Yunchao Cao | Engineering | Innovative Research Award

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Innovative Research Award

Yunchao Cao
Hunan University, China

Yunchao Cao
Affiliation Hunan University
Country China
Documents 1
Subject Area Engineering
Event International Forensic Scientist Awards
ORCID 0009-0003-6522-5745

Yunchao Cao is a researcher affiliated with Hunan University, China, whose reported research output addresses point cloud filtering for slope light detection and ranging (LiDAR) applications. The publication focuses on applying attention mechanisms and model scaling to PointNet++, a deep-learning architecture for processing three-dimensional point clouds. This research topic connects engineering, artificial intelligence, and geospatial data processing, with potential relevance to the analysis of complex terrain and slope environments. The recognition profile presents the available publication information without assuming unverified citation metrics or research achievements.

Abstract

Yunchao Cao’s reported research examines an attention-enhanced and scaled PointNet++ approach for filtering slope LiDAR point clouds. Point cloud filtering is an important processing stage in three-dimensional data analysis because unwanted measurements and irrelevant points can complicate the interpretation of terrain surfaces. Combining attention mechanisms with model scaling offers a methodological direction for investigating feature representation and computational performance. The associated article is listed in AI in Civil Engineering with DOI 10.1007/s43503-026-00110-z. Its publication metadata identifies a specific contribution to machine-learning-based engineering research, although detailed experimental results and independent impact indicators require verification from the full article. [1]

Keywords

Point cloud filtering; slope LiDAR; PointNet++; attention mechanism; model scaling; three-dimensional data; deep learning; civil engineering.

Introduction

LiDAR technology captures spatial information by measuring distances with laser pulses, producing point clouds that can support terrain mapping and engineering assessment. In slope-related applications, the quality of these datasets can influence subsequent modelling and interpretation. Deep-learning methods provide approaches for learning spatial features from point-based representations, while attention mechanisms can help models emphasize informative features. PointNet++ is designed to learn hierarchical representations of point clouds, making it a relevant architecture for this research direction. [2]

Research Profile

The available publication record places Cao’s documented research in engineering-oriented artificial intelligence, particularly the processing of three-dimensional spatial data. The reported study combines a point-cloud learning architecture with attention and scaling strategies. Further details concerning the researcher’s complete specialization, institutional research group, and broader project portfolio have not been independently established from the supplied information.

Research Contributions

The reported study identifies several areas of methodological interest:

  • Investigating point cloud filtering methods tailored to slope LiDAR data.
  • Incorporating an attention mechanism into a PointNet++-based processing approach.
  • Exploring model scaling as part of the architecture’s design.
  • Contributing to research at the intersection of three-dimensional data processing and civil engineering.

These points describe the study’s stated subject and approach; quantitative improvements over baseline methods should be assessed using the article’s reported experiments. [1]

Publications

One publication is provided in the supplied research record:

  1. “Point cloud filtering method for slope LiDAR based on attention mechanism and model scaling of PointNet++.” AI in Civil Engineering. Listed publication date: December 2026. [1]

As this profile is dated October 2026, the supplied December 2026 publication date is future-dated and should be checked against the publisher’s current record before final publication.

Research Impact

The documented research topic has potential relevance to terrain-data preparation, point-cloud analysis, and machine-learning applications in engineering. However, the supplied information does not establish citation counts, h-index, adoption by practitioners, or independently measured performance gains. These indicators should remain unreported until confirmed through reliable bibliographic databases or the published study. The listed document count is one, as provided for this recognition profile.

Award Suitability

The Innovative Research Award profile recognizes the methodological focus of Cao’s reported work on attention mechanisms, point-cloud processing, and model scaling. These subjects align with innovation-oriented engineering research because they investigate computational approaches to a practical data-processing problem. A complete award evaluation should additionally consider the originality of the method, experimental validation, comparison with established techniques, reproducibility, and demonstrated significance. This profile records the research area without implying an independently verified award decision or unsupported performance claims.

