaging applications.

💼 Professional Experience 

Karthik K brings over 10 years of experience in academia and research. He is currently an Assistant Professor Sr Grade I at Vellore Institute of Technology, Vellore, where he specializes in AI, computer vision, and medical imaging. Prior to this, he was an Assistant Professor at St. Joseph Engineering College, Vamanjoor, Mangaluru (2020–2023) and an Assistant Lecturer at NITK, Surathkal (2015–2017). His professional journey includes a research fellowship at NITK Surathkal, where he worked on a DST-ECR-funded project developing deep learning frameworks for intelligent healthcare. Karthik has contributed significantly to AI-driven innovations, collaborating with institutions like NITK, NITPy, and VIT AP. His expertise extends to consultancy projects, editorial appointments, and patents. He has published extensively in SCI and Scopus-indexed journals and remains actively involved in advancing deep learning applications for medical imaging, making significant contributions to academia and industry collaborations.

🏅 Awards and Recognition

Karthik K has been recognized for his contributions to artificial intelligence and medical imaging research. He received the VIT Seed Grant (2023–2025) for his innovative project on AI-driven cricket commentary generation. Additionally, he has applied for the DST-SURE research grant, currently under review. His work in content-based medical image retrieval and deep neural networks for healthcare applications has been acknowledged in multiple international journals and conferences. Karthik has published several book chapters with ISBN numbers, showcasing his expertise in AI and deep learning. He actively collaborates with esteemed institutions and has been invited for editorial appointments in reputed journals. His research contributions have earned him membership in professional organizations such as IEEE and IAENG. With over 145 citations in SCI and Scopus-indexed publications, his work continues to impact the field of intelligent healthcare applications. His commitment to research excellence makes him a strong contender for prestigious awards.

🌍 Research Skills On Engineering

Karthik K possesses extensive research skills in computer vision, deep learning, and medical imaging. His expertise includes developing AI-driven frameworks for intelligent healthcare applications, enhancing medical scan quality, and implementing deep neural networks for automated medical image retrieval. He has successfully led research projects, including a DST-ECR-funded initiative at NITK Surathkal and ongoing consultancy projects. His ability to integrate AI with real-world healthcare challenges has resulted in significant innovations such as ViewNet for scan orientation and automated radiography report retrieval. Karthik’s research has been published in SCI and Scopus-indexed journals, contributing to the broader scientific community. He is skilled in grant writing, patent filing, and interdisciplinary collaborations, with active partnerships with NITK, NITPy, and VIT AP. His research acumen, combined with hands-on experience in deep learning and AI applications, positions him as a leader in advancing intelligent healthcare solutions through cutting-edge technology.

 📖 Publication Top Notes

  • Title: A deep neural network model for content-based medical image retrieval with multi-view classification
    Authors: K Karthik, SS Kamath
    Citation: 60
    Year: 2021
  • Title: A hybrid feature modeling approach for content-based medical image retrieval
    Authors: K Karthik, SS Kamath
    Citation: 16
    Year: 2018
  • Title: COVIDDX: AI-based Clinical Decision Support System for Learning COVID-19 Disease Representations from Multimodal Patient Data
    Authors: V Mayya, K Karthik, KS Sowmya, K Karadka, J Jeganathan
    Citation: 13
    Year: 2021
  • Title: Analysis and prediction of fantasy cricket contest winners using machine learning techniques
    Authors: K Karthik, GS Krishnan, S Shetty, SS Bankapur, RP Kolkar, TS Ashwin, …
    Citation: 13
    Year: 2021
  • Title: MSDNet: A deep neural ensemble model for abnormality detection and classification of plain radiographs
    Authors: K Karthik, S Sowmya Kamath
    Citation: 12
    Year: 2023
  • Title: Deep neural models for automated multi-task diagnostic scan management—quality enhancement, view classification and report generation
    Authors: K Karthik, S Kamath
    Citation: 12
    Year: 2021
  • Title: Automatic quality enhancement of medical diagnostic scans with deep neural image super-resolution models
    Authors: K Karthik, SS Kamath, SU Kamath
    Citation: 6
    Year: 2020
  • Title: An automated robotic arm: a machine learning approach
    Authors: NSK Rao, NJ Avinash, HR Moorthy, K Karthik, S Rao, S Santosh
    Citation: 5
    Year: 2021
  • Title: Automated view orientation classification for x-ray images using deep neural networks
    Authors: K Karthik, S Kamath
    Citation: 3
    Year: 2021
  • Title: GAN-Based Encoder-Decoder Model for Multi-Label Diagnostic Scan Classification and Automated Radiology Report Generation
    Authors: R Kumar, K Karthik, SS Kamath
    Citation: 3

