Seok-Woo Jang | Computer Vision | Best Researcher Award

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Prof. Seok-Woo Jang | Computer Vision | Best Researcher Award

Associate Professor at Anyang University South Korea

Dr. Seok-Woo Jang is an Associate Professor in the Department of Software at Anyang University, Korea. With extensive experience in computer science and software engineering, he has contributed significantly to the fields of image processing, artificial intelligence, and human-computer interaction. His research spans biometrics, computer vision, and information security. Over the years, he has actively participated in numerous research projects and published widely in internationally recognized journals. Dr. Jang’s academic journey and professional experience highlight his dedication to advancing technology through innovative research and education.

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Education

Dr. Seok-Woo Jang obtained his Ph.D. in Computer Science from Soongsil University, Seoul, Korea, in 2000. His doctoral dissertation focused on “Shot Transition Detection by Compensating Camera Operations,” showcasing his early expertise in image and video processing. He completed his Master’s degree in Computer Science from the same institution in 1997, researching velocity extraction of moving objects through cluster analysis. His academic foundation was laid with a Bachelor’s degree in Computer Science from Soongsil University in 1995.

Experience

Dr. Jang’s professional career spans over two decades in academia and research. He has been a Professor at Anyang University since 2009, contributing to software education and research. Prior to that, he was a Research Professor at Sungkyunkwan University from 2008 to 2009. His industry and research experience include roles as a Senior Researcher at the Korea Institute of Construction Technology and a Principal Researcher at the Institute of Industrial Technology Research at Soongsil University. He has also conducted post-doctoral research at the University of Massachusetts, Boston, and the University of North Carolina at Charlotte. His teaching experience includes lecturing at Soongsil University and Sungkyul University.

Research Interests

Dr. Jang’s research focuses on multiple domains, including 2D/3D image processing, human-computer interaction, biometrics, information security, and pattern recognition. He is particularly interested in digital video data indexing, computer vision, object tracking, and image surveillance. His work also extends to developing innovative techniques for harmful content detection and deep learning-based solutions in software engineering and AI-driven image analysis.

Awards

Dr. Jang has received numerous awards for his contributions to research and academia. He was awarded the Best Paper Award at the International Conference on Small and Medium Business in 2018 for his work on harmful content extraction using learning algorithms. In 2016, he received the Best Researcher Award at Anyang University. He also won the Best Paper Award at the International Conference on Digital Policy and Management in 2013 for his work on dynamic camera switching. His achievements have been recognized internationally, including being listed in Marquis Who’s Who in the World in 2008.

Publications

Dr. Jang has authored numerous peer-reviewed publications. Some of his notable works include:

“Detection of Ventricular Fibrillation Using Wavelet Transform and Phase Space Reconstruction from ECG Signals” – Journal of Mechanics in Medicine and Biology, 2021.

“Pupil Detection and Gaze Tracking Using a Deformable Template” – Multimedia Tools and Applications, 2020.

“Robust Hand Pose Estimation Using Visual Sensor in IoT Environment” – The Journal of Supercomputing, 2019.

“Harmful Content Detection Based on Cascaded Adaptive Boosting” – Journal of Sensors, 2018.

“A Monitoring Method of Semiconductor Manufacturing Processes Using Internet of Things-based Big Data Analysis” – International Journal of Distributed Sensor Networks, 2017.

“Learning-based Detection of Harmful Data in Mobile Devices” – Mobile Information Systems, 2016.

“An Adaptive Camera-Selection Algorithm to Acquire Higher-Quality Images” – Cluster Computing, 2015.

Conclusion

Dr. Seok-Woo Jang is a highly deserving candidate for the Best Researcher Award. His extensive academic credentials, innovative research projects, influential publications, and numerous awards establish him as a leading researcher in his field. His contributions to computer vision, biometrics, and artificial intelligence continue to push the boundaries of technology, making a lasting impact on both academia and industry.

Duaa Mehiar | Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr Duaa Mehiar | Artificial Intelligence | Best Researcher Award

Assistant Professor, Middle East University, Jordan

Duaa Mehiar is an expert in Artificial Intelligence and Robotics, currently part of the Department of IT at Middle East University. She has a strong background in developing intelligent robotic systems, optimizing robotic swarm behaviors, and exploring AI applications in education and healthcare. Duaa is passionate about the intersection of technology and practical solutions, particularly in enhancing robot autonomy and improving human-robot interactions. She has contributed significantly to research in robotic optimization and AI systems, with numerous publications in international journals.

