On the afternoon of March 25, Sias University held the AI+X Experimental Class Industry–Education Dialogue at the lecture hall on the first floor of the library. Centered on the theme of “industry–education dialogue,” the event brought together experts to discuss educational transformation in the AI era and the cultivation of “human–AI collaborative dual-intelligence talent.”
Dr. Shawn Chen, Founder and Chairman of the Board, industry mentor Dr. Gao Qunyao, enterprise representative Li Ya, Program Director Dr. Xiao Fujun, along with representatives from the Academic Affairs Office, faculty members, student representatives, and participants of the AI+X Experimental Class attended the event. The session was chaired by Vice President Zhao Yuxin.
Prior to the meeting, guests toured the university’s holographic smart classroom, gaining first-hand insight into its development, teaching applications, and the university’s broader efforts in AI-enabled education and smart learning environments.
During the event, Dr. Shawn Chen, Dr. Gao Qunyao, and Li Ya jointly unveiled the AI+X Experimental Class Smart Classroom. The new facility will provide advanced support for course delivery, project-based training, and academic exchange within the program.
In his remarks, Dr. Shawn Chen emphasized that the AI+X Experimental Class represents a key initiative in deepening industry–education integration and advancing curriculum reform. The launch of the smart classroom, he noted, will create a more open, interactive, and intelligent learning environment for both faculty and students.
Dr. Xiao Fujun introduced the overall structure of the experimental class and outlined expectations for students’ future learning. He encouraged participants to actively explore new learning approaches, ask questions proactively, and quickly adapt to an efficient and engaged learning mode.
Dr. Gao Qunyao expressed strong support for the university’s AI+X initiatives. Drawing on his insights into industry transformation, he noted that artificial intelligence is reshaping not only tools but also job structures, workflows, and talent standards. He highlighted the program as a forward-looking effort to align talent cultivation with global trends, aiming to develop application-oriented professionals capable of solving real-world problems.
Li Ya also emphasized that AI competence is becoming a core competitive advantage in the workforce, with increasing demand for professionals who can design and build AI systems. She encouraged students to use the program as a starting point to explore the boundaries of human–AI collaboration and transition from traditional learners to value creators.
Faculty member Zhang Di from the School of Engineering and student Xu Donghui, majoring in Data Science and Big Data Technology, shared their teaching and learning experiences. Their insights covered areas such as teaching reform, course design, task optimization, assessment methods, project-based training, and common learning challenges, offering valuable guidance for future teaching and study.
During the interactive dialogue and Q&A session, guests and students engaged in lively discussions on talent development, curriculum design, project practice, and career preparation. The dynamic exchange of ideas highlighted the event’s strong emphasis on interaction and practical learning.
This dialogue represents an important step in advancing industry–education integration and exploring smart education at Sias University. It not only provided a high-level platform for collaboration among academia, industry, and enterprises, but also clarified the direction for cultivating “human–AI collaborative dual-intelligence talent.” Insights gathered from industry experts, corporate partners, and educators will support the continuous optimization of the program’s curriculum, project design, and teaching reform.
Looking ahead, Sias University will continue to strengthen the AI+X Experimental Class, align educational content more closely with industry needs, and cultivate high-quality, application-oriented talent equipped for the AI era.
