Michael Todinov | Engineering | Innovative Research Award

Published on by Academic Excellence

Innovative Research Award

Michael Todinov
Oxford Brookes University,United Kingdom

Michael Todinov
Affiliation Oxford Brookes University
Country United Kingdom
Scopus ID 7004595988
Documents 111
Citations 1,122
h-index 18
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0002-3957-7961

Michael Todinov is an engineering researcher associated with Oxford Brookes University whose scholarly work focuses on reliability, risk, engineering design, probabilistic methods, and structural efficiency. His recent publications address domain-independent reliability improvement, lightweight structures, algebraic approaches to reliability prediction, and probabilistic interpretations of engineering inequalities.[1][2]

Abstract

Michael Todinov’s research profile centers on engineering reliability, risk reduction, probabilistic analysis, and structural design. His recent work proposes methods for improving reliability by exploiting asymmetry, balancing system components, and interpreting algebraic relationships probabilistically. Other studies investigate lightweight structures subjected to bending and the use of reverse engineering of algebraic inequalities for reliability prediction and engineering-process improvement.[1][3]

Keywords

Engineering; Reliability Engineering; Risk Analysis; Probabilistic Methods; Structural Design; Lightweight Structures; Reliability Prediction; Engineering Optimization; Algebraic Inequalities; System Reliability.

Introduction

Reliability and risk are central concerns in engineering systems because failures can affect safety, performance, cost, and service continuity. Todinov’s research addresses these concerns through analytical approaches that seek to identify relationships between system configuration, reliability, and risk. His publications span reliability theory and engineering design, providing a connection between mathematical analysis and practical engineering problems.[3][4]

Research Profile

The supplied bibliometric profile records 111 documents, 1,122 citations, and an h-index of 18. These indicators describe a substantial body of indexed scholarly output. His publication portfolio demonstrates continuity in reliability and risk research while also extending into mechanical and structural engineering applications.[1][2]

Research Contributions

  • Development of a domain-independent approach to reliability improvement and risk reduction through exploitation of asymmetry.[1]
  • Investigation of lightweight multi-element structures subjected to bending loads, with emphasis on structural configuration and efficiency.[2]
  • Application of reverse engineering of algebraic inequalities to system reliability prediction and engineering-process enhancement.[3]
  • Probabilistic interpretation of algebraic inequalities associated with reliability and risk analysis.[4]

Publications

Among the recent publications is A new domain-independent method for improving reliability and reducing risk based on exploiting asymmetry, published in Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability in December 2025.[1] A related 2025 contribution examines lightweight structures composed of multiple elements loaded in bending.[2] Earlier work in IEEE Transactions on Reliability considers algebraic inequalities for system reliability prediction, while a 2023 study develops their probabilistic interpretation.[3][4]

Research Impact

The reported citation count and h-index indicate sustained scholarly visibility. The research is also notable for connecting reliability theory with engineering design problems, including structural loading and system configuration. The domain-independent orientation of recent reliability research may support application across different engineering contexts where risk and failure probabilities must be assessed systematically.[1][4]

Award Suitability

The documented publication record, citation indicators, and sustained focus on reliability and risk provide a substantive basis for consideration for an Innovative Research Award. His work combines analytical methods with engineering applications and addresses questions concerning system performance, structural efficiency, reliability prediction, and risk reduction. These characteristics align with recognition criteria emphasizing methodological innovation and meaningful engineering research contributions.

Conclusion

Michael Todinov’s research profile reflects sustained contributions to engineering reliability, risk analysis, probabilistic methods, and structural design. His recent publications demonstrate continued development of analytical approaches to reliability improvement alongside applications in mechanical engineering. The available bibliometric and publication information supports his consideration within an academic recognition framework focused on innovative engineering research.

References

  1. Todinov, M. (2025). A new domain-independent method for improving reliability and reducing risk based on exploiting asymmetry. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability.
    https://doi.org/10.1177/1748006X251324081
  2. Todinov, M. (2025). Designing light-weight structures consisting of multiple elements loaded in bending. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.
    https://doi.org/10.1177/09544062251365722
  3. Todinov, M. (2024). Reverse Engineering of Algebraic Inequalities for System Reliability Predictions and Enhancing Processes in Engineering. IEEE Transactions on Reliability.
    https://doi.org/10.1109/TR.2023.3315662
  4. Todinov, M. (2023). Probabilistic interpretation of algebraic inequalities related to reliability and risk. Quality and Reliability Engineering International.
    https://doi.org/10.1002/qre.3345
  5. Todinov, M. (2023). Improving reliability by increasing the level of balancing and by substitution. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.
    https://doi.org/10.1177/09544062221132419
  6. Elsevier. (n.d.). Scopus author details: Michael Todinov, Author ID 7004595988. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7004595988

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/

Sherief Hashima | Engineering | Innovative Research Award

Published on by Academic Excellence

Innovative Research Award

Sherief Hashima
RIKEN Center for Advanced Intelligence Project,Japan

Sherief Hashima, RIKEN-AIP, Japan, is recognized in the context of the International Academic Excellence Awards for research activity spanning engineering, wireless communications, intelligent networks, signal processing, and emerging communication technologies.

Sherief Hashima
Affiliation RIKEN Center for Advanced Intelligence Project
Country Japan
Scopus ID 55849342400
Documents 88
Citations 1,113
h-index 19
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0002-4443-7066

Abstract

Sherief Hashima’s documented publication record covers contemporary engineering problems involving wireless networks, intelligent communication systems, signal analysis, Internet of Things technologies, and next-generation mobile communications. Recent publications address neutron/gamma pulse-shape discrimination using scalogram imaging and pretrained convolutional neural networks, mobility management for unified 6G networks, integrated sensing and communications, reconfigurable intelligent surface-assisted wireless information and power transfer, and UAV-assisted vehicular communications. [1][2]

Keywords

Engineering; wireless communications; 6G; signal processing; artificial intelligence; Internet of Things; ISAC; RIS; UAV communications; beamforming; mobility management.

Introduction

Research in advanced communication engineering increasingly combines signal processing, machine learning, network optimization, and heterogeneous wireless infrastructure. The supplied publication record places Hashima’s recent work within this multidisciplinary engineering environment, with studies addressing both methodological developments and surveys of emerging communication architectures. [3]

Research Profile

The supplied profile records 88 documents, 1,113 citations, and an h-index of 19, associated with Scopus author ID 55849342400. These figures are bibliometric indicators and can change as databases update their indexing and citation records.

Research Contributions

  • Applied scalogram imaging and pretrained CNN methods to neutron/gamma pulse-shape discrimination. [1]
  • Examined mobility management challenges and future directions in three-dimensional unified 6G networks. [2]
  • Surveyed ISAC integration with emerging wireless network technologies and RIS-assisted SWIPT architectures. [3][4]

Publications

  • Neutron/Gamma Pulse Shape Discrimination via Scalogram Imaging and Pretrained CNN, Signals, 2026. DOI. [1]
  • Mobility management in 3D unified 6G networks: Challenges, opportunities and future directions, ICT Express, 2026. DOI. [2]
  • ISAC Integration With Emerging Wireless Network Technologies: A Comprehensive Survey, IEEE Open Journal of the Communications Society, 2026. DOI. [3]
  • RIS-Assisted SWIPT for IoT Networks: A Survey of Architectures, Optimization, and Future Directions, 2026. DOI. [4]
  • Delay-Doppler-Based Joint mmWave Beamforming and UAV Selection in Multi-UAV-Assisted Vehicular Communications, Aerospace, 2025. DOI. [5]

Research Impact

The reported citation count and h-index provide quantitative indicators of scholarly visibility in the supplied Scopus profile. The publication set also demonstrates engagement with several active engineering themes, including 6G networks, ISAC, RIS-enabled IoT systems, machine-learning-based signal analysis, and UAV communications.

Award Suitability

The documented research themes correspond to the engineering scope of the Innovative Research Award. In particular, the combination of signal-processing methods, intelligent communication technologies, network architectures, and emerging wireless systems provides a substantive basis for consideration within an academic recognition program. This description concerns alignment between the supplied research record and the stated award category.

Conclusion

Sherief Hashima’s supplied academic profile reflects research activity across multiple areas of contemporary engineering and wireless communication. The listed publications demonstrate work on both applied signal analysis and emerging network technologies, while the reported bibliometric indicators provide additional context for the research profile.