Professional Profile

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Strengths for the Award

Duaa Mehiar is an accomplished researcher in the fields of Artificial Intelligence (AI) and Robotics. With a PhD in AI from the University of Malaya, her extensive academic background, demonstrated by her impactful research on optimization methods in robot swarm behaviors, makes her a prime candidate for the Best Researcher Award. Her published works in high-impact journals and international conferences, including contributions to cloud-based frameworks for social robotics and AI-based systems for education, have received recognition in academia. Duaa’s research on dynamic task distribution in drone swarms and deep fake image detection also highlights her broad expertise in both practical applications and cutting-edge AI research.

Areas for Improvement

Although Duaa has made significant strides in her research, further collaboration with interdisciplinary teams in the fields of neuroscience and psychology could enhance the human-robot interaction aspects of her work, especially with virtual agents. Expanding the scope of her research to explore more industry-based applications of her findings, particularly in education and healthcare, would also make her work more impactful. Additionally, more emphasis on real-world robotic deployments could demonstrate her research’s practical outcomes.

Education

  • Ph.D. in Artificial Intelligence – University of Malaya, 2016–2021
    Thesis: Improving Robot Darwinian Particle Swarm Optimization Using Quantum-Behaved Swarm Theory for Robot Exploration and Communication
  • MSc in Computer Science – Al Balqa Applied University, Jordan, 2007–2009
    Thesis: The Multi-Robot Cooperative System for Objects Detection
  • B.Sc. in Computer Science – Al Zaytoona University, Jordan, 1998–2002
    Graduation Project: Production System for Oriental Arabs using Oracle Language

Experience

Duaa Mehiar has a wealth of experience in the field of robotics and AI. She has trained teachers and school supervisors on integrating AI into education, including using metaverse and robots. Duaa was involved in numerous training programs with institutions like EduTech and Ishraq Institute. She has contributed to robotic research and development, from swarm optimization algorithms to practical applications like controlling robots using various protocols. Her expertise includes IoT projects and robot building using Arduino technology.

Awards and Honors

Duaa has received multiple honors for her work in robotics and AI. She was nominated as a trainer for the Ministry of Education in Dubai and Ras Al Khaima for teaching robotic theory and practice. She has also been part of the Arab Robotics Association and has served as a judge for the Arab Robotics Competition. Her research in AI and robotics has been recognized by international platforms, earning her citations and respect within the scientific community.

Research Focus

Duaa’s research primarily focuses on AI and robotics, particularly in optimization algorithms for swarm robots, human-robot interaction, and AI applications in education and healthcare. She has developed quantum-behaved swarm optimization methods for robot exploration and communication. Her interests include improving robotic autonomy, integrating robots in educational environments, and exploring AI systems in healthcare, such as asthma management and rehabilitation. She is dedicated to advancing AI technologies to benefit society.

Publication Top Notes

  • Revolutionizing Social Robotics: A Cloud-Based Framework for Enhancing the Intelligence and Autonomy of Social Robots 🤖
  • Towards Renewable Urban Landscapes: Exploring Photovoltaic Panel Integration – A Case Study 🌍
  • Chatbots in Classrooms: Tailoring Education and Boosting Engagement 🎓
  • QRDPSO: A New Optimization Method for Swarm Robot Searching and Obstacle Avoidance in Dynamic Environments 🤖
  • Customized Convolutional Neural Network for Accurate Detection of Deep Fake Images in Video Collections 🎥
  • Report on Optimization for Efficient Dynamic Task Distribution in Drone Swarms Using QRDPSO Algorithm 🚁
  • Linguistic and Gender Factors in User Engagement with Arabic LLM-Based Virtual Agents for Rehabilitation 🧑‍💻
  • Real-Time Student Attention Evaluation and Engagement Recommendation System Using AI-Based Behavior Analysis 📚
  • Personalized Alarming System for Asthma Management Based on Lung Functionality 🫁
  • Reducing Interrupts Among Robots in Quantum-Behaved Swarm Exploration with MR-LEACH 🤖
  • Improving Robot Darwinian Particle Swarm Optimization Using Quantum-Behaved Swarm Theory for Robot Exploration and Communication 🔍
  • Multi-Robot Cooperative System for Object Detection 🤖
  • QRDPSO Equation: A New Optimization Method for Swarm Robot 🏎
  • Multi-Agent Cooperative System for Object Detection 🛠
  • Multi-Robot System for Search and Rescue Operations 🚑

Conclusion

Duaa Mehiar stands out for her contributions to the fields of AI and Robotics, with a focus on innovative solutions to enhance autonomous robotic systems and optimize AI-driven tasks. She demonstrates strong academic potential, with a portfolio of research that is not only technically sound but also socially relevant, particularly in education and healthcare. For the Best Researcher Award, her continued growth in interdisciplinary collaboration and real-world applications would solidify her place as a leading researcher in her field.

