Yogesh Shankar | Engineering | Innovative Research Award

Published on by Academic Excellence

Innovative Research Award

Yogesh shankar
Infineon Technologies Asia Pacific, Singapore

Yogesh shankar
Affiliation Infineon Technologies Asia Pacific
Country Singapore
Scopus ID 57215433281
Documents 2
Citations 21
h-index 2
Subject Area Engineering
Event International Academic Excellence Awards

Yogesh shankar is an engineering researcher associated with Infineon Technologies Asia Pacific in Singapore. The supplied indexed record identifies research involving radar-based sensing, non-intrusive motion recognition, and deformable convolutional neural networks. The available bibliometric information reports two documents, 21 citations, and an h-index of 2. The documented publication record provides a focused example of applying deep-learning methods to sensing and recognition problems. [1]

Abstract

The supplied research profile concerns engineering applications of intelligent sensing and machine learning. Its identified publication, presented at the 18th IEEE International Conference on Machine Learning and Applications in 2019, investigates radar-based non-intrusive fall motion recognition using a deformable convolutional neural network. Such work combines radar sensing with deep-learning-based recognition, addressing the computational interpretation of motion without relying on direct physical contact. [2]

Keywords

Engineering; radar sensing; fall recognition; motion recognition; deep learning; convolutional neural networks; deformable convolution; non-intrusive sensing; machine learning; intelligent systems.

Introduction

Radar-based sensing provides a means of observing movement without requiring conventional wearable or contact-based instrumentation. Within this context, machine learning can be used to extract patterns from radar-derived information and classify specific human activities. The documented work by yogesh shankar and collaborators applies a deformable convolutional neural network to fall-motion recognition, placing the research at the intersection of radar sensing, signal interpretation, and artificial intelligence. [2]

Research Profile

The stated subject area is Engineering, with the available publication evidence specifically connected to machine learning and sensing applications. The supplied profile reports two documents, 21 citations, and an h-index of 2. These bibliometric indicators represent the supplied database snapshot and may change as additional publications and citations are indexed. [1]

Research Contributions

  • Investigation of radar-based non-intrusive sensing for human fall-motion recognition. [2]
  • Application of deformable convolutional neural networks to motion-recognition tasks. [2]
  • Integration of radar sensing and deep-learning-based computational recognition within an engineering research context.

Publications

Radar-based non-intrusive fall motion recognition using deformable convolutional neural network was published as a conference paper in the Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). The listed authors are Y. Shankar, Yogesh Shankar, Souvik Hazra, and Avik Santra. The supplied record reports 12 citations for this publication. [2]

Research Impact

The supplied Scopus information reports 21 citations across two documents and an h-index of 2. The identified conference paper accounts for 12 citations in the supplied results. Citation counts are dynamic bibliometric measures and can differ between indexing services; therefore, they are best interpreted as indicators of documented scholarly visibility rather than as a complete measure of research significance. [1] [2]

Award Suitability

The documented publication provides evidence of research activity relevant to an Innovative Research Award within the Engineering subject area. Its focus on radar-based non-intrusive sensing and deformable convolutional neural networks represents an application of contemporary computational methods to human-motion recognition. Consideration for an award should be made alongside the complete research record and the applicable criteria of the International Academic Excellence Awards.

Conclusion

yogesh shankar’s supplied academic record demonstrates focused research at the intersection of engineering, radar sensing, and machine learning. The documented work on non-intrusive fall-motion recognition illustrates the use of deformable convolutional neural networks in an applied sensing context. The available bibliometric indicators and publication evidence provide a concise basis for academic recognition within the International Academic Excellence Awards framework.