AWAIS KHAN | Engineering | Best Researcher Award

Published on by Academic Excellence

Assist. Prof. Dr. AWAIS KHAN | Engineering | Best Researcher Award

👤 Assist. Prof. Dr. AWAIS KHAN, Beijing Institute of Technology Zhuhai Campus, China

Dr. Awais Khan is an Assistant Professor at the Beijing Institute of Technology, Zhuhai Campus, specializing in advanced control systems, renewable energy technologies, and interval observers. With a PhD in Control Theory and Control Engineering from South China University of Technology, Dr. Khan has made significant contributions to mechatronics and control engineering during his tenure as a Postdoctoral Research Fellow at Shenzhen University. His research is recognized for its innovative approach, particularly in the application of control systems in energy-efficient technologies. A prolific researcher and published author, Dr. Khan has been actively involved in securing research funding and publishing in top-tier journals. His passion for both teaching and research allows him to foster a dynamic learning environment for students while contributing to the advancement of technology in engineering and energy sectors.

Professional Profile

Google Scholar

🌟 Summary of Suitability for the Research for Best Researcher Award

Awais Khan’s impressive academic background and research trajectory make him highly suitable for the Research for Best Researcher Award. He currently serves as an Assistant Professor at the Beijing Institute of Technology, where he leads cutting-edge research in advanced control systems, renewable energy technologies, and interval observers. His teaching excellence, combined with his groundbreaking research contributions, aligns well with the award’s criteria, which honors those making significant academic and technological advancements.

Awais Khan’s postdoctoral experience at Shenzhen University further solidifies his research prowess, particularly in mechatronics and control engineering. His work has been recognized in reputable journals, with a consistent record of impactful publications in high-impact platforms such as IEEE Transactions and the Journal of the Franklin Institute. He has demonstrated leadership in securing research funding and fostering interdisciplinary collaboration.

🎓   Education 

Dr. Awais Khan holds a PhD in Control Theory and Control Engineering from the South China University of Technology (2016–2020), where his research focused on interval observers and their applications to control theory. Prior to that, he earned a Master’s degree in Electrical Engineering from the University of Engineering and Technology (UET) Lahore (2014–2016). Dr. Khan’s academic journey began with a Bachelor of Science in Electronics Engineering from UET Peshawar (2009–2013), which laid the foundation for his expertise in engineering and control systems. Throughout his academic career, he has received several scholarships, including the prestigious Chinese Government Scholarship for his PhD studies. His educational background is complemented by his active participation in various research projects, workshops, and technical conferences, enabling him to stay at the forefront of advancements in control systems, renewable energy technologies, and energy-efficient engineering solutions.

💼   Professional Experience 

Since 2022, Dr. Awais Khan has been an Assistant Professor at the Beijing Institute of Technology, Zhuhai Campus, where he teaches a range of courses, including C/C++, Probability & Statistical Analysis, Circuits & Electronics, and Physics. His role involves both delivering high-quality lectures and conducting groundbreaking research in advanced control systems, renewable energy, and interval observers. Prior to this, Dr. Khan was a Postdoctoral Research Fellow at Shenzhen University (2020–2022), where he worked on mechatronics and control engineering, developing innovative technologies in interdisciplinary research collaborations. His work on interval observers for nonlinear systems garnered attention, leading to publications in reputable journals. Dr. Khan has also contributed to National Natural Science Foundation of China projects, enhancing the understanding of control systems in uncertain environments. His teaching and research experience are central to his contributions to the field, shaping future engineers and advancing the integration of energy-efficient technologies.

