Professor at North China University of Technology Beijing, China
Prof. Li Ma is a distinguished Professor and Dean of the School of Information Science at North China University of Technology, Beijing. He also serves as a Doctoral Supervisor at Beijing University of Technology. With over three decades of academic and research contributions, Prof. Ma has authored and co-authored more than journal and conference papers. His scholarly journey began with a B.S. degree from Beijing Institute of Technology , followed by an M.S. from North University of China , and a Ph.D. from Beijing Institute of Technology . His research spans artificial intelligence, advanced computing, and physical oceanography, integrating interdisciplinary approaches to solve complex challenges. A recognized leader, he is a Distinguished Member of the China Computer Federation (CCF), and an active member of IoT committees, IEEE-CS, and ACM. Prof. Ma continues to guide innovation while mentoring the next generation of researchers.
Professional Profile
Scopus Profile
Education
Prof. Li Ma academic foundation is built upon rigorous training at prestigious Chinese institutions. He earned his B.S. degree from Beijing Institute of Technology, one of China’s leading centers for science and engineering education. He then pursued his M.S. degree at North University of China, Shaanxi, where he further specialized in computational and information sciences. With a growing passion for advancing artificial intelligence and computing technologies, he returned to Beijing Institute of Technology for doctoral studies, successfully completing his Ph.D. During his doctoral journey, he focused on exploring advanced models and algorithms, setting the stage for his prolific academic career. This educational pathway provided him with a strong balance of theoretical expertise and applied research training, enabling him to later contribute significantly to AI, computational sciences, and interdisciplinary applications in fields such as physical oceanography.
Experience
Prof. Li Ma professional journey reflects leadership in both academia and research. Currently, he serves as Professor and Dean of the School of Information Science at North China University of Technology, Beijing, where he oversees academic development, curriculum innovation, and interdisciplinary research. Additionally, he holds the position of Doctoral Supervisor at Beijing University of Technology, mentoring Ph.D. candidates and guiding cutting-edge projects in artificial intelligence and advanced computing. His contributions extend beyond teaching and supervision he has authored over research papers, shaping knowledge in AI algorithms, model optimization, and computational sciences. As an influential figure, he also leads academic innovation teams across Beijing municipal universities, fostering collaborative networks. Beyond his institutional roles, he actively participates in professional societies such as CCF, IEEE-CS, and ACM, strengthening global research ties. With decades of experience, Prof. Ma continues to bridge science, technology, and education for future advancements.
Research Interest
Prof. Li Ma research interests are diverse and interdisciplinary, bridging computer science with applied fields. His core expertise lies in artificial intelligence technology, particularly in developing robust models that enhance accuracy, allocation algorithms, attention mechanisms, and bounding box optimization. He also explores deep learning applications, focusing on classification head architectures, loss functions, and anchor boxes within image recognition systems, including real-world datasets like COCO. Another dimension of his research extends to complex computational dependencies and buffer space optimization, enhancing the efficiency of AI-driven systems. Uniquely, Prof. Ma also applies computational models to physical oceanography, integrating AI with environmental and marine sciences. This interdisciplinary approach highlights his vision of combining data science, machine learning, and computational modeling to solve critical problems across science and technology. His work reflects innovation at the crossroads of advanced computing, AI research, and environmental applications.
Award and Honor
Prof. Li Ma has earned recognition as a leading scholar and academic leader. He is a Distinguished Member of the China Computer Federation (CCF), a prestigious acknowledgment of his contributions to computer science research and development in China. He is also an active member of IEEE Computer Society and ACM, which reflects his international engagement and commitment to advancing global standards in computing and AI. Beyond memberships, Prof. Ma leads an Academic Innovation Team supported by Beijing Municipal Colleges and Universities, showcasing his leadership in fostering research excellence and interdisciplinary collaboration. His roles as Dean and Doctoral Supervisor further illustrate the trust placed in him to shape future researchers and contribute to academic policy. While specific individual awards were not listed in the available record, his professional honors demonstrate recognition at both national and international levels in AI, computing, and interdisciplinary science.
Research Skill
Prof. Li Ma possesses a broad range of advanced research skills that position him at the forefront of computer science and AI. His expertise includes algorithm design and optimization, focusing on allocation methods, classification models, and bounding box refinement for image recognition tasks. He has strong command over deep learning frameworks, applying attention mechanisms, anchor boxes, and classification head models to improve accuracy and system performance. Additionally, his skills in large-scale dataset utilization (e.g., COCO dataset) enable him to test, validate, and refine machine learning models effectively. His computational skills extend into buffer space optimization and handling complex dependencies, key for enhancing efficiency in AI-driven environments. Beyond technical areas, he demonstrates leadership in interdisciplinary applications, especially in using AI for physical oceanography and environmental modeling. These skills, combined with over publications, reflect his ability to merge theory with impactful real-world applications.
Publication Top Notes
Title: FedECP: Enhancing global collaboration and local personalization for personalized federated learning
Journal: Knowledge Based Systems
Year: 2025
Title: A verifiable EVM-based cross-language smart contract implementation scheme for matrix calculation
Journal: Digital Communications and Networks
Year: 2025
Title: Construction of Low-latency Artificial Intelligence of Things for Marine Meteorological Forecasting
Journal: Tien Tzu Hsueh Pao Acta Electronica Sinica
Year: 2025
Title: Blockchain-Based Trust Model for Inter-Domain Routing
Journal: Computers Materials and Continua
Year: 2025
Title: Multivariate Short-Term Marine Meteorological Prediction Model
Journal: IEEE Transactions on Geoscience and Remote Sensing
Year: 2025
Title: A trusted IoT data sharing method based on secure multi-party computation
Journal: Journal of Cloud Computing
Year: 2024
Title: Obstacle Avoidance Method Using DQN to Classify Obstacles in Unmanned Driving
Journal: Jisuanji Gongcheng (Computer Engineering)
Year: 2024
Title: A quantum artificial bee colony algorithm based on quantum walk for the 0-1 knapsack problem
Journal: Physica Scripta
Year: 2024
Title: MIMA: Multi-Feature Interaction Meta-Path Aggregation Heterogeneous Graph Neural Network for Recommendations
Journal: Future Internet
Year: 2024
Conclusion
Prof. Li Ma is an accomplished scholar in computer science, artificial intelligence, and computational technologies, currently serving as Dean of the School of Information Science at North China University of Technology and Doctoral Supervisor at Beijing University of Technology. With over publications and citations, his research contributions span AI model optimization, federated learning, blockchain systems, IoT, marine meteorological forecasting, and quantum-inspired algorithms.