References

  1. Elsevier. (n.d.). Scopus author details: Yogesh Shankar, Author ID 57215433281. Scopus. The supplied Scopus record reports two documents, 21 citations, and an h-index of 2.
  2. Shankar, Y., Shankar, Y., Hazra, S., & Santra, A. (2019). Radar-based non-intrusive fall motion recognition using deformable convolutional neural network. Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). The supplied record reports 12 citations.
  3. IEEE. (2019). 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). Conference publication record associated with the documented research.
  4. International Academic Excellence Awards. (n.d.). Academic Excellence Awards.
    https://academicexcellenceawards.com/

Isaac Akinwumi | Civil Engineering | Academic Excellence Award

Published on by Academic Excellence

Academic Excellence Award

Isaac Akinwumi
Covenant University,Nigeria

Isaac Akinwumi
Affiliation Covenant University
Country Nigeria
Scopus ID 55923337600
Documents 65
Citations 1,205
h-index 20
Subject Area Civil Engineering
Event International Academic Excellence Awards
ORCID 0000-0003-3053-8189

Isaac Akinwumi is a researcher affiliated with Covenant University, Nigeria, whose documented academic profile is associated with civil engineering. The available researcher identifiers provide a basis for distinguishing his scholarly record across major research-information platforms. According to the supplied Scopus profile data, the record contains 65 documents, 1,205 citations, and an h-index of 20. [1]

Abstract

The Academic Excellence Award profile recognizes the documented scholarly record of Isaac Akinwumi of Covenant University, Nigeria. His supplied bibliometric information identifies 65 research documents, 1,205 citations, and an h-index of 20 in Scopus. [1] The profile is situated within civil engineering and provides a concise academic overview based on researcher identifiers and publicly associated scholarly records.

Keywords

Isaac Akinwumi; Academic Excellence Award; Civil Engineering; Covenant University; Nigeria; Scopus; ORCID; Research Impact; Scholarly Publications; Academic Recognition.

Introduction

Academic recognition commonly considers evidence such as scholarly publications, citations, research visibility, and persistent researcher identifiers. For Isaac Akinwumi, the supplied bibliometric indicators provide measurable information for describing his research profile. Scopus and ORCID identifiers also support more consistent attribution of scholarly work. [1] [2]

Research Profile

The supplied profile places Akinwumi’s research within civil engineering and records an affiliation with Covenant University. His Scopus author identifier is 55923337600, while his ORCID identifier is 0000-0003-3053-8189. [1] [2] These persistent identifiers can assist readers in locating and distinguishing his scholarly output.

Research Contributions

The documented publication count and citation indicators provide quantitative measures through which Akinwumi’s research activity can be described. The available information does not, by itself, establish the substantive findings of individual studies; therefore, specific contributions should be evaluated through the underlying publications and their respective bibliographic records.

Publications

The supplied Scopus record lists 65 documents associated with the researcher profile. [1] Individual publication titles, journals, publication years, and DOI identifiers should be verified against the relevant publisher or indexing record before being cited independently.

Research Impact

The supplied Scopus metrics report 1,205 citations and an h-index of 20. [1] These indicators describe citation activity associated with the indexed author record. Citation counts can change over time as databases add, remove, merge, or update records.

Award Suitability

The Academic Excellence Award profile is supported by the supplied evidence of scholarly activity, including 65 indexed documents, 1,205 citations, and an h-index of 20. [1] The International Academic Excellence Awards provides the stated event context for this recognition. [4]

Conclusion

Isaac Akinwumi’s academic profile is associated with Covenant University and civil engineering, with the supplied Scopus record documenting 65 documents, 1,205 citations, and an h-index of 20. [1] These indicators provide a concise quantitative description of his indexed research activity and form the principal evidence presented in this academic recognition profile.

References

  1. Elsevier. (n.d.). Scopus author details: Isaac Akinwumi, Author ID 55923337600. Scopus.https://www.scopus.com/authid/detail.uri?authorId=55923337600
  2. ORCID. (n.d.). Isaac Akinwumi, ORCID iD 0000-0003-3053-8189.https://orcid.org/0000-0003-3053-8189
  3. Google Scholar. (n.d.). Isaac Akinwumi, Google Scholar profile.https://scholar.google.com/citations?user=LQMdAjEAAAAJ&hl=en&oi=sra
  4. International Academic Excellence Awards. (n.d.). Academic Excellence Awards.https://academicexcellenceawards.com/