References

  1. MDPI. (2026). Neutron/Gamma Pulse Shape Discrimination via Scalogram Imaging and Pretrained CNN. Signals.
    https://doi.org/10.3390/signals7050091
  2. Elsevier. (2026). Mobility management in 3D unified 6G networks: Challenges, opportunities and future directions. ICT Express.
    https://doi.org/10.1016/j.icte.2025.11.011
  3. IEEE. (2026). ISAC Integration With Emerging Wireless Network Technologies: A Comprehensive Survey. IEEE Open Journal of the Communications Society.
    https://doi.org/10.1109/OJCOMS.2026.3690251
  4. IEEE. (2026). RIS-Assisted SWIPT for IoT Networks: A Survey of Architectures, Optimization, and Future Directions. IEEE Open Journal of the Communications Society.
    https://doi.org/10.1109/OJCOMS.2026.3724584
  5. MDPI. (2025). Delay-Doppler-Based Joint mmWave Beamforming and UAV Selection in Multi-UAV-Assisted Vehicular Communications. Aerospace.
    https://doi.org/10.3390/aerospace12090757
  6. Elsevier. (n.d.). Scopus author details: Sherief Hashima, Author ID 55849342400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55849342400

Sumaraj S | Engineering | Academic Excellence Award

Published on by Academic Excellence

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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Documents
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h-index
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Featured Publications

Srikanth Nandoori | Engineering | Best Researcher Award

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Dr. Srikanth Nandoori | Engineering | Best Researcher Award

Anurag University | India

Dr. Nandoori Srikanth is an accomplished academician and training strategist with over eleven years of combined experience in teaching, training, placements, and industry engagement. He holds a Ph.D. in Wireless Communications from KL University, where his research focused on developing energy-efficient cluster-based routing protocols to enhance the lifetime and performance of Wireless Sensor Networks. His academic background spans VLSI System Design at the postgraduate level and Electronics & Communication Engineering at both graduation and diploma levels, forming a strong foundation for his technical expertise. Throughout his career, Dr. Srikanth has contributed significantly to engineering education through his roles as Associate Professor, Assistant Professor, Placement Coordinator, Training & Placement Officer, and currently as Dean of Placements at St. Peter’s Engineering College. His leadership has strengthened institutional-industry collaboration, resulting in the establishment of multiple Centers of Excellence with global organizations such as Microsoft, IDS Blockchain, Movate, and Juniper Networks. He has also led the signing of key MoUs with Google Cloud, Infosys Springboard, Eduskills, Internshala, and several emerging technology firms, enabling students to access high-value skilling, internship, and hiring opportunities. Dr. Srikanth’s efforts in fostering employability have earned him prestigious recognitions, including the All-India 4th Rank and State 2nd Rank in Internshala Rankings, the Best SPOC Award from Eduskills (received three times), and commendations for promoting Google Cloud certifications. Additionally, he holds professional certifications in Google Cloud Associate, ServiceNow, and Microsoft Azure Fundamentals. His work reflects a deep commitment to academic excellence, student development, and innovation-driven education.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Srikanth, N., & Prasad, M. S. G. (2018). Efficient clustering protocol using fuzzy K-means and midpoint algorithm for lifetime improvement in WSNs. International Journal of Intelligent Engineering and Systems, 11(4), 61–71.

Srikanth, N., & Prasad, M. S. (2019). Energy efficient trust node based routing protocol (EETRP) to maximize the lifetime of wireless sensor networks in plateaus. International Journal of Online & Biomedical Engineering, 15(6).

Srikanth, N., & Prasad, M. S. G. (2019). A compressive family based efficient trust routing protocol (C-FETRP) for maximizing the lifetime of WSN. In Data Communication and Networks: Proceedings of GUCON 2019 (pp. 69–80).

Srikanth, N., & Prasad, M. S. G. (2019). Family based efficient routing protocol (FERP) for lifetime improvement in heterogeneous wireless sensor networks. Journal of Advanced Research in Dynamical and Control Systems, 11(6), 131–140.

Sangari, M. S., Thangaraj, K., Vanitha, U., Srikanth, N., Sathyamoorthy, J., … (2023). Deep learning-based object detection in underwater communications system. In 2023 Second International Conference on Electrical, Electronics, Information and Communication Technology.