Outstanding IBSS Faculty-Student Collaboration Leads to Two Notable Papers

Recently, two papers co-authored by the faculty and student from the International Business School Suzhou (IBSS) at Xi’an Jiaotong-Liverpool University (XJTLU) have garnered widespread attention in academic and industry circles. Under the mentorship of Professor Hefei Wang, Associate Dean for Academic Engagement, Zhenhao Li's graduation thesis, titled “Integrating Multi-Temporal Feature Ranking with Forecasting Models for Enhanced Stock Price Prediction,” was accepted by the International Conference on Neural Information Processing (ICONIP), a renowned core A computer science conference. Additionally, a collaborative paper by Professor Wang, Zhenhao Li, and Professor Xun Liang from Renmin University of China, “A Bone to Pick with Ancient Chinese: AI Analysis of Handedness in Bone Inscriptions,” has been highlighted by the South China Morning Post."

Upon completing his undergraduate studies at IBSS, Zhenhao was deeply drawn to the school’s advanced hardware facilities and open learning atmosphere, and thus decided to continue his pursuit of a master degree at IBSS. His curiosity about the interdisciplinary operation of machine learning and high-frequency financial data became the chosen topic for his master thesis. Zhenhao explained, “Financial data, especially high-frequency data, is relatively easy to obtain. The combination of finance and machine learning is relatively mature in the research field, providing the basis for my research.” This choice of research direction also marked the beginning of his collaboration with Professor Wang.

Zhenhao’s research involves constructing a vast dataset and delving deeply into the implicit features of different financial time series, with the aim of enhancing the accuracy of stock price prediction. He explained that the framework of his paper resonated with Professor Wang due to a mutual selection process. With dual degrees in mathematics and computer science, Professor Wang possesses extensive research experience in finance, aligning perfectly with Zhenhao’s interests. Professor Wang also highly values Zhenhao’s exceptional independent thinking and solid theoretical foundation. She highlighted, "Our collaboration is a mutual learning process. Although it can be challenging for teachers to keep up with the latest research methods amidst a busy schedule sometimes, interacting and communicating with students like Zhenhao provides me with opportunities to engage with cutting-edge research methods."

During the guidance of his graduation thesis, Professor Wang's rigorous approach to scientific research and meticulous mentorship enabled Zhenhao to swiftly identify and address experimental deviations. Furthermore, impressed by his enthusiasm for machine learning and appreciative of his research assistant skills, Professor Wang invited him to join another interdisciplinary project. This project utilized artificial intelligence to investigate ancient texts. Having undergone the rigorous training of two practical projects, Zhenhao humbly acknowledged his evolution from a novice to a capable practitioner in the field of machine learning. He learned to analyze and process data and information from a more systematic viewpoint and to employ models for more profound analysis.

As artificial intelligence technology advances and becomes deeply integrated into various sectors, Professor Wang emphasizes that integrating AI into scientific research and teaching is a key part of both her personal goals and the school's strategic development. She actively encourages faculty and students to engage in cutting-edge, interdisciplinary collaborative projects, fostering knowledge exchