The Data Science and Intelligent Computing Laboratory recruits international students in the field of electronic information, mainly covering three directions: computer science and technology, software engineering, and computer application technology. The direction of computer science and technology focuses on intelligent algorithms, system architecture, and computational theory, conducting research on artificial intelligence basic models, dynamic graph learning, and trusted computing; The software engineering direction focuses on the modeling, analysis, and quality assurance of large-scale software systems, with a particular emphasis on exploring intelligent software development methods, program understanding, and automated testing techniques; The direction of computer application technology emphasizes the implementation of technology and cross disciplinary integration, committed to promoting the systematic application of artificial intelligence in smart cities, healthcare, intelligent manufacturing and other scenarios.

The research covers inference optimization, context enhancement, and lightweight deployment of large language models, exploring their capability boundaries in code generation, knowledge services, and multi round conversations; In the field of multimodal intelligence, research is conducted on visual language joint modeling, cross modal retrieval and generation techniques to enhance the model's ability to understand complex semantics; At the level of intelligent systems, a computational framework is constructed to support collaborative decision-making among group intelligent agents, and research is conducted on multi-agent path planning, task allocation, and consistency control; At the same time, in terms of underlying supporting technologies, we will promote 3D reconstruction algorithms, high-dimensional data compression and rendering optimization in light field imaging, as well as resource scheduling and energy efficiency management mechanisms for heterogeneous computing environments. The related work has formed a complete chain from theoretical innovation to system implementation, providing a solid scientific research foundation and practical platform for graduate students.