Ronald Garcés | Electrical and Electronics Engineering | Research Excellence Award

Research Excellence Award

Ronald Garcés

Ronald Garcés
Affiliation Corporación WOLF S.A
Country Ecuador
Scopus ID 58072300700
Documents 1
Citations 2
h-index 1
Subject Area Electrical and Electronics Engineering
Event Scientific World Research Awards

Ronald Garcés is associated with engineering and technological research activities related to automation systems, artificial vision, and Internet of Things (IoT)-based monitoring applications. His scholarly contributions reflect emerging developments in electrical and electronics engineering, particularly in hydraulic infrastructure automation and remote measurement technologies.[1] His academic profile demonstrates participation in applied engineering research intended to improve operational efficiency and technological reliability in environmental and industrial systems.

Abstract

Ronald Garcés has contributed to the advancement of engineering applications involving artificial vision, automation, and IoT-enabled monitoring systems. His published research demonstrates interest in remote data acquisition methods for hydraulic infrastructures and automated environmental observation technologies.[2] Through collaborative engineering approaches, his work supports the modernization of remote measurement systems and contributes to practical developments within electrical and electronics engineering. The integration of intelligent monitoring solutions in hydraulic systems represents a relevant contribution to infrastructure management, operational precision, and technological sustainability within applied engineering environments.

Keywords

Artificial Vision, Internet of Things, Automation Engineering, Hydraulic Monitoring, Remote Reading Systems, Electrical Engineering

Introduction

The growing integration of intelligent automation technologies has transformed engineering practices across environmental and industrial sectors. Research involving remote sensing and IoT-based monitoring systems has become increasingly significant for operational efficiency and infrastructure analysis.[3] Ronald Garcés has participated in this evolving area through contributions connected to automated hydraulic measurement technologies and artificial vision applications.

Research Profile

The researcher’s Scopus profile identifies scholarly activity within electrical and electronics engineering. His profile includes conference-based engineering publications focused on intelligent automation and remote observation systems.[1] These contributions reflect interdisciplinary technical engagement involving automation technologies and infrastructure management systems.

Research Contributions

Ronald Garcés contributed to research concerning artificial vision and IoT solutions for automated remote reading in hydraulic weirs and limnimeter systems.[2] The study explored methods for improving monitoring precision and enabling more efficient infrastructure observation processes through integrated digital technologies.

Publications

  • “Artificial Vision and IoT for Automation of Remote Reading for Limnimeters in Hydraulic Weirs.”[2]
  • Engineering conference contributions related to intelligent monitoring and automation technologies.

Research Impact

The application of automated monitoring technologies in hydraulic systems contributes to improved data reliability and operational responsiveness. Research involving artificial vision and IoT integration has relevance for water resource management, infrastructure maintenance, and digital engineering innovation.

Award Suitability

Ronald Garcés demonstrates suitability for recognition through his involvement in applied engineering research focused on intelligent automation and infrastructure technologies. His scholarly participation within emerging engineering applications aligns with the objectives of research excellence and innovation-oriented academic awards.

Conclusion

The academic contributions of Ronald Garcés highlight ongoing engagement with technological research areas involving automation, IoT systems, and artificial vision applications. His engineering-related studies contribute to contemporary discussions surrounding intelligent monitoring systems and digital infrastructure development within applied engineering disciplines.[4]

References

  1. Elsevier. (n.d.). Scopus author details: Ronald Garcés, Author ID 58072300700. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58072300700
  2. Garcés-Llerena, R. et al. (2022). Artificial Vision and IoT for Automation of Remote Reading for Limnimeters in Hydraulic Weirs.
    DOI:https://doi.org/10.1007/978-3-031-21438-7_34
  3. Scopus Preview. (2026). Conference publication records for Ronald Garcés-Llerena.
    https://www.scopus.com/
  4. Scientific World Research Awards. (2026). Research recognition and engineering innovation awards.

    Scientific World Research Awards


Yao GE | Electrical and Electronics Engineering | Young Scientist Award

Dr. Yao GE | Electrical and Electronics Engineering | Young Scientist Award

Research Fellow | Nanyang Technological University | Singapore

Dr. Yao Ge, a leading researcher at Nanyang Technological University, Singapore, has made significant contributions to advanced wireless communication systems, with research interests spanning secure precoding for ISAC systems, XL-RIS-aided near-field MIMO, OTFS-RSMA, and affine frequency division multiplexing in high-mobility and doubly-dispersive channels. His research skills include multiuser interference management, next-generation multiplexing techniques, and performance optimization of wireless networks. Dr. Ge’s work has earned him 743 citations across 57 documents, with an h-index of 14, highlighting his impactful contributions to the field. He has also been recognized for his innovative approaches in wireless communications through various awards and honors. Overall, his research advances both theoretical understanding and practical applications in secure, high-capacity, and efficient communication systems.

