Artificial Intelligence and Software Engineering Research Center

Location:Hengqin Science and Technology Innovation Center (In Process)

Description:

The M.U.S.T. Artificial Intelligence and Software Engineering Research Center (M.U.S.T. AI + SE Research Center) is led by Associate Professor Rubing Huang. It mainly explores artificial intelligence (AI), software engineering (SE), and the cross-applications of AI and SE. Research contents mainly include intelligent software engineering, trustworthy AI, software testing and maintenance, computer vision and image processing, and AI applications.

Equipment:

The research center has provided a Supermicro SYS-740GP-TNRT 4U GPU super server, specially designed for high-performance computing tasks. The server is equipped with an Intel Xeon Silver 4314 processor, has 16 cores and 32 threads, supports DDR4 memory up to 3200MT/s, and is configured with a total of 128GB of memory. In terms of storage, the server is equipped with a 960GB SSD and a 2.4TB 10K RPM SAS hard drive to ensure fast data reading and writing performance. To meet high-performance computing needs, the server is also equipped with two Nvidia 3090 24GB GPU cards, which are suitable for scientific computing in the fields of deep learning, machine learning, and software engineering.

Research Projects:

1. Intelligent Recommendation Driven Adaptive Testing Framework and Methods of Complex Software Systems, 2023.12~2026.11

2. Adversarial Perturbation for Privacy Protection in Social Networks, 2023.01~2025.12

3. Micro-Expression Recognition Technology for Lie Detection Applications, 2023.12~2025.12

4. Key Technologies and Applications for Content Detection Generated by Artificial Intelligence, 2023.12~2025.12

5. Privacy Protection of Social Platforms Based on Discrete Lupine Adversarial perturbation, 2024.01~2026.12

6. Visual Adversarial Perturbation for Digital Property Rights and Privacy Protection, 2023.10~2026.10.

7. Near-Neighbor-Search Driven Adaptive Random Testing Methods, 2021.12~2023.05

8. Regression Testing by Multi-Information Dynamic Extraction, Fusion, and Correlation, 2019.01~2022.12

9. Multi-Information Driven Random Testing Methods by Adaptively Adjusting Test Profiles, 2023.01~2024.07