Jinming Wang (Mr)

I am interested in the following topics:

• Generative Methods: How to synthesize data or generate creative content using traditional algorithms or neural networks? My work explores advanced generative models such as Variational Autoencoders (VAE), Generative Adversarial Networks (GAN), and diffusion models, focusing on their applications in data-driven tasks.
• Urban Computing: Understanding urban dynamics is fundamental for smart city applications. My research aims to process and analyze urban data to provide more beneficial services to citizens, with a focus on trajectory processing, road network processing, urban planning, and traffic analysis.
• Spatio-temporal Data: I study the unique challenges and opportunities in analyzing and modeling data with both spatial and temporal dimensions, such as human or vehicle trajectories, environmental data, and dynamic urban systems.
• Computer Vision: My interests include the application of computer vision techniques in areas such as image segmentation, object detection, and scene understanding, particularly in urban and transportation domains.
• Neural Network Architectures: I enjoy exploring novel neural network architectures that improve efficiency, accuracy, and scalability. My focus includes graph neural networks, attention mechanisms, and hybrid models for structured and unstructured data.
• Reinforcement Learning: I am interested in leveraging reinforcement learning to solve sequential decision-making problems, especially in the context of traffic optimization, autonomous driving, and resource allocation in smart cities.
• Python: I have extensive experience using Python for a variety of tasks, including data analysis, machine learning, deep learning, and software prototyping. Python's versatility and rich ecosystem make it a key tool in my research and development.
• Program Design: I have a strong interest in designing and implementing efficient, maintainable, and scalable software systems. My work emphasizes clarity, modularity, and performance to ensure codebases are robust and easy to extend.

Currently, I am pursuing a PhD degree, where my research focuses on integrating generative methods and spatio-temporal data analysis to address complex urban challenges.