In July, with the promotion of the Shanghai Jing’an District Human Resources and Social Security Bureau, CASCO and Tsinghua University deepened university-enterprise collaboration. Both parties will focus on core demands of intelligent and digital transformation of rail transit, and jointly carry out cutting-edge research. During this period, CASCO will provide a summer social practice platform for 4 Tsinghua PhD students. Relying on research projects, both parties will jointly explore innovative applications of breakthrough technologies such as artificial intelligence, big data, and large models in rail transit scenarios.

Component Selection and Quality Evaluation System Based on AI

It aims to build an intelligent agent system for component selection and quality evaluation by innovatively applying AI and data mining technologies, committed to solving problems such as component reliability assessment, batch anomaly avoidance, and quality consistency assurance, so as to improve equipment screening efficiency and quality control.

Application of Generative AI in Safety Analysis of Rail Transit Signaling

It focuses on human-machine interaction pain points in safety analysis of rail transit signaling systems, explores innovative applications of generative AI in the field of human factors engineering, builds an intelligent safety analysis workflow, and comprehensively improves the efficiency and accuracy of safety analysis.

Design and Verification of Rail Transit Signaling Systems Based on MBSE Method

Based on MBSE (Model-Based Systems Engineering) theory and practical methods, it conducts in-depth research on the design, simulation verification, and digital twin technology application of rail transit signaling systems, laying a foundation for the design and optimization of future complex systems.

Identification of Safety Circuit Failure Modes Based on AI

It deeply integrates AI and circuit principles to develop a new safety circuit failure mode identification technology, which can identify and eliminate potential hardware safety hazards at the design stage, and improve the reliability of safe operation of rail transit system.

To ensure the research achieve practical results, CASCO gives full play to its resource advantages such as technical accumulation, project experience, and industry insights in rail transit, and provides solid data foundation and clear industrial demand orientation for the research, which effectively guarantees the practicality and forward-looking nature of the research.

At the same time, CASCO carefully selects and assigns senior technical experts to serve as mentors, providing one-on-one guidance throughout the process. They not only answer students' professional questions, but also guide the students to effectively translate the theoretical models and methodologies they have learned into feasible solutions to meet the actual needs of enterprises.

As the research progresses, the students have come to learn that scientific research can only be truly converted into practical value and serve social needs when it steps out of the laboratory and takes root in the industry. They have stated that this experience has not only enhanced their scientific research abilities, but also accumulated valuable experience for their future contributions to society.

The successful scientific research collaboration has demonstrated CASCO's high attention to talent cultivation and its relentless pursuit of technological innovation. With research projects as the link, CASCO will further deepen university-enterprise collaboration, and committed itself to joining hands with more outstanding talents to jointly explore cutting-edge technologies and assist the sustainable development of the rail transit industry.