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

Yafei Chen | Engineering | Innovative Research Award

Published on by Academic Excellence

Innovative Research Award

Yafei Chen
Zhengzhou University of Light Industry,China

Yafei Chen, Zhengzhou University of Light Industry, China, is a researcher in the field of Engineering whose scholarly profile is represented through indexed research records and persistent researcher identifiers. The recognition associated with the Innovative Research Award considers the documented research profile and academic contribution of the nominee within an international academic recognition framework.

Yafei Chen
Affiliation Zhengzhou University of Light Industry
Country China
Scopus ID 57208723653
Documents 35
Citations 929
h-index 16
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0001-8760-4277

The bibliographic indicators presented in this article are based on the supplied researcher profile information and should be interpreted as profile-level indicators rather than as independent measures of research quality. Citation counts and h-index values can change as databases are updated and additional publications are indexed. [1]

Abstract

Yafei Chen is affiliated with Zhengzhou University of Light Industry and is associated with the Engineering subject area. The supplied bibliometric profile records 35 documents, 929 citations, and an h-index of 16. These indicators provide a quantitative description of the indexed research record and form part of the evidence considered in documenting the researcher’s academic profile. [1]

Keywords

  • Yafei Chen
  • Engineering
  • Research Innovation
  • Bibliometrics
  • Academic Research

Introduction

Engineering research encompasses the development, analysis, and application of scientific and technological knowledge to practical and theoretical problems. Within this broad domain, research impact may be documented through scholarly publications, citations, collaboration, and the continuing visibility of research outputs in recognized bibliographic systems. Persistent identifiers such as ORCID also support accurate attribution of scholarly work across research systems. [2]

Research Profile

The supplied profile identifies Yafei Chen with Zhengzhou University of Light Industry in China and assigns the researcher to Engineering. The Scopus author identifier is 57208723653. The reported 35 documents and 929 citations provide an indexed overview of scholarly output and citation activity, while the h-index of 16 represents a further bibliometric indicator of publication and citation distribution. [1]

Research Contributions

The available profile information supports a description of Chen’s contribution at the level of documented scholarly productivity and research visibility. A complete assessment of individual technical contributions would require examination of the underlying publications, methodologies, datasets, patents, collaborations, and application outcomes. Accordingly, the award profile does not infer specific technical findings beyond the information supplied. [3]

Publications

The researcher profile is associated with 35 indexed documents. Individual publication titles, journal information, and DOI records should be verified against the corresponding bibliographic databases before being attributed to the researcher. DOI identifiers provide persistent links to scholarly publications and are commonly used for reliable article-level referencing. [4]

Research Impact

The supplied figures of 929 citations and an h-index of 16 indicate measurable citation activity within the indexed profile. Bibliometric indicators are descriptive rather than comprehensive measures of research quality, because citation practices vary among disciplines, publication types, research communities, and time periods. [5]

Award Suitability

For the International Academic Excellence Awards, the documented Engineering affiliation, indexed research record, publication count, citation count, and h-index constitute profile information relevant to an academic recognition page. The Innovative Research Award can therefore be presented in connection with the supplied scholarly record, while detailed evaluation of innovation should remain grounded in verified research outputs and supporting evidence. [6]

Conclusion

Yafei Chen’s supplied academic profile documents an Engineering research record affiliated with Zhengzhou University of Light Industry, with 35 documents, 929 citations, and an h-index of 16. These indicators provide a concise bibliometric context for the Innovative Research Award profile and can be supplemented by verified publication, DOI, and researcher-identifier records.

References

  1. Elsevier. (n.d.). Scopus author details: Yafei Chen, Author ID 57208723653. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57208723653
  2. ORCID. (n.d.). ORCID record for Yafei Chen. ORCID.
    https://orcid.org/0000-0001-8760-4277
  3. National Academies of Sciences, Engineering, and Medicine. (2018). Open Science by Design: Realizing a Vision for 21st Century Research. National Academies Press.
    https://doi.org/10.17226/25116
  4. International DOI Foundation. (n.d.). DOI Handbook. DOI Foundation.
    https://doi.org/10.1000/182
  5. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572.
    https://doi.org/10.1073/pnas.0507655102
  6. International Academic Excellence Awards. (n.d.). Academic Excellence Awards.
    https://academicexcellenceawards.com/

Vidya Nandikolla | Engineering | Best Researcher Award

Published on by Academic Excellence

Best Researcher Award

Dr Vidya Nandikolla
Affiliation California State University Northridge
Country United States
Scopus ID 8339231200
Documents 25
Citations 136
h-index 5
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0002-4151-4783

Dr Vidya Nandikolla
California State University Northridge,United States

Dr Vidya Nandikolla is an engineering researcher affiliated with California State University Northridge in the United States. Her documented research output includes work in autonomous vehicles, robotics, brain-computer interfaces, and simultaneous localization and mapping (SLAM), reflecting an interdisciplinary interest in intelligent robotic and autonomous systems. Available bibliographic indicators record 25 documents, 136 citations, and an h-index of 5.

Abstract

Dr Vidya Nandikolla’s research profile is situated within engineering applications involving robotics, autonomous systems, human-machine interaction, and computational sensing. Her publication record includes research on a hybrid EEG-based brain-computer interface (BCI) arm manipulator controlled through ROS and work concerning autonomous vehicles and LiDAR-based localization. These topics connect sensing, control, perception, and intelligent automation, all of which are central areas of contemporary engineering research.