Conclusion

Yunchao Cao’s reported publication presents a research direction combining PointNet++, attention mechanisms, and model scaling for slope LiDAR point cloud filtering. The work connects artificial intelligence with engineering data processing and provides a defined basis for evaluating methodological innovation. Verification of publication timing, bibliographic identifiers, citation metrics, and experimental findings would strengthen the completeness and reliability of this academic recognition profile.

References

  1. Springer Nature. (2026). Point cloud filtering method for slope LiDAR based on attention mechanism and model scaling of PointNet++. AI in Civil Engineering. DOI: 10.1007/s43503-026-00110-z. Publication details and date should be confirmed against the publisher’s record.
    https://doi.org/10.1007/s43503-026-00110-z
  2. Qi, C. R., Yi, L., Su, H., & Guibas, L. J. (2017). PointNet++: Deep hierarchical feature learning on point sets in a metric space. Advances in Neural Information Processing Systems, 30.
  3. ORCID. (n.d.). Yunchao Cao: ORCID researcher identifier.
    https://orcid.org/0009-0003-6522-5745

Sarat Mohapatra | Engineering | Innovative Research Award

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Dr. Sarat Mohapatra | Engineering | Innovative Research Award

Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, University of Lisbon | Portugal

Dr. Sarat Mohapatra is an accomplished marine researcher whose work bridges theoretical modeling, computational simulation, and experimental validation in the fields of hydroelasticity, ocean hydrodynamics, offshore aquaculture systems, and floating platform dynamics. His research primarily addresses complex fluid–structure interactions and the development of hydroelastic models for flexible and porous marine structures under combined wave and current conditions. With over 70 international publications in leading journals such as Ocean Engineering, Applied Ocean Research, Journal of Fluids and Structures, Physics of Fluids, and Journal of Marine Science and Engineering, his work has received significant global recognition, reflected in an h-index of 21 and more than 1,160 citations. Dr. Sarat Mohapatra has been a key contributor to several European and Portuguese Foundation for Science and Technology (FCT)-funded projects, focusing on hydrodynamic and hydroelastic analysis of large floating structures and wave energy systems. His recent studies include the development of analytical, numerical, and CFD-based models to predict wave-current interactions and improve the design of sustainable marine systems. In addition to his strong publication record, he has served as a journal reviewer, editorial contributor, and co-supervisor for doctoral and postgraduate research, promoting innovation and collaboration within marine technology. Through his pioneering contributions, Dr. Sarat Mohapatra continues to advance the understanding of ocean engineering phenomena, supporting innovations in marine renewable energy, offshore structure design, and environmentally resilient aquaculture technologies that contribute to the sustainable utilization of ocean resources.

Profiles: Scopus | Google Scholar | ORCID | ResearchGate | Cienciavitae

Featured Publications

  • Mohapatra, S. C., Amouzadrad, P., & Guedes Soares, C. (2025). Recent developments in the nonlinear hydroelastic modeling of sea ice interaction with marine structures. Journal of Marine Science and Engineering, 13(8), Article 1410. https://doi.org/10.3390/jmse13081410

  • Mohapatra, S. C., & Guedes Soares, C. (2025). Oblique wave analysis under current conditions on a floating flexible membrane. Physics of Fluids, 37(7), Article 072101. https://doi.org/10.1063/5.0278003

  • Mohapatra, S. C., Guedes Soares, C., & Meylan, M. H. (2025). Three-dimensional and oblique wave-current interaction with a floating elastic plate based on an analytical approach. Symmetry, 17(6), Article 831. https://doi.org/10.3390/sym17060831

  • Amouzadrad, P., Mohapatra, S. C., & Guedes Soares, C. (2025). Review on sensitivity and uncertainty analysis of hydrodynamic and hydroelastic responses of floating offshore structures. Journal of Marine Science and Engineering, 13(6), Article 1015. https://doi.org/10.3390/jmse13061015

  • Mohapatra, S. C., & Guedes Soares, C. (2025). Wave–current interaction with a deformable bottom in a three-dimensional channel. Physics of Fluids, 37(5), Article 052104. https://doi.org/10.1063/5.0267255

Nadiia Kopiika | Engineering | Best Paper Award

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Dr. Nadiia Kopiika | Engineering | Best Paper Award

