Dr. Nikolaos Tsoulias | Precision Agriculture | Best Researcher Award

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Dr. Nikolaos Tsoulias | Precision Agriculture | Best Researcher Award

Dr. Nikolaos Tsoulias, Hochschule Geisenheim University, Germany

Nikos Tsoulias is a Senior Researcher and Lecturer at Hochschule Geisenheim University in Germany, specializing in agricultural engineering with a focus on precision horticulture and the integration of advanced AI and machine learning techniques in agriculture. He holds a Ph.D. in Precision Horticulture from the Agricultural University of Athens and multiple master’s degrees in Precision Farming and Agricultural Engineering. Nikos has extensive research experience in real-time sensor communication, machine vision systems, and data acquisition software development for agricultural applications, particularly in vineyards and perennial crops. His work includes leading projects on ISO-compliant machinery integration, LiDAR and thermal imaging data fusion, and the development of predictive models for crop management. He has contributed to numerous international research collaborations and published widely in journals on smart agricultural technologies. With expertise in programming languages such as Python, MATLAB, and C++, Nikos combines cutting-edge technology with practical agricultural solutions to advance sustainability and productivity in modern farming.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

Summary of Suitability – Nikos Tsoulias for Best Researcher Award

Nikos Tsoulias is an accomplished researcher and academic in the field of precision horticulture and agricultural engineering, with a robust blend of expertise in advanced sensing technologies, machine learning, and real-time agricultural applications. His work focuses on developing innovative solutions that integrate optical sensors, machine vision, and data acquisition systems to enhance sustainable agricultural practices.

🎓 Education

  • Ph.D. in Precision Horticulture
    Agricultural University of Athens, Greece | 2018 – 2021

  • MSc in Precision Farming
    Harper Adams University, UK | 2014 – 2015

  • MSc in Agricultural Engineering
    Agricultural University of Athens, Greece | 2012 – 2014

  • BSc in Agriculture
    Agricultural University of Athens, Greece | 2009 – 2012

💼 Work Experience

  • Senior Researcher (Agricultural Engineering)
    Hochschule Geisenheim University, Germany | Jan 2023 – Present

  • Postdoctoral Researcher (Precision Horticulture)
    Leibniz Institute for Agricultural Engineering and Bioeconomy, Germany | Nov 2021 – Present

  • Doctoral Researcher (Precision Horticulture)
    Leibniz Institute for Agricultural Engineering and Bioeconomy, Germany | Jun 2018 – Nov 2021

  • Research Associate (Precision Horticulture)
    Leibniz Institute for Agricultural Engineering and Bioeconomy, Germany | Jan 2017 – Jun 2017

  • Research Associate (Precision Farming)
    Harper Adams University, UK | Jan 2015 – Aug 2015

🏆 Achievements & Awards

  • Lead author of impactful journal articles on real-time applications in perennial trees and vegetables, ISO11783-compliant variable rate spraying, and UAV-based fruit detection and yield estimation.

  • Successfully developed innovative machine vision systems and data acquisition software for precision horticulture applications.

  • Played a key role in H2020 and EIP-AGRI projects involving machine learning and agricultural robotics.

🌟 Honors & Recognition

  • Recognized expert in precision horticulture and agricultural engineering with international collaborations and leadership roles.

  • Contributor to multiple international scientific journals and conferences, enhancing sustainable agricultural technology development.

Publication Top Notes:

Real-time applications in perennial trees and vegetables – A review

Developing an ISO11783-compliant prescription map for variable rate spraying in vineyards based on 3D canopy reconstruction

Fruit Detection and Yield Mass Estimation from a UAV Based RGB Dense Cloud for an Apple Orchard

Fruit Water Stress Index of Apple Measured by Means of Temperature-Annotated 3D Point Cloud

Fruit surface temperature data at different ripeness stages and ambient temperature provided as temperature-annotated 3D point clouds of apple trees

Hyper- and Multi-spectral Imaging Technologies

Prof. Bouabdellah Kechar | Smart Farming Awards | Best Innovation Award

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Prof. Bouabdellah Kechar | Smart Farming Awards | Best Innovation Award

Prof. Bouabdellah Kechar, University of Oran1 Ahmed Benbella, Algeria

Professor Bouabdellah Kechar, is a prominent Full Professor and Director of the RIIR laboratory at Oran1 Ahmed Benbella University. He earned his Bachelor’s degree in Mathematics in 1982, followed by an Engineering degree in Software from the Institute of Computer Science at the University of Oran Es-Sénia in 1987, both with excellent marks. He further advanced his studies by obtaining a Magister in Computer Science (CAD/IAO & Simulation) in 1997 and a PhD in Computer Science with a focus on Networking in 2010, both awarded with high honors. Professor Kechar’s research interests are diverse and encompass wireless sensor networks (WSN), Internet of Things (IoT) architectures, energy harvesting, machine learning, and cybersecurity, among other topics. He has taught various courses at the undergraduate and postgraduate levels, including wireless networks, information systems security, and advanced databases. As a dedicated educator, he has supervised 19 PhD theses and 18 Magister theses, contributing significantly to the academic development of his students. In addition to his teaching and research, he has evaluated numerous theses and developed educational materials. Professor Kechar maintains an active presence in the scientific community and can be contacted via email at kechar.bouabdellah@univ-oran1.dz.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Innovation Award:

Dr. Kechar Bouabdellah is a highly deserving candidate for the Best Innovation Award, thanks to his significant contributions and innovative approaches in the fields of wireless sensor networks (WSN), the Internet of Things (IoT), and cybersecurity. Here is a detailed summary highlighting his qualifications

Education 🎓

  • Bachelor’s Degree in Mathematics
    University of Oran, Algeria (1982)
  • Engineer in Software
    Institute of Computer Science, University of Oran Es-Sénia, Algeria (1987) – Very Good
  • Magister in Computer Science (CAD/IAO & Simulation)
    University of Oran Es-Sénia, Algeria (1997) – Very Honorable
  • PhD in Computer Science (Networking)
    University of Oran Es-Sénia, Algeria (2010) – Very Honorable

Work Experience 🏢

  • Full Professor / Director of the RIIR Laboratory
    Department of Computer Science, Faculty of Exact and Applied Sciences
    Oran1 Ahmed Benbella University, Algeria
  • Teacher-Researcher
    Engaged in teaching various courses at the undergraduate and graduate levels, including:

    • Wireless Sensor Networks
    • Information Systems Security
    • Cryptography and Security of Wireless Networks

Achievements 🏆

  • Supervision of Theses:
    • 19 PhD theses defended
    • 18 Magister theses defended
    • 44 Master’s theses (defended and in progress)
    • 10 Bachelor’s theses (defended and in progress)
  • Theses and Dissertations Evaluated:
    • Evaluated a total of 44 doctoral theses in Science and LMD
    • Evaluated 5 Magister’s theses

Awards and Honors 🥇

  • University Accreditations: 12
  • Recognized Contributions: Expertise in developing educational materials and supervising numerous successful theses.
  • International Recognition: Frequent participation in national and international conferences, enhancing collaboration and knowledge exchange in his fields of interest.

Publication Top Notes:

CITED:148
CITED:72
CITED:71
CITED:46
CITED:37

Mr. Huangfu Yi | Smart Agriculture Awards | Best Researcher Award

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Mr. Huangfu Yi | Smart Agriculture Awards | Best Researcher Award 

Mr. Huangfu Yi, Yunnan Agricultural University, China

Huangfu Yi is a dedicated and innovative Master’s degree candidate in Mechanical Design and Manufacturing at Yunnan Agricultural University, with a focus on smart agriculture, point cloud and image processing, and end-to-end object detection and perception. Born in Hohhot, Inner Mongolia, he earned his Bachelor’s degree in Computer Science and Technology from Inner Mongolia University of Science and Technology. Huangfu has contributed to the field through impactful research, including a method for panoramic image stitching of corn ears and the development of a citrus greening disease detection system. His work has led to accepted publications in SCI Zone 2 journals and has resulted in an authorized invention patent. With strong technical skills in deep learning, machine learning, and programming languages such as Java, C/C++, and Python, he is proficient in developing applications for agricultural solutions. Huangfu is also actively engaged in competitions, earning recognition for his programming skills. He is fluent in reading English literature, and his proactive involvement in work-study and volunteer activities has honed his communication skills and work ethic.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award: Huangfu Yi

Personal Profile: Huangfu Yi is a Master’s degree candidate at Yunnan Agricultural University, specializing in mechanical design and manufacturing. At just 26 years old, he has made significant strides in the fields of smart agriculture, point cloud and image processing, and end-to-end object detection and perception. His educational background, which includes a Bachelor’s degree in Computer Science and Technology, equips him with a strong foundation in technology that enhances his research capabilities.

🎓 Education Background:

  • Master’s Degree in Mechanical Design and Manufacturing
    Yunnan Agricultural University (2022.09 – 2025.09)
  • Bachelor’s Degree in Computer Science and Technology
    Inner Mongolia University of Science and Technology (2017.09 – 2021.07)

🔧 Projects and Contributions:

  • Panoramic Stitching System for Corn
  • Citrus Huanglongbing Detection System
  • Information Transmission Between Internet Sensors

📜 Patents:

  • Title: Method and Device for Detecting Huanglongbing Based on Deep Learning

🛠️ Research Skills:

  • Deep Learning, Machine Learning, Linux System Programming, Java, C/C++, PHP, Python, Web Crawling, OpenCV.

🏆 Competition Experience:

  • 2018: NAGC Software Engineer Certificate
  • 2019: National NetEase Security Cup, Excellent Prize
  • 2020: China University Student Programming Contest, Third Prize Nationally

Publication Top Notes

HHS-RT-DETR: A Method for the Detection of Citrus Greening Disease

Research on a Panoramic Image Stitching Method for Images of Corn Ears, Based on Video Streaming