🏅 Awards and Recognition 

Dr. Awais Khan has been recognized for his outstanding contributions to control systems and engineering through several prestigious awards and honors. Notably, he received the Best Presentation Award at the EECR in 2018, reflecting his excellence in research communication. His doctoral research, supported by the Chinese Government Scholarship, marked a milestone in the development of interval observers for linear and nonlinear systems. In addition, Dr. Khan serves as an editor for Technological Innovations & Energy and has been an active member of professional organizations, such as the IEEE and the International Association of Engineers, since 2024. His scholarly work has been widely recognized, with numerous publications in leading journals and conferences. He continues to secure research grants, supporting the advancement of innovative technologies in control systems and energy efficiency. Dr. Khan’s contributions to both academia and the engineering community have made him a respected figure in the field.

🌍  Research Skills On Engineering

Dr. Awais Khan possesses a deep proficiency in advanced control systems, renewable energy technologies, and interval observers. His research expertise spans control theory, nonlinear systems, and energy-efficient technologies, focusing on their applications in both academia and industry. With a strong background in mechatronics and control engineering, he has developed innovative solutions for system stability and energy optimization. Dr. Khan is skilled in designing interval observers for dynamic systems, particularly in uncertain environments, and has published extensively on the subject. His work also explores adaptive control strategies for robotics and power systems, leveraging cutting-edge technologies such as SiC and GaN. Dr. Khan is proficient in several programming languages, including Matlab, Simulink, Python, and C/C++, enabling him to implement complex models and simulations for his research. His skills in interdisciplinary collaboration and securing funding for research projects further highlight his versatility and commitment to advancing technological solutions in engineering.

 📖 Publication Top Notes

  • A survey of interval observers design methods and implementation for uncertain systems
    A Khan, W Xie, Z Bo, LW Liu
    Journal of the Franklin Institute, 358(6), 3077-3126, 2021
    Citation: 52
  • Design and Applications of Interval Observers for Uncertain Dynamical Systems
    A Khan, W Xie, Z Langwen, LW Liu
    IET Circuits, Devices & Systems, 14(6), 721-740, 2020
    Citation: 48
  • Path Planning for Wheeled Mobile Robot in Partially Known Uneven Terrain
    B Zhang, G Li, Q Zheng, X Bai, Y Ding, A Khan
    Sensors, 22(14), 5217, 2022
    Citation: 41
  • Finite‐time nonsingular terminal sliding mode control of converter‐driven DC motor system subject to unmatched disturbances
    A Rauf, M Zafran, A Khan, AR Tariq
    International Transactions on Electrical Energy Systems, 31(11), e13070, 2021
    Citation: 26
  • Interval state estimation for linear time-varying (LTV) discrete-time systems subject to component faults and uncertainties
    A Khan, W Xie, L Zhang, Ihsanullah
    Archives of Control Sciences, 29(2), 289-305, 2019
    Citation: 22
  • Set-Membership Interval State Estimator Design Using Observability Matrix for Discrete-Time Switched Linear Systems
    A Khan, LW Liu, W Xie
    IEEE Sensors Journal, 20(11), 6121-6129, 2020
    Citation: 20
  • Interval State Estimator Design for Linear Parameter Varying (LPV) Systems
    A Khan, X Bai, Z Bo, P Yan
    IEEE Transactions on Circuits and Systems II: Express Briefs, 68(8), 2865-2869, 2021
    Citation: 19
  • Finite‐time functional interval observer for linear systems with uncertainties
    L Liu, W Xie, A Khan, L Zhang
    IET Control Theory & Applications, 14(18), 2868-2878, 2020
    Citation: 14
  • Fault detection and diagnosis for a class of linear time-varying (LTV) discrete-time uncertain systems using interval observers
    Z Yi, W Xie, A Khan, B Xu
    2020 39th Chinese Control Conference (CCC), 4124-4128, 2020
    Citation: 14
  • Interval State Estimator Design Using the Observability Matrix for Multiple Input Multiple Output Linear Time-Varying Discrete-Time Systems
    A Khan, W Xie
    IEEE Access, 7, 167566-167576, 2019
    Citation: 13