Ruo Hu | Computer Science | Best Keynote Speaker

Prof. Ruo Hu | Computer Science | Best Keynote Speaker

Guangdong Polytechnic Normal University | China

Professor Hu Ruo is a distinguished academician with a prolific background in artificial intelligence (AI) and medical image recognition. For over a decade, he has been leading graduate research in AI-driven medical diagnostics, with an emphasis on image-based disease classification and predictive systems. As a seasoned professor at Guangdong Polytechnic Normal University, his groundbreaking contributions have helped bridge clinical practice with intelligent systems, yielding innovations that benefit both academia and healthcare industries.

Professional profile👤

Scopus

Strengths for the Awards✨

Professor Hu Ruo brings a compelling blend of academic depth, technological innovation, and real-world collaboration that makes him exceptionally suitable for the “Best Keynote Speaker” award. With over a decade of leadership in AI-driven medical image recognition, his research is not only pioneering but also highly relevant to global health and AI advancements.

He holds three advanced degrees in computer science and information systems, complemented by long-standing teaching and research roles at esteemed Chinese institutions. His work spans key domains like deep learning, neuro-fuzzy systems, medical big data, and Internet of Things (IoT), with numerous peer-reviewed publications in top journals like Medical Physics and IEEE Transactions on Geoscience and Remote Sensing.

Prof. Hu has been PI of several government-funded high-impact projects, such as the Guangzhou Industry-University-Research Science & Tech project, with funding up to 2 million RMB, and has contributed to cross-sector collaborations with tech companies and hospitals. These collaborations have led to clinical applications, including tumor prediction systems and medical IoT platforms, underscoring his applied vision.

🎓 Education

Prof. Hu Ruo’s academic journey began with a Master of Science in Computer Science and Technology at Shaanxi Normal University (1987–1991). He then pursued a Master of Engineering in Computer Application at East China University of Science and Technology (1998–2002). Culminating his academic pursuits, he earned a Doctor of Management in Information System Management from the University of Shanghai for Science and Technology (2003–2006). His diverse interdisciplinary background forms a strong foundation for his research in AI applications.

🏢 Experience

Starting his career as a faculty member at the School of Mathematics and Computer Science, Ningxia University (1992–2007), Dr. Hu transitioned to the School of Computer Science, Guangdong Polytechnic Normal University in 2007. He was promoted to Associate Professor in 2006 and then to Full Professor in 2013. With over 30 years of teaching and research experience, he has played a pivotal role in shaping AI education and research methodologies in China.

🔬 Research Interests On Computer Science

Professor Hu’s research centers on AI in medical image recognition, big data semantic conflict resolution, neuro-fuzzy systems, and deep learning applications in disease diagnosis. He is particularly invested in the development of smart systems for tumor classification, sleep disorder diagnosis, and colorectal cancer detection. His work reflects a robust integration of knowledge-driven and data-driven models, contributing significantly to intelligent healthcare technologies.

🏅 Awards & Honors

Professor Hu Ruo has been the recipient of multiple prestigious research grants, including:

  • 2017 Guangzhou Industry-University-Research Major Science and Technology Project (¥2 million)

  • 2015 Guangdong Natural Science Foundation Project on big data and semantic conflict modeling (¥100,000)
    He has also received acclaim for his collaboration with high-tech companies and top medical institutions, cementing his reputation as a leader in interdisciplinary research.

📚 Selected Publications

Here are some of Professor Hu Ruo’s significant publications with citation details:

  1. Vision Transformer-based recognition of diabetic retinopathy grade, Medical Physics, 2021 — cited by numerous works in AI diagnostics.

  2. Diagnosis of sleep disorders in traditional Chinese medicine based on adaptive neuro-fuzzy inference system, Biomedical Signal Processing and Control, 2021 — contributed to fuzzy modeling in TCM.

  3. Research on data classification and feature fusion method of cancer nuclei image, International Journal of Imaging Systems and Technology, 2021 — applied deep learning in oncology.

  4. Locality Regularized Robust-PCRC framework for hyperspectral images, IEEE Transactions on Geoscience and Remote Sensing, 2020 — innovative feature extraction method.

  5. Key technologies for medical image knowledge discovery, International Journal of Pattern Recognition and Artificial Intelligence, 2020 — on intelligent knowledge systems.

  6. “A Mechanism for Healthy Big Data System Confliction Detection”, Basic & Clinical Pharmacology & Toxicology, 2016.

  7. “A New Efficiency Judging Method for Healthy Big Data”, Basic & Clinical Pharmacology & Toxicology, 2016.

  8. “Sensor Network Component Searching Method”, Journal of Investigative Medicine, 2015.

  9. “Semantic Data Network Analysis System”, Journal of Computer, 2013.

  10. “Stability Analysis of IoT Service via Data Stream Methods”, Applied Mathematics & Information Sciences, 2012.

🤝 Collaborations

Prof. Hu collaborated with Guangzhou Jinglian Information Technology Co., Ltd. to develop an AI-powered cloud platform for tumor prediction and postoperative classification. This was based on his earlier Guangdong-funded big data project. He also engaged in clinical-level partnerships with Sun Yat-sen University Cancer Prevention Center and Sixth Affiliated Hospital, providing valuable datasets and expertise for AI training and medical validation.

🎓 Supervision & Mentorship

Professor Hu has mentored numerous graduate theses, including work on deep learning for colorectal cancer, fuzzy systems for sleep disorders, and image-based diagnostics for lung and brain tumors. His students have published in top-tier journals and contributed to a total of 10 high-impact papers and 5 patents under his leadership.