Prasad Mutkule | Machine Learning | Best Researcher Award

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Mr Prasad Mutkule | Machine Learning | Best Researcher Award

Assistant Professor, Sanjivani College of Engineering, Kopargaon, India

Prasad Mutkule is an accomplished academic and researcher serving as an Assistant Professor at Sanjivani College of Engineering, Kopargaon. He holds expertise in Machine Learning, Data Science, and Artificial Intelligence, contributing significantly to academia and industry. His work spans developing advanced algorithms for healthcare and agriculture, with a strong emphasis on practical applications. Prasad is known for his dedication to research and education, mentoring students and fostering innovation.

PROFILE

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STRENGTHS FOR THE AWARD

  1. ACADEMIC BACKGROUND:
    • Advanced academic qualifications, including a pursuing Ph.D. in Computer Engineering, focusing on cutting-edge research.
    • High academic performance in Master’s and Bachelor’s programs, showcasing a strong foundation in computer engineering.
  2. RESEARCH CONTRIBUTIONS:
    • A significant number of publications in reputed journals and conferences.
    • Research topics include brain tumor segmentation, agriculture disease detection, predictive analytics in healthcare, and integration of AI/ML for societal applications like cybersecurity and smart farming.
    • Contributions are well-cited, with notable impact in the field of computational intelligence and applied machine learning.
  3. PROFESSIONAL EXPERIENCE:
    • Diverse professional background encompassing academia and industry, with over 6 years in teaching and 1 year in Android development.
    • Current role as an Assistant Professor at a reputed autonomous institution emphasizes leadership in research and teaching.
  4. MULTIDISCIPLINARY IMPACT:
    • Research spans critical areas such as healthcare, agriculture, and traffic prediction, reflecting versatility.
    • Innovative projects like IoT-based interactive clothing and AI-based health monitoring systems underscore practical applications of research.
  5. TEAM COLLABORATION:
    • Collaboration with various researchers and authors in multiple publications, indicating strong teamwork and networking abilities.

AREAS FOR IMPROVEMENT

  1. ONGOING RESEARCH FOCUS:
    • Completing the Ph.D. will further solidify expertise and enhance research credentials.
    • Exploring patent filings or practical implementations of research outcomes could amplify real-world impact.
  2. INCREASED GLOBAL PRESENCE:
    • Expanding participation in international conferences or collaborations could increase visibility on a global scale.
  3. FOCUSED SPECIALIZATION:
    • While multidisciplinary research is a strength, deeper specialization in one or two niches can establish leadership in specific domains.
  4. FUNDING AND GRANTS:
    • Securing funded projects or grants for research would demonstrate recognition and support for work.

EDUCATION

  • Ph.D. (Computer Engineering) – Pursuing at Vishwakarma Institute of Information Technology, Pune, affiliated with Savitribai Phule Pune University (2023–ongoing).
  • M.E. (Computer Engineering) – Completed at Sanjivani College of Engineering, Kopargaon, Savitribai Phule Pune University, with a CGPA of 8.25 (2016–2018).
  • B.E. (Computer Engineering) – Graduated from Sanjivani College of Engineering, Kopargaon, under Savitribai Phule Pune University, achieving 68.46% (2012–2016).

EXPERIENCE

  • Assistant Professor, Sanjivani College of Engineering (2021–present).
  • Assistant Professor, Shri Chatrapati Shivaji Maharaj College of Engineering, Ahmednagar (2021).
  • Assistant Professor, Adsul’s Technical Campus, Ahmednagar (2019–2021).
  • Lecturer, S.P.I.T. Polytechnic, Ahmednagar (2017–2019).
  • Android Developer, Advitiya IoT Solutions, Pune (2016–2017).

AWARDS AND HONORS

  • Recognized for impactful research contributions in Machine Learning and Artificial Intelligence.
  • Awarded for excellence in teaching and academic service.
  • Published influential papers in top-tier journals.
  • Honored as a mentor for guiding student innovations in computing and IoT.
  • Esteemed presenter at international conferences.

RESEARCH FOCUS

Prasad Mutkule focuses on developing intelligent systems using Machine Learning and Data Science. His areas of interest include healthcare diagnostics, agricultural optimization, and IoT applications. He aims to bridge the gap between academia and industry through innovative solutions in Artificial Intelligence and its transformative applications.