University College London | United Kingdom

Dr. Nadiia Kopiika is a distinguished civil and structural engineering researcher whose work unites innovation, sustainability, and resilience in the reconstruction of critical infrastructure. She is affiliated with University College London, London, United Kingdom, and serves as a BA/CARA Research Fellow at the University of Birmingham (UK) and Teaching Assistant at Lviv Polytechnic National University (Ukraine). Dr. Nadiia Kopiika has made exceptional contributions to developing advanced methodologies for damage assessment, probabilistic modelling, and structural rehabilitation of reinforced concrete structures. Her publication, “Probabilistic Assessment of RC Beams with Corroded Thermally Strengthened Reinforcement” (Structures, 2025), presents a comprehensive probabilistic framework for evaluating the reliability and residual capacity of corroded reinforcement systems, providing crucial insights for sustainable and data-driven restoration. According to Scopus, she has authored 34 indexed publications, accumulated 416 citations across 219 citing documents, and holds an h-index of 15, reflecting her growing impact in the global engineering community. Her work seamlessly combines analytical precision with practical applications in infrastructure resilience and recovery. Dr. Kopiika is also actively engaged in collaborative initiatives such as bridgeUkraine.org and MetaInfrastructure.org, advancing digital diagnostics, AI integration, and circular design for post-disaster reconstruction. Her achievements have been recognised through prestigious honours, including the Award of the Verkhovna Rada of Ukraine for Young Scientists (2024) and the BA/CARA Research Fellowship (2023–2026). Through her interdisciplinary research and commitment to sustainable engineering, Dr. Nadiia Kopiika continues to advance innovative frameworks for resilient, future-ready infrastructure systems worldwide.

Profile: Scopus | Google Scholar | ORCID | ResearchGate | LinkedIn

Featured Publications

  • Blikharskyy, Y., Kopiika, N., Khmil, R., Selejdak, J., & Blikharskyy, Z. (2022). Review of development and application of digital image correlation method for study of stress–strain state of RC structures. Applied Sciences, 12(19), 10157. [Cited by 56]
    https://doi.org/10.3390/app121910157

  • Kopiika, N., Karavias, A., Krassakis, P., Ye, Z., Ninic, J., Shakhovska, N., … (2025). Rapid post-disaster infrastructure damage characterisation using remote sensing and deep learning technologies: A tiered approach. Automation in Construction, 170, 105955. [Cited by 27]
    https://doi.org/10.1016/j.autcon.2025.105955

  • Blikharskyy, Y., Vashkevych, R., Kopiika, N., Bobalo, T., & Blikharskyy, Z. (2021). Calculation residual strength of reinforced concrete beams with damages, which occurred during loading. IOP Conference Series: Materials Science and Engineering, 1021(1), 012012. [Cited by 32]
    https://doi.org/10.1088/1757-899X/1021/1/012012

  • Blikharskyy, Y., Selejdak, J., & Kopiika, N. (2021). Corrosion fatigue damages of rebars under loading in time. Materials, 14(12), 3416. [Cited by 31]
    https://doi.org/10.3390/ma14123416

  • Blikharskyy, Y., Selejdak, J., Kopiika, N., & Vashkevych, R. (2021). Study of concrete under combined action of aggressive environment and long-term loading. Materials, 14(21), 6612. [Cited by 30]
    https://doi.org/10.3390/ma14216612

Guruswamy K. P | Engineering | Best Researcher Award

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Dr. Guruswamy K. P | Engineering | Best Researcher Award

University of Visvesvaraya College of Engineering | India

Dr. Guruswamy K. P. is an Associate Professor in the Department of Electrical Engineering at the University of Visvesvaraya College of Engineering (UVCE), Bengaluru. He is widely recognized for his expertise in power electronics, particularly in the modeling and control of advanced power converter systems. His professional journey reflects a blend of academic teaching and innovative research, enabling him to contribute to both the classroom and the wider engineering community. Through his dedicated work, he has advanced the design of compact, efficient, and reliable power converters, making a significant impact on electric vehicle charging systems, renewable energy integration, and smart power management technologies.