Keywords

Robotics; autonomous vehicles; LiDAR; SLAM; brain-computer interface; ROS; robotic control; engineering; localization; intelligent systems.

Introduction

Modern autonomous and robotic platforms depend on reliable perception, localization, control, and human-machine communication. SLAM methods allow robotic systems to estimate their position while constructing representations of an environment, while BCI technologies investigate alternative mechanisms for controlling assistive robotic devices. Nandikolla’s documented work intersects these engineering challenges, providing a research profile that combines robotics with emerging sensing and control technologies. [2]

Research Profile

The available record identifies Engineering as the principal subject area. Her research themes include ROS-enabled robotic control, EEG-based BCI systems, autonomous vehicle technologies, and LiDAR SLAM. ROS is widely used as a framework for developing modular robotic applications, making its use relevant to experimental robotics and autonomous-system research. [3]

Research Contributions

  • Research involving a hybrid EEG-based BCI arm manipulator and ROS-based robotic control.
  • Investigation of autonomous vehicle technologies, including custom battery-pack design using solar energy.
  • Evaluation of Extended Kalman Filter odometry for improving the performance of 2D LiDAR SLAM algorithms. [1]

Publications

Evaluating the Impact of Extended Kalman Filter Odometry on the Performance of 2D LiDAR SLAM Algorithms is listed as a working paper and carries. Another documented publication is Teleoperation Robot Control of a Hybrid EEG-Based BCI Arm Manipulator Using ROS, published in the Journal of Robotics in 2022 and reported with five citations in the supplied record. A conference paper, Design and Analysis of an Custom Battery Pack Using Solar Energy for an Autonomous Vehicle, further demonstrates an application-oriented engineering focus.

Research Impact

The reported bibliometric record of 136 citations across 25 documents indicates measurable scholarly visibility. An h-index of 5 provides an additional bibliometric indicator of citation distribution. These metrics should be interpreted alongside publication quality, research relevance, technical contribution, and broader application potential rather than as standalone measures of research excellence. [4]

Award Suitability

Dr Vidya Nandikolla demonstrates characteristics relevant to consideration for a Best Researcher Award in Engineering, particularly through a research portfolio connecting robotics, autonomous mobility, BCI systems, and localization. The combination of published research, interdisciplinary engineering applications, and documented citation activity provides a reasonable academic basis for recognition. Final award assessment should consider the complete submitted evidence and the evaluation criteria established by the International Academic Excellence Awards.

Conclusion

Dr Vidya Nandikolla’s documented research reflects an engineering-oriented approach to robotics, autonomous systems, human-machine interfaces, and intelligent localization. Her publication activity and bibliometric indicators support recognition of sustained research engagement, while her work addresses practical challenges in emerging robotic technologies.

References

  1. Nandikolla, Vidya K. et al. (2026). Evaluating the Impact of Extended Kalman Filter Odometry on the Performance of 2D LiDAR SLAM Algorithms. Preprints.
    https://doi.org/10.20944/preprints202607.1435.v1
  2. Cadena, C. et al. (2016). Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age. IEEE Transactions on Robotics, 32(6), 1309–1332.
    https://doi.org/10.1109/TRO.2016.2624754
  3. Quigley, M. et al. (2009). ROS: an open-source Robot Operating System. ICRA Workshop on Open Source Software.
  4. Elsevier. (n.d.). Scopus author details: Vidya Nandikolla, Author ID 8339231200. Scopus.
    https://www.scopus.com/pages/authors/8339231200
  5. Nandikolla, Vidya K., and Medina Portilla, Daniel A. (2022). Teleoperation Robot Control of a Hybrid EEG-Based BCI Arm Manipulator Using ROS. Journal of Robotics.
  6. Nandikolla, Vidya K. et al. Design and Analysis of an Custom Battery Pack Using Solar Energy for an Autonomous Vehicle. Conference paper.

Rahul Diwate | Engineering | Best Researcher Award

Published on by Academic Excellence

Best Researcher Award

Rahul Diwate
Vishwakarma Institute of Technology, India

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

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

Abstract

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

Keywords

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

Introduction

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

Research Profile

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

Research Contributions

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

Publications

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

Research Impact

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

Award Suitability

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

Conclusion

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

References

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

KARTHIK M | Engineering | Research Excellence Award

Published on by Academic Excellence

Dr. KARTHIK M | Engineering | Research Excellence Award

SRM Madurai College for Engineering and Tchnology | India

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

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An efficient waste management technique with IoT based smart garbage system
– Materials Today: Proceedings, 2023
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– 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.

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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
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– 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.

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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.

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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.

Farzin Naghibalsadati | Engineering | Best Researcher Award

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Mr. Farzin Naghibalsadati | Engineering | Best Researcher Award

Mr. Farzin Naghibalsadati, University of Regina, Canada

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

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Suitability Summary for Research for Best Researcher Award

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

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

Education 🎓 

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

Professional Experience 💼

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

Awards and Recognition 🏅

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

Research Skills On Engineering 🌍 

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

📖  Publication Top Notes

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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