🏁 Conclusion

In conclusion, Professor Hu Ruo exemplifies the spirit of innovation and interdisciplinary excellence. With a solid academic background, pioneering research in medical AI, and extensive industry and clinical collaborations, he stands out as a prime candidate for the Best Keynote Speaker. His work has not only advanced academic knowledge but also translated into tangible tools that enhance modern healthcare.

Gokalp Çınarer | Artificial Intelligence | Best Researcher Award

Assist. Prof. Dr. Gokalp Çınarer | Artificial İntelligence | Best Researcher Award

Yozgat Bozok University Computer Engineering Department | Turkey

Dr. Gökalp Çınarer is an Assistant Professor in the Department of Computer Engineering at Yozgat Bozok University. His expertise lies in artificial intelligence, machine learning, image processing, and deep neural networks. Over the years, he has contributed significantly to the academic community with applications of AI in diverse fields, including medicine, agriculture, food technologies, and environmental analysis.

Professional profile👤

Google Scholar

ORCID

Scopus

Strengths for the Awards✨

  • Diverse Research Portfolio: Dr. Çınarer has made significant contributions across multiple domains — medicine, agriculture, food technologies, and environmental analysis — leveraging artificial intelligence and machine learning, showcasing versatility and cross-disciplinary impact.
  • High Research Output: With over 50 publications indexed in SCI-Expanded, SSCI, and Scopus, his research output is impressive, indicating a consistent contribution to advancing knowledge in computer engineering and AI applications.
  • Innovative Work in Medical Imaging: His PhD thesis on brain tumor detection through image processing and classification algorithms reflects a critical application of AI in medical diagnostics, directly contributing to healthcare advancements.
  • Academic Leadership: As Head of the Department of Information Processing and Computer Engineering Software at Yozgat Bozok University, Dr. Çınarer plays a pivotal role in shaping academic programs, guiding research initiatives, and mentoring students.
  • Teaching Excellence: He teaches a broad range of courses, including Machine Learning, Deep Learning, and Artificial Intelligence Applications, fostering the next generation of AI researchers and practitioners.

🎓 Education

Dr. Çınarer earned his PhD in Computer Engineering from Kırıkkale University between 2017 and 2021. His doctoral research focused on “Detection of Brain Tumors with Image Processing Techniques and Analysis with Classification Algorithms.”

💼 Experience

Since 2021, Dr. Çınarer has been serving as the Head of the Department of Information Processing and the Head of the Department of Computer Engineering Software at Yozgat Bozok University. He teaches undergraduate and graduate courses, including Machine Learning, Deep Learning, Python Programming, Algorithm Analysis, and Artificial Intelligence Applications.

🔬 Research Interests On Artificial Intelligence

Dr. Çınarer’s research interests encompass artificial intelligence, machine learning, image processing, and deep neural networks. His work delves into AI applications across various fields such as medicine, agriculture, food technologies, and environmental analysis.

🏆 Awards

Dr. Çınarer has been recognized for his pioneering work in artificial intelligence and its applications across multiple disciplines, earning accolades for his contributions to AI-driven medical analysis and agricultural technologies.

📚 Publications

  • Classification of brain tumors by machine learning algorithms
    Authors: G Çınarer, BG Emiroğlu
    Year: 2019
    Citations: 74

  • Prediction of Glioma Grades Using Deep Learning with Wavelet Radiomic Features
    Authors: G Çınarer, BG Emiroğlu, AH Yurttakal
    Year: 2020
    Citations: 57

  • Öğretmenlerin Teknolojik Araçlarla Eğitime Yönelik Tutumlarının Çeşitli Değişkenlere Göre İncelenmesi Yozgat İli Örneği
    Author: G Çınarer
    Year: 2016
    Citations: 27

  • Classification of hazelnuts according to their quality using deep learning algorithms
    Authors: N Erbaş, G Çınarer, K Kiliç
    Year: 2022
    Citations: 21

  • A comparative study on segmentation and classification in breast mri imaging
    Authors: AH Yurttakal, H Erbay, T İkizceli, S Karacavus, G Çinarer
    Year: 2018
    Citations: 21

  • Brain Tumor Classification Using Deep Neural Network
    Authors: G Çınarer, BG Emiroğlu, RS Arslan, AH Yurttakal
    Year: 2020
    Citations: 16

  • Application of various machine learning algorithms in view of predicting the CO2 emissions in the transportation sector
    Authors: G Çınarer, MK Yeşilyurt, Ü Ağbulut, Z Yılbaşı, K Kılıç
    Year: 2024
    Citations: 11

  • Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation: Proceedings of the INFUS 2021 Conference
    Authors: G Çınarer, C Kahraman, S Cebi, SC Onar, B Oztaysi, AC Tolga, IU Sari
    Year: 2021
    Citations: 9

  • Classification of Diabetic Rat Histopathology Images Using Convolutional Neural Networks
    Authors: AH Yurttakal, H Erbay, G Çınarer, H Baş
    Year: 2021
    Citations: 8

  • A Deep Transfer Learning Framework For The Staging Of Diabetic Retinopathy
    Authors: G Çınarer, K Kılıç, T Parlar
    Year: 2022
    Citations: 6

📄 Conclusion

Dr. Gökalp Çınarer stands at the forefront of AI research, leveraging machine learning and image processing to solve complex problems in medicine, agriculture, and environmental science. His work continues to inspire advancements in interdisciplinary fields and pave the way for future innovations.