Associate Professor at Shandong Computer Science Center (National Supercomputing Center in Jinan), China
Dr. Hao Hao currently serves as an Associate Researcher at Qilu University of Technology and the Shandong Provincial Computing Center (National Supercomputing Jinan Center). His expertise lies in computer science and technology, with a focus on mobile edge computing, task offloading, reinforcement learning, and intelligent optimization for multimedia systems. His contributions to resource allocation, privacy protection, and large-scale distributed systems demonstrate his pioneering role in advancing high-performance computing and its applications in critical areas such as emergency response and wireless communications.
Professional Profile
Scopus Profile
Education
He completed his academic journey in computer science and technology at Beijing University of Posts and Telecommunications, earning his bachelor’s, master’s, and doctoral degrees in succession. This strong academic foundation provided him with a solid background in algorithms, distributed systems, and artificial intelligence, enabling him to contribute significantly to the fields of edge computing and wireless communication technologies. His research training at this leading institution prepared him for impactful scientific inquiry and innovation in both theoretical and applied computing.
Experience
Following his academic training, Dr. Hao Hao began his career as a lecturer at the College of Electronic Countermeasures, National University of Defense Technology, where he contributed to advanced teaching and research in computational technologies. He then joined Qilu University of Technology and the Shandong Provincial Computing Center, initially as an Assistant Researcher and later as an Associate Researcher. In these roles, he has been deeply involved in high-performance computing, mobile edge intelligence, and cooperative system design. His current position at the National Supercomputing Jinan Center allows him to advance cross-disciplinary research while contributing to national priorities in computing infrastructure and technological innovation.
Research Focus
His research primarily centers on mobile edge computing, multi-UAV cooperative task scheduling, reinforcement learning methods for computation offloading, and privacy-preserving group intelligence sensing. He has explored optimization strategies for resource allocation, trajectory design in UAV networks, and fairness-aware computing solutions. His work also spans mobile multimedia systems, heterogeneous network optimization, and green communications. Supported by competitive research grants from the National Natural Science Foundation of China (NSFC) and the Shandong Provincial Science and Technology Department, his projects address pressing challenges in computationally intensive multimedia, emergency computing, and mobile caching technologies.
Awards and Honors
Dr. Hao Hao has made remarkable contributions recognized through multiple academic patents and funded projects. He has secured support as Principal Investigator for the NSFC Young Scientists Fund on emergency computing for multimedia applications and for the Shandong Provincial Natural Science Foundation on mobile edge caching technologies. His patents, including methods for fairness-aware task offloading and cooperative optimization in computing systems, highlight his ability to transform theoretical research into practical innovations. These achievements underscore his scientific leadership and dedication to advancing computational intelligence in real-world applications.
Publication Top Notes
Title: DART: A Dynamic Adaptive Framework for Reducing Idle Waiting Time in Cloud-Edge Collaborative Inference
Summary: Proposes a dynamic adaptive framework minimizing idle waiting time in cloud-edge collaborative inference, enhancing efficiency and responsiveness of distributed AI systems.
Title: A Deep Reinforcement Learning-based Collaborative Edge Caching Approach for AIoT
Summary: Introduces a deep reinforcement learning strategy for collaborative edge caching in AIoT, improving data availability, latency reduction, and system performance.
Conclusion
Through his strong academic background, professional experience, and sustained contributions to cutting-edge research, Dr. Hao Hao has established himself as an influential scholar in computer science and technology. His work in mobile edge computing, reinforcement learning, and task offloading has advanced the state-of-the-art in both theory and practice. With impactful publications, patented innovations, and successful research projects, he has demonstrated excellence in both independent and collaborative research. His trajectory reflects not only technical innovation but also a commitment to advancing computational methods that address real-world challenges, making him a highly deserving candidate for recognition in this award nomination.