Professional Profile

Google Scholar

Education

Dr. Guruswamy K. P began his academic journey at the University of Visvesvaraya College of Engineering, where he earned both his Bachelor’s and Master’s degrees in Electrical Engineering. His early academic training laid a strong foundation in fundamental engineering principles while also sparking his interest in power conversion systems. He further strengthened his expertise by pursuing doctoral research at the Indian Institute of Technology Roorkee, where he specialized in advanced control and modeling of DC–DC converters and resonant converters. This educational progression provided him with a comprehensive balance of theory, practical knowledge, and research skills that continue to influence his work today.

Experience

Over the course of his professional career, Dr. Guruswamy K. P has accumulated extensive teaching and research experience. He began with faculty positions in engineering institutions before advancing to his current role as Associate Professor at UVCE. In this position, he has not only taught core electrical engineering courses but has also supervised research projects and guided students in innovative converter design. He has contributed to the development of laboratory infrastructure, collaborative research initiatives, and academic curricula that integrate emerging topics such as digital control, interleaved converter systems, and sustainable energy applications. His leadership extends beyond teaching, as he regularly collaborates with researchers from leading institutions on interdisciplinary projects.

Research Interest

Dr. Guruswamy K. P research interests lie in the broad area of power electronics, with a specific focus on resonant converters, interleaved DC–DC converters, bidirectional converters, PWM rectifiers, and digital control strategies. He is particularly interested in applying analytical methods and computational modeling to improve the efficiency, reliability, and adaptability of converter technologies. His research often bridges theoretical modeling with practical implementation, which is especially evident in applications such as electric vehicle charging systems, auxiliary power units, and renewable energy integration. By combining modern control approaches with traditional converter design, he continues to drive advancements in sustainable energy systems and high-performance power management solutions.

Awards

Dr. Guruswamy K. P has been consistently recognized for his academic excellence, research contributions, and professional commitment. His innovative work in the field of power converters has earned him appreciation within the engineering community, and his nomination for the Best Researcher Award reflects his sustained achievements in both research and teaching. His professional memberships with ISTE and IEEE further highlight his active involvement in knowledge dissemination and collaboration, underscoring his contributions to advancing power electronics at both national and international levels.

Publications

Dr. Guruswamy K. P has authored and co-authored multiple publications in reputed international journals and conferences. His research spans topics such as digital control methods, resonant LLC converters, bidirectional DC–DC converters, and PWM rectifier applications. Selected works include:

1. Title: Modelling of flyback converter using state space averaging technique
Journal: 2015 IEEE International Conference on Electronics, Computing and Communication Technologies (ICECCT)
Published on: 2015
Citation: 34

2. Title: Design, modeling and analysis of two level interleaved boost converter
Journal: 2013 International Conference on Machine Intelligence and Research Advancement (ICMIRA)
Published on: 2013
Citation: 31

3. Title: Design, Modelling, Analysis and Implementation of Two Phase Interleaved Buck DC-DC Converter
Journal: International Journal of Innovative Science and Research Technology
Published on: 2018
Citation: 8

4. Title: FPGA based 2-stage power conditioning system for PV power generation
Journal: 2013 International Conference on Power, Energy and Control (ICPEC)
Published on: 2013
Citation: 8

5. Title: Design and implementation of two phase interleaved DC-DC boost converter with digital PID controller
Journal: International Journal of Electrical and Electronics Engineering (IJEEE)
Published on: 2013
Citation: 8

6. Title: Performance Analysis for LLC Resonant Converter in Electric Vehicle Applications
Journal: 2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)
Published on: 2023
Citation: 4

7. Title: Performance Analysis of Half-Bridge LC Resonant Converter for UPS Battery Charging Application
Journal: 2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)
Published on: 2023
Citation: 3

Conclusion

Dr. Guruswamy K. P. stands out as a dedicated academic and researcher in the field of power electronics. His educational background, teaching experience, and innovative research collectively illustrate his strong commitment to advancing the field of converter technology. Through his publications, collaborations, and professional memberships, he has consistently contributed to both theoretical and applied aspects of electrical engineering. His nomination for the Best Researcher Award acknowledges not only his scholarly achievements but also his role in shaping the next generation of engineers and promoting sustainable energy solutions through advanced power electronics.