 

Citation Metrics (Scopus)

743
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Citations

743

Documents

57

h-index

14

Citations

Documents

h-index

View Scopus Profile View Google Scholar Profile View ResearchGate Profile

Featured Publications


Receiver design for OTFS with a fractionally spaced sampling approach


– IEEE Transactions on Wireless Communications, 2021 (Citations: 129)


OTFS signaling for uplink NOMA of heterogeneous mobility users


– IEEE Transactions on Communications, 2021 (Citations: 93)


STAR-RIS aided integrated sensing and communication over high mobility scenarios


– IEEE Transactions on Communications, 2024 (Citations: 52)

 

sainand jadhav | Mechanical Engineering | Emerging Researcher Award

Dr. Sainand Jadhav | Mechanical Engineering | Emerging Researcher Award

Assistant Professor | Kennesaw State University | United States

Dr. Sainand M. Jadhav is an accomplished emerging researcher in the field of Mechanical Engineering, specializing in additive manufacturing, advanced materials, and welding technologies. He earned his Ph.D. in Mechanical Engineering from Tennessee Technological University, USA, in 2024, after completing his Master’s and Bachelor’s degrees in Mechanical Engineering in India. His doctoral research primarily focused on wire arc additive manufacturing (WAAM) of refractory alloys and the development of bimetallic structures with tailored properties for industrial applications. With over thirteen years of academic involvement and three and a half years of concentrated research, he has gained significant international experience through collaborations with Oak Ridge National Laboratory, USA, and leading research institutes in South Korea. Professionally, Dr. Jadhav has served as a faculty member and mentor, imparting knowledge in mechanical design, manufacturing, and materials engineering while actively guiding student research projects. His research interests include metal additive manufacturing, WAAM of refractory and high-temperature alloys, bimetallic structures, materials characterization, and the development of sustainable and advanced manufacturing processes. He possesses strong research skills in process optimization, alloy design, computational modeling, and advanced characterization techniques, complemented by hands-on expertise in welding, fabrication, and mechanical testing. Dr. Jadhav has authored impactful publications in globally recognized journals such as Additive Manufacturing, International Journal of Refractory Metals and Hard Materials, Virtual and Physical Prototyping, and IEEE conferences, reflecting both the quality and relevance of his work. His growing reputation has also been supported by invitations to participate in collaborative projects, workshops, and academic exchanges. He has been recognized with prestigious honors, including research fellowships, scholarships, and awards that highlight his contributions to the advancement of metal additive manufacturing. As an educator and mentor, he continues to inspire young engineers and researchers to explore sustainable manufacturing and innovative material solutions. Looking ahead, Dr. Jadhav aims to expand his international collaborations, publish in high-impact Q1 journals, and participate in global conferences as a keynote speaker, thereby contributing further to the field of additive manufacturing and materials science. His career trajectory demonstrates a blend of academic dedication, technical expertise, and research innovation that positions him as a future leader in advanced manufacturing. According to Scopus, his research output includes 15 documents with 105 citations by 83 documents and an h-index of 6, reflecting the growing influence and recognition of his scholarly work.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

  1. Karim, D. M. A., Jadhav, S., Kannan, R., Pierce, D., & Yousub, … (2024). Investigating stainless steel/aluminum bimetallic structures fabricated by cold metal transfer (CMT)-based wire-arc directed energy deposition. Additive Manufacturing, 81, 104015. Citations: 37

  2. Shin, S.-J., Lee, J.-H., & Jadhav, S. (2023). Material-adaptive anomaly detection using property-concatenated transfer learning in wire arc additive manufacturing. International Journal of Precision Engineering and Manufacturing. Citations: 26

  3. Shin, S.-J., Hong, S.-H., & Jadhav, S. (2023). Detecting balling defects using multisource transfer learning in wire arc additive manufacturing. Journal of Computational Design and Engineering, 10(4), 1423–1442. Citations: 19

  4. Mohite, D. D., & Jadhav, S. (2016). An investigation of effect of dressing parameters for minimum surface roughness using CNC cylindrical grinding machine. Euro Asia Research and Development Association, 6(6). Citations: 18

  5. Swami, S. A., Jadhav, S., & Deshpande, A. (2016). Influence of MIG welding process parameters on tensile properties of mild steel. European Journal of Engineering and Technology Research, 1(2), 1–5. Citations: 16