PUBLICATION TOP

📘 Development of machine learning and medical-enabled multimodal for brain tumor classification.
📗 Manipulation of flowering time to mitigate high temperature stress in rice.
📘 Identification of disease based on symptoms using ML.
📗 Efficient supervised learning algorithm for kidney stone prediction.
📘 One-stop solution for farmer-consumer interaction.
📗 Interactive clothing based on IoT with QR codes.
📘 A survey on interactive IoT-based clothing applications.
📗 ML algorithms for agricultural leaf disease detection.
📘 Predictive analytics for early brain tumor prevention using XAI.
📗 Applicability of AI in healthcare, banking, and education.

CONCLUSION

Prasad Mutkule has a strong academic and professional portfolio that demonstrates his expertise in machine learning, artificial intelligence, and their applications in healthcare and beyond. His research contributions are impactful, multidisciplinary, and address real-world challenges. With continued focus on specialization and global engagement, he is an excellent candidate for the Best Researcher Award.

Jiaming Zhong – Artificial intelligence – Best Researcher Award

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Jiaming Zhong - Artificial intelligence - Best Researcher Award

Wuyi university - China

AUTHOR PROFILE

SCOPUS

📚 SCIENTIFIC RESEARCH ACHIEVEMENTS

Jiaming Zhong has made significant contributions to the fields of video classification and tactile sensing. His groundbreaking papers include "Exploring Cross-video Matching for Few-shot Video Classification via Dual-Hierarchy Graph Neural Network Learning," published in Image and Vision Computing, and "Text-guided Graph Temporal Modeling for Few-Shot Video Classification," featured in Engineering Applications of Artificial Intelligence. These studies, published in top-tier journals, highlight Zhong's innovative approaches in utilizing graph neural networks and multimodal models for advanced video analysis and classification.

🛠️ PATENTS AND TECHNOLOGICAL INNOVATIONS

Zhong holds several patents that showcase his expertise in developing practical solutions for various technological challenges. His patents include methods for video anomaly classification, chip defect detection, and mobile robot obstacle avoidance. These patents reflect his commitment to translating theoretical research into tangible technological advancements that address real-world problems.

🔬 PROJECT EXPERIENCE: PEEL RECOGNITION

In a project focused on the precise identification of Chenpi years using a multimodal model, Zhong's work involved designing lightweight modules and fine-tuning models to achieve high recognition accuracy. His use of the CLIP multimodal model for feature extraction led to a remarkable 99% accuracy in recognizing Chenpi years with limited sample data. This project, detailed on GitHub, demonstrates his proficiency in applying advanced machine learning techniques to practical problems.

🎥 PROJECT EXPERIENCE: FEW-SHOT VIDEO CLASSIFICATION

Zhong's research in video behavior classification involved addressing challenges related to data scarcity and model capabilities. Collaborating with Macau University of Science and Technology and Wuyi University, he developed a dual-hierarchy graph neural network that significantly improved classification performance through cross-video frame matching. This innovative approach was published in Image and Vision Computing and showcased Zhong's ability to enhance model performance through sophisticated temporal modeling.

🔍 PROJECT EXPERIENCE: MULTIMODAL REPRESENTATION LEARNING

In a project focused on multimodal video behavior analysis, Zhong led efforts to develop a novel framework for self-supervised learning using multimodal data. This project, supported by a 500,000 RMB research grant, involved developing a text-guided feature optimization module and a query text token learning mechanism. His research aimed to leverage multimodal knowledge to improve the classification performance of few-shot video behaviors, with results published in top journals.

📈 IMPACTFUL RESEARCH AND PUBLICATIONS

Zhong's work has significantly impacted the fields of video classification and sensor technology. His papers in renowned journals and his patents contribute to advancing the understanding and application of these technologies. His research not only addresses current challenges but also paves the way for future innovations in these areas.

🏆 ACKNOWLEDGEMENTS AND RECOGNITION

Zhong's contributions to scientific research and technology have earned him recognition within the academic and professional communities. His innovative work in video classification and sensor technology continues to influence the field and inspire further research and development.

NOTABLE PUBLICATION

Ultra-sensitive and stable All-Fiber iontronic tactile sensors under high pressure for human movement monitoring and rehabilitation assessment
Authors: K. Ma, D. Su, B. Qin, Y. Xin, X. He
Year: 2024
Journal: Chemical Engineering Journal

Real-time citrus variety detection in orchards based on complex scenarios of improved YOLOv7
Authors: F. Deng, J. Chen, L. Fu, J. Li, N. Li
Year: 2024
Journal: Frontiers in Plant Science

Exploring cross-video matching for few-shot video classification via dual-hierarchy graph neural network learning
Authors: F. Deng, J. Zhong, N. Li, D. Wang, T.L. Lam
Year: 2023
Journal: Image and Vision Computing