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.

Shidong Liang | Quantum mechanics | Best Researcher Award

Prof. Dr. Shidong Liang | Quantum mechanics | Best Researcher Award

Emeritus Professor, Ph.D. at Sun Yat-sen University, China

Dr. Shi-Dong Liang is a leading researcher in theoretical and condensed matter physics. His contributions to quantum mechanics and mathematical physics have been widely recognized. He developed novel approaches to non-Hermitian quantum systems and Finsler geometry in physics. His work on quantum tunneling, noncommutative physics, and topological states has influenced numerous areas of physics research. He continues to advance the understanding of quantum phenomena and their applications.

Profile

ORCID

Educational

      • Dr. Shi-Dong Liang received his Ph.D. in Physics from The University of Hong Kong in 1999. Following this, he pursued postdoctoral research at the Institute of Physics, Academia Sinica, Taiwan, from 1999 to 2001.

Professional Experience

Since 2001, Dr. Liang has been a tenured Associate Professor at Sun Yat-sen University. His research interests span theoretical condensed matter physics, theoretical physics, gravity, and mathematical physics. Over his academic career, he has published over 85 research papers and authored three books. His work is well-recognized, with an H-index of 19, reflecting significant contributions to his fields of expertise. Additionally, Dr. Liang has served as an editor for multiple special issues and collaborated on projects involving quantum geometry and uncertainty relations.

Research Interests

Dr. Liang’s recent research focuses on noncommutative quantum mechanics. He developed a theoretical framework based on the Heisenberg representation of noncommutative relations, proposing innovative methods to explain novel physical phenomena, such as particle-antiparticle asymmetry, quantum decoherence, and the nature of dark matter and dark energy. His expertise extends to condensed matter physics, quantum mechanics, gravity theory, and financial physics.

Author Metrics

  • Research Papers: 85 (Indexed in SCI and Scopus)
  • Books Published:
    1. Quantum Tunneling and Field Electron Emission Theories (World Scientific Press, 2014) [ISBN: 978-9814440219]
    2. Special Issue on New Advances in Quantum Geometry (MDPI, 2023) [ISBN: 978-3-0365-8770-7]

Publications