Feng Hu | Multi-modal feature recognition | Best Researcher Award

Assoc Prof Dr. Feng Hu l Multi-modal feature recognitionΒ | Best Researcher Award

Communication University of China, China

Author Profile

Scopus

Early Academic Pursuits πŸŽ“

Assoc. Prof. Dr. Feng Hu’s academic journey began with a deep interest in communication and information systems. He earned his Ph.D. in Communication and Information Systems from the prestigious Communication University of China (CUC), Beijing, in 2013. This educational foundation set the stage for his distinguished career in the fields of wireless communications, media convergence, and related technologies, shaping his future research and academic contributions.

Professional Endeavors and Contributions 🌐

Dr. Feng Hu is a prominent figure in the domain of 5G/6G wireless communications, and his professional journey has been marked by several key roles. Since December 2018, he has been an Associate Professor at Communication University of China and a master tutor, where he plays a significant role in mentoring future engineers and researchers. He has also been an active member of the Working Group of Radio, Film, and Television Administration for Wireless Interactive Radio and Television, as well as a member of the Working Group of 5G Broadcast. These positions have allowed him to contribute to the development and regulation of cutting-edge technologies in the media and communications sector.

Research Focus and Impact πŸ”¬

Dr. Hu’s research interests lie in the development of transmitting and receiving techniques for 5G and 6G wireless communications. His work focuses on optimizing wireless communication systems, utilizing machine learning, and exploring optimization theory to enhance the efficiency and performance of modern communication technologies. His research has significant implications for the advancement of wireless communication systems, contributing to the global transition to next-generation technologies and improving communication capabilities in various sectors.

Technical Skills and Expertise βš™οΈ

Dr. Hu is highly skilled in the areas of wireless communications, machine learning, and optimization theory. His expertise includes developing novel algorithms and techniques for 5G/6G systems, addressing challenges in data transmission, signal processing, and system optimization. He is proficient in applying advanced mathematical models and machine learning approaches to improve communication systems’ performance, reliability, and security, making him a key player in advancing the state-of-the-art in wireless communications.

Teaching Experience and Mentorship 🍎

As an Associate Professor and master tutor, Dr. Hu is deeply involved in shaping the next generation of professionals in communication and information systems. He has taught a variety of undergraduate and graduate-level courses, imparting his knowledge in wireless communications, machine learning, and optimization. His mentorship extends beyond the classroom, guiding students in research and academic pursuits, while fostering a culture of innovation and critical thinking in the field of communications.

Legacy and Future Contributions 🌱

Dr. Hu’s legacy is rooted in his pioneering work in the development of 5G/6G wireless communication systems and his significant contributions to the academic and professional communities. Looking ahead, he aims to continue pushing the boundaries of wireless communication technologies, with a particular focus on optimizing next-generation communication networks and integrating machine learning approaches to improve system efficiencies. His future contributions will likely influence both academic research and practical implementations in the rapidly evolving fields of wireless communications and media convergence.

Academic Citations and Recognition πŸ†

Dr. Feng Hu’s research has garnered recognition in top-tier academic journals and conferences in the fields of communication systems and wireless technology. His work has not only contributed to the scientific community but has also influenced industry practices and standards in wireless communication. He continues to be a sought-after figure in academic circles, providing valuable insights into the development of 5G/6G systems and machine learning applications in communications.

Professional Affiliations and Leadership 🌍

Dr. Hu is an active member of several esteemed organizations, including IEEE and the Society of Communications, where he holds the prestigious title of Senior Member. His involvement in key working groups related to wireless interactive radio and television and 5G broadcast further highlights his leadership in shaping the future of communication technologies. These affiliations enhance his ability to drive impactful research and contribute to the global dialogue on the future of communication systems.

Future Outlook and Innovation πŸš€

With his vast expertise in wireless communication systems and emerging technologies, Dr. Hu’s future endeavors will focus on leading innovations in 6G communication systems, integrating artificial intelligence and machine learning to enhance system performance, and tackling the challenges posed by next-generation wireless networks. His ongoing research will play a critical role in shaping the future of global communication, advancing both academic theory and practical applications in the field.

Β Top Noted PublicationsΒ πŸ“–

SDDA: A progressive self-distillation with decoupled alignment for multimodal image–text classification

Authors: Chen, X., Shuai, Q., Hu, F., Cheng, Y.
Journal: Neurocomputing
Year: 2025

EmotionCast: An Emotion-Driven Intelligent Broadcasting System for Dynamic Camera Switching

Authors: Zhang, X., Ba, X., Hu, F., Yuan, J.
Journal: Sensors
Year: 2024

Β Asymptotic performance of reconfigurable intelligent surface assisted MIMO communication for large systems using random matrix theory

Authors: Hu, F., Zhang, H., Chen, S., Zhang, J., Feng, Y.
Journal: IET Communications
Year: 2024

Real-Time Multi-Service Adaptive Resource Scheduling Algorithm Based on QoE

Authors: Li, W., Li, S., Hu, F., Yin, F.
Conference: 2024 IEEE 12th International Conference on Information and Communication Networks, ICICN 2024
Year: 2024

5G RAN Slicing Resource Allocation Based on PF/M-LWDF

Authors: Hu, F., Qiu, J., Chen, A., Yang, H., Li, S.
Conference: 2024 4th International Conference on Computer Communication and Artificial Intelligence, CCAI 2024
Year: 2024

Jing An | Artificial Intelligence | Best Researcher Award

Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

πŸ‘¨β€πŸŽ“Professional Profile

Scopus Profile

πŸ‘¨β€πŸ« Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

πŸŽ“ Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Master’s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

πŸ’Ό Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships πŸš€.

πŸ“š Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

πŸ”§ Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

πŸ§‘β€πŸ« Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

πŸ” Research Interests

Dr. An’s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

πŸ“–Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020