Assist. Prof. Dr. Hossein Bagherpour | Machine Learning Awards | Best Researcher Award

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Assist. Prof. Dr. Hossein Bagherpour | Machine Learning Awards | Best Researcher Award

Assist. Prof. Dr. Hossein Bagherpour, Department of Biosystems Engineering, Bu-Ali Sina Universit, Iran

Dr. Hossein Bagherpour is an accomplished Assistant Professor in the Department of Biosystems Engineering at Bu-Ali Sina University, where he has served since 2013. Holding a Ph.D. and M.Sc. in Biosystems and Agricultural Machinery Engineering from Tarbiat Modares University and a B.Sc. in Mechanical Engineering from the University of Tehran, his interdisciplinary expertise bridges advanced engineering with agricultural innovation. Dr. Bagherpour is a leading researcher in the application of artificial intelligence and machine vision in precision agriculture, with a focus on plant disease detection, crop quality assessment, and robotic harvesting. He has supervised multiple Ph.D. and M.Sc. theses on deep learning, image processing, and AI-driven diagnostics for crops like rose, wheat, hazelnut, and quince. His contributions significantly advance smart farming technologies, offering solutions for enhanced productivity and sustainable agriculture in small and large-scale systems.

Professional Profile:

GOOGLE SCHOLAR

ORCID

Summary of Suitability for Best Researcher Award – Dr. Hossein Bagherpour

Dr. Hossein Bagherpour is an exemplary candidate for the Best Researcher Award, recognized for his pioneering work at the intersection of biosystems engineering, artificial intelligence, and precision agriculture. As an Assistant Professor at Bu-Ali Sina University since 2013, Dr. Bagherpour has made significant contributions to the development and application of intelligent systems in agricultural automation and food quality assessment.

🎓 Education

  • 🧪 Ph.D. in Biosystems Engineering – Tarbiat Modares University, Tehran, Iran

  • 🚜 M.Sc. in Agricultural Machinery Engineering – Tarbiat Modares University, Tehran, Iran

  • ⚙️ B.Sc. in Mechanical Engineering (Design of Machinery) – University of Tehran, Tehran, Iran

🏢 Work Experience

  • 👨‍🏫 Assistant Professor, Department of Biosystems Engineering, Bu-Ali Sina University (2013–Present)

    • 📍 Faculty of New Agriculture, Room 207

    • 📍 Business Incubator Center No. 2, Room 7

🏆 Achievements & Contributions

  • 📊 Supervised numerous Ph.D. and M.Sc. theses focusing on AI, deep learning, and smart agricultural systems

  • 🤖 Developed algorithms for robotic harvesting, crop disease detection, and quality inspection using machine learning and computer vision

  • 📚 Published multiple research papers (see Google Scholar) in areas such as AI-based phenotyping, intelligent sensors, and agricultural robotics

🎖 Awards & Honors

  • 🌟 Recognized for advancing smart agriculture through AI integration

  • 🧠 Leader in AI-driven research in agricultural biosystems

Publication Top Notes:

Hyperparameter Optimization of ANN, SVM, and KNN Models for Classification of Hazelnuts Images Based on Shell Cracks and Feature Selection Method

Enhancing the Performance of YOLOv9t Through a Knowledge Distillation Approach for Real-Time Detection of Bloomed Damask Roses in the Field

Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases

Detection of different adulteration in cinnamon powder using hyperspectral imaging and artificial neural network method

Design, Construction, and Evaluation of a Precision Vegetable Reaper to Use in Small Plots

A New Method to Optimize Deep CNN Model for Classification of Regular Cucumber Based on Global Average Pooling

Dr. Jany Shabu | Artificial Intelligence Awards | Best Researcher Award

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Dr. Jany Shabu | Artificial Intelligence Awards | Best Researcher Award 

Dr. Jany Shabu, Sathyabama Institute of Science & Technology, India

Dr. S.L. Jany Shabu is an accomplished Associate Professor in the Department of Computer Science Engineering at Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India. With a Ph.D. in Image Fusion, her research focuses on multimodal image fusion using intelligent optimization techniques, particularly in the context of brain tumor detection. Dr. Shabu has a strong academic background, holding both M.Tech and MS degrees in Information Technology, and has published extensively, with 58 papers indexed in Scopus and four in WoS. She has received multiple accolades for her contributions to research and education, including cash awards for publishing in high-impact journals and the prestigious NPTEL Discipline Star Certificate. As an active member of the National Institute for Technical Training and Skill Development, Dr. Shabu is dedicated to advancing the field of computer science through her research, teaching, and professional engagement. Her innovative projects, including a Safety Stick for Elders, and her patents in smart traffic control and gesture-based systems, exemplify her commitment to leveraging technology for societal benefit. She has also authored several books on machine learning, cloud computing, and data analytics, further solidifying her reputation as a thought leader in her field. With a robust online presence, including profiles on ORCID and Scopus, Dr. Shabu continues to contribute to academic excellence and innovation in computer science.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award:

Dr. S.L. Jany Shabu is a commendable candidate for the Best Researcher Award, recognized for her significant contributions to computer science engineering and her innovative research in image fusion and optimization techniques.

