Academic Background:
- Ph.D. in Computer Science and Technology, Central South University (2019-2023)
- Major: Satellite multi-intelligence collaborative computing, digital twins, swarm intelligence negotiation, multi-intelligence deep reinforcement learning, online scheduling, artificial intelligence, machine learning.
- Master in Computer Science and Technology, Guizhou University (2015-2018)
- Major: Medical big data, big data analysis and prediction, deep learning, multi-label data classification, natural language processing.
- Bachelor in Network Engineering, Nanyang Institute of Technology (2010-2014)
- Major: Computer Networks, Principles of Computer Composition, Operating Systems, Algorithm Design.
Professional Experience:
- Data Analyst, Beijing Ark Hospital (June 2014-Sept 2015; Dec. 2023-Present)
- Responsibilities: Data cleaning, analysis, and visualization, system development and maintenance, research on satellite networks, collaborative computing, and edge computing.
- R&D Engineer, Hunan Lisen Data Technology Co Ltd (June 2018-Sept 2019)
- Responsibilities: Algorithm design, multi-platform software architecture design, software development, database management, interface development and design.
Projects and Leadership:
- Led projects on mixed integer programming for multi-process production scheduling, satellite and management software R&D, and real-time analysis methods for large-scale multi-source data based on supercomputing.
- Participated in significant research such as intelligent analysis technology for TFDS images and resource allocation technology based on collaborative perception.
Awards and Patents:
- Second prize in scientific and technological progress (2020)
- First prize in the Guizhou Province Innovation and Entrepreneurship Competition (2016)
- National third prize in the ‘Internet +’ College Students Innovation and Entrepreneurship Competition (2016)
- Invention Patents: Multi-agent Space-based Information Network Task Scheduling Method (2021), Dynamic Reconfigurable Space-based Information Network Simulation and Computing System (2022).
Skills:
- Proficient in software architecture design, Java, Python, C, and other programming languages.
- Experienced in leading R&D teams and writing research project applications.
Research Focus in Computer Science:
Huilong Fan’s research in Computer Science spans several advanced and interdisciplinary areas, primarily focusing on:
- Satellite Multi-Intelligence Collaborative Computing:
- Developing systems that allow multiple intelligent agents to work together effectively in satellite networks.
- Utilizing collaborative algorithms to improve the efficiency and reliability of satellite communications and operations.
- Digital Twins:
- Creating digital replicas of physical systems to simulate and analyze their real-world counterparts.
- Applying digital twin technology to monitor, diagnose, and optimize satellite and network operations.
- Swarm Intelligence Negotiation:
- Investigating algorithms that enable decentralized agents to coordinate and negotiate within a swarm.
- Using swarm intelligence for tasks such as resource allocation and scheduling in dynamic environments.
- Multi-Intelligence Deep Reinforcement Learning:
- Developing deep learning models that enable multiple intelligent agents to learn and adapt to complex environments.
- Applying these models to solve problems in satellite networks and edge computing.
- Online Scheduling:
- Researching methods for real-time scheduling of tasks and resources in dynamic and distributed systems.
- Focusing on optimizing the allocation of contact windows in satellite communication networks.
- Artificial Intelligence and Machine Learning:
- Applying AI and ML techniques to solve complex problems in big data analysis, prediction, and decision-making.
- Emphasizing multi-label data classification and natural language processing for diverse applications.
- Medical Big Data:
- Analyzing and predicting trends in medical data using big data technologies.
- Developing models for deep learning and multi-label classification to enhance medical data interpretation and application.
- Graph-Driven Resource Allocation:
- Utilizing graph theory and cooperative game theory to optimize resource allocation in Internet of Things (IoT) and satellite networks.
- Developing adaptive scheduling algorithms for real-time and dynamic environments.
Through his extensive research, Huilong Fan aims to push the boundaries of what is possible in satellite communication, edge computing, and AI, contributing significantly to advancements in these fields.
Publication Top Notes:
- Dynamic Network Resource Autonomy Management and Task Scheduling Method Li, X., Yang, J., Fan, H.
Mathematics, 2023, 11(5), 1232. Citations: 6
- A novel multi-satellite and multi-task scheduling method based on task network graph aggregation Fan, H., Yang, Z., Zhang, X., Long, J., Liu, L.
Expert Systems with Applications, 2022, 205, 117565. Citations: 15
- A Spatio-Temporal Graph Neural Network Approach for Traffic Flow Prediction Li, Y., Zhao, W., Fan, H.
Mathematics, 2022, 10(10), 1754. Citations: 6
- Quantum Digital Signature with Continuous-Variable Deng, X., Zhao, W., Shi, R., Ding, C., Fan, H.
International Journal of Theoretical Physics, 2022, 61(5), 144. Citations: 3