Chang Gao | Engineering | Best Researcher Award

Published on by Academic Excellence

Mrs. Chang Gao | Engineering | Best Researcher Award

👤 Mrs. Chang Gao, Changsha University of Science and Technology, China

Chang Gao is an accomplished researcher and educator based in China, specializing in civil engineering and material sciences. With a strong academic foundation, he obtained his Bachelor’s degree in Civil Engineering from Hunan University and further advanced his expertise with a Ph.D. in Civil Engineering from the same institution. His innovative research spans high-performance concrete materials, eco-friendly construction methods, and machine learning applications in engineering. Currently, Chang serves as an Assistant Professor in the Intelligent Construction Department at Changsha University of Science and Technology while also pursuing postdoctoral research at Southeast University and Hunan University. His exceptional contributions to academia and industry have been recognized through prestigious awards, including the Third Prize of the Science and Technology Award by the China Circular Economy Association. Chang’s dedication to sustainable practices and cutting-edge research underscores his impact on the field of engineering.

Professional Profile

Orcid

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

Dr. Chang Gao’s impressive academic and professional accomplishments establish him as a strong candidate for the “Research for Best Researcher Award.” His expertise lies in Civil Engineering, with a particular focus on innovative and eco-friendly concrete materials, shrinkage and creep behavior, and machine learning applications in construction materials. His contributions are evident through his impactful research, as highlighted in numerous peer-reviewed publications in reputable journals such as the Journal of Building Engineering, Construction and Building Materials, and the Journal of Materials Research and Technology.

Dr. Gao’s multidisciplinary approach, blending traditional civil engineering with advanced technologies like machine learning, sets him apart as a forward-thinking researcher. His work on recycled aggregate concrete and nanoparticles demonstrates a commitment to sustainable engineering solutions, addressing critical global challenges like resource efficiency and environmental impact.

🎓 Education

Chang Gao has a robust educational background in civil engineering, beginning with a Bachelor’s degree from Hunan University in 2014. Demonstrating exceptional academic performance, he pursued a Ph.D. in Civil Engineering at the same university, graduating in 2019. During his Ph.D. journey, Chang’s research focused on eco-friendly construction materials and the integration of machine learning in structural analysis. To broaden his expertise, he completed another doctoral program in Aeronautics and Astronautics Engineering at Purdue University in 2019, showcasing his interdisciplinary capabilities. This diverse academic experience not only honed his technical skills but also instilled a profound understanding of sustainable and advanced construction practices. With a passion for innovation and academic excellence, Chang has built a solid foundation to lead pioneering research and mentor the next generation of engineers.

💼  Professional Experience

Chang Gao’s professional journey reflects his dedication to advancing engineering practices. Since September 2022, he has served as an Assistant Professor in the Intelligent Construction Department of Civil Engineering at Changsha University of Science and Technology, where he actively contributes to academia through teaching and research. Simultaneously, Chang is a postdoctoral researcher at Southeast University, specializing in high-performance concrete materials, shrinkage and creep analysis, and the application of machine learning in construction engineering. Previously, he conducted postdoctoral research at Hunan University from December 2019 to September 2022, focusing on eco-friendly concrete and composite material improvements. Chang’s professional accomplishments are underpinned by his innovative approach, collaborative mindset, and dedication to sustainable construction solutions. His extensive experience bridges academia and industry, making him a prominent figure in civil engineering.

🏅 Awards and Recognitions

Chang Gao’s exemplary contributions to engineering have earned him multiple accolades. He was honored with the Third Prize in the Science and Technology Award from the China Circular Economy Association, recognizing his innovative research in sustainable materials. Additionally, he received funding from the Youth Program of the National Natural Science Foundation of China (Grant No. 52308233, 2023) and the Youth Program of the Hunan Province Natural Science Foundation of China (Grant No. 2022JJ40062, 2022). These awards highlight Chang’s commitment to advancing eco-friendly construction practices and integrating cutting-edge technologies into civil engineering. His achievements underscore his leadership and innovation in the field, inspiring peers and students alike to pursue excellence in engineering research and sustainable development.

🌍  Research Skills On Engineering

Chang Gao possesses advanced research skills in civil engineering and materials science, with a focus on sustainable and high-performance construction materials. His expertise includes the development of eco-friendly concrete materials, composite improvements, and shrinkage and creep analysis. He is proficient in leveraging machine learning techniques to evaluate the mechanical properties and performance of recycled aggregate concrete, demonstrating his ability to integrate technology into engineering research. Chang’s work also explores nanotechnology applications in material modification, further enhancing the durability and efficiency of construction materials. His interdisciplinary approach combines practical problem-solving with theoretical rigor, enabling him to produce innovative solutions for modern engineering challenges. Chang’s research skills are complemented by his strong analytical capabilities and collaborative mindset, making him a leader in advancing sustainable construction practices.

📖 Publication Top Notes

  • Simulation and numerical analysis of the seismic performance of the quick repaired seismic-damaged RC frame
    • Authors: Chang Gao, Liang Huang, Lei Wang, Qiang Sun, Yin Li
    • Journal: Soil Dynamics and Earthquake Engineering
    • Year: 2025
    • DOI: 10.1016/j.soildyn.2024.109083
  • Creep behavior evaluation of recycled aggregate concrete using machine learning technology
    • Authors: Chang Gao, Chuyu Luo, Bin Zhang, Zhangli Hu, Jinhui Tang, Lei Wang, Jiaping Liu
    • Journal: Journal of Building Engineering
    • Year: 2024
    • DOI: 10.1016/j.jobe.2024.111538
  • Axial compressive behavior of steel reinforced GGBS-RFBP-FA ternary composite geopolymer recycled fireclay brick aggregates concrete columns
    • Authors: Yin Li, Liang Huang, Chang Gao, Yiqun Qu, Xiaofeng Luo, Bodong Lv, Zhijun Chen
    • Journal: Structures
    • Year: 2024
    • DOI: 10.1016/j.istruc.2024.105913
  • Workability and mechanical properties of GGBS-RFBP-FA ternary composite geopolymer concrete with recycled aggregates containing recycled fireclay brick aggregates
    • Authors: Yin Li, Liang Huang, Chang Gao, Zhijie Mao, Mingzhu Qin
    • Journal: Construction and Building Materials
    • Year: 2023
    • DOI: 10.1016/j.conbuildmat.2023.131450
  • Jute Fiber-Reinforced Polymer Tube-Confined Sisal Fiber-Reinforced Recycled Aggregate Concrete Waste
    • Authors: Chang Gao, Qiu Ni Fu, Liang Huang, Libo Yan, Guangming Gu
    • Journal: Polymers
    • Year: 2022
    • DOI: 10.3390/polym14061260
  • Compressive performance of fiber reinforced polymer encased recycled concrete with nanoparticles
    • Authors: Chang Gao, Liang Huang, Libo Yan, Bohumil Kasal, Wengui Li, Ruoyu Jin, Yutong Wang, Yin Li, Peng Deng
    • Journal: Journal of Materials Research and Technology
    • Year: 2021
    • DOI: 10.1016/j.jmrt.2021.07.159
  • Flax FRP tube and steel spiral dual-confined recycled aggregate concrete: Experimental and analytical studies
    • Authors: Liang Huang, Jinmei Liang, Chang Gao, Libo Yan
    • Journal: Construction and Building Materials
    • Year: 2021
    • DOI: 10.1016/j.conbuildmat.2021.124023
  • Mechanical properties of recycled aggregate concrete modified by nano-particles
    • Authors: Chang Gao, Liang Huang, Libo Yan, Ruoyu Jin, Haoze Chen
    • Journal: Construction and Building Materials
    • Year: 2020
    • DOI: 10.1016/j.conbuildmat.2020.118030
  • Strength and ductility improvement of recycled aggregate concrete by polyester FRP-PVC tube confinement
    • Authors: Chang Gao, Liang Huang, Libo Yan, Ruoyu Jin, Bohumil Kasal
    • Journal: Composites Part B: Engineering
    • Year: 2019
    • DOI: 10.1016/j.compositesb.2018.10.102
  • Experimental and numerical studies of CFRP tube and steel spiral dual-confined concrete composite columns under axial impact loading
    • Authors: Liang Huang, Chang Gao, Libo Yan, Tao Yu, Bohumil Kasal
    • Journal: Composites Part B: Engineering
    • Year: 2018
    • DOI: 10.1016/j.compositesb.2018.07.008