Education 🎓

  • Ph.D. in Image Fusion
    Sathyabama Institute of Science and Technology
    Thesis Title: Multimodal Image Fusion using Intelligent Optimization Techniques with Brain Tumor Detection
  • M.Tech (IT) in Information Technology
    Sathyabama Institute of Science and Technology
    Graduated with First Class
  • M.S. (IT) in Information Technology
    Manonmaniam Sundaranar University
    Graduated with First Class

Work Experience 💼

  • Current Position: Associate Professor, Computer Science Engineering
    Sathyabama Institute of Science and Technology

Achievements 🌟

  • Seed Funding:
    Project Title: Safety Stick for Elders
    Amount: ₹300,000
    Period: Oct 2021 – June 2022
    Role: Co Principal Investigator
  • Patent Holder:
    1. SMART TRAFFIC CONTROL SYSTEM USING IOT BASED MONITORING SYSTEM
      Application No: 201741038384 – Published
    2. GARMENT STEAMER MANAGEMENT SYSTEM
      Application No: 367890-001 – Published
    3. GESTURE BASED ELECTRONIC GADGET OPERATING SYSTEM
      Application No: 202341088351 A – Published
  • Reviewer:
    • Journal of Scientific Research and Reports
    • Journal of Pharmaceutical Research International
    • International Conference on Computational Intelligence, Networks & Security
    • Book Chapter for CRC PRESS Taylor & Francis Group

Awards and Honors 🏆

  • Cash Award for Publishing Paper in High Impact WOS Journal
    Sathyabama Institute of Science and Technology (Teachers Day 2022 & 2024)
  • NPTEL Discipline Star Certificate
  • Disciplinarian Award
    Sathyabama Institute of Science & Technology, Chennai

Publication Top Notes:

DeepExuDetectNet: Diabetic retinopathy diagnosis: Blood vessel segmentation and exudates disease detection in fundus images

A swarm intelligence optimization for lung cancer detection from RNA-seq gene expression data using convolutional neural networks

A novel framework for entertainment robots in personalized elderly care using adaptive emotional resonance technologies

An Improved Adaptive Neuro-fuzzy Inference Framework for Lung Cancer Detection and Prediction on Internet of Medical Things Platform

Rainfall prediction using machine learning techniques

Online product review using sentiment analysis

Prof. Changgyun Kim | Artificial Intelligence Award | Best Researcher Award

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Prof. Changgyun Kim | Artificial Intelligence Award | Best Researcher Award 

Prof. Changgyun Kim, Department of Artificial Intelligence & Software/Samcheok,South Korea

Changgyun Kim is an esteemed academic and researcher associated with Kangwon National University, Department of Artificial Intelligence & Software, and Dongguk University’s Industrial Engineering department in South Korea. His research expertise spans deep learning, healthcare, and data mining. He has made significant contributions to the field, including developing AI-based systems for detecting betting anomalies in sports, diagnosing tooth-related diseases using panoramic images, and creating models for obesity diagnosis using 3D body information. His work is published in renowned journals such as Scientific Reports, Annals of Applied Sport Science, JMIR Medical Informatics, Sensors, Sustainability, the International Journal of Distributed Sensor Networks, and Applied Sciences. Dr. Kim’s notable projects include establishing IoT-based smart factories for SMEs in Korea and developing web applications for obesity diagnosis using data mining methodologies. His extensive research portfolio underscores his commitment to advancing AI applications in various domains

Professional Profile:

ORCID

 

Education

No specific details about Changgyun Kim’s educational background are provided in the provided information. To give a more comprehensive overview, details such as degrees obtained, institutions attended, and fields of study would be needed.

Work Experience

  1. Dongguk University: Jung-gu, Seoul, KR
    • Department: Industrial Engineering
    • Position: Not specified in the provided information.
  2. Kangwon National University
    • Department: Artificial Intelligence & Software
    • Position: Not specified in the provided information.

Publication top Notes:

 

AI-based betting anomaly detection system to ensure fairness in sports and prevent illegal gambling

Detectability of Sports Betting Anomalies Using Deep Learning-based ResNet: Utilization of K-League Data in South Korea

Tooth-Related Disease Detection System Based on Panoramic Images and Optimization Through Automation: Development Study

Development of an Obesity Information Diagnosis Model Reflecting Body Type Information Using 3D Body Information Values

Development of a Web Application Based on Human Body Obesity Index and Self-Obesity Diagnosis Model Using the Data Mining Methodology

Establishment of an IoT-based smart factory and data analysis model for the quality management of SMEs die-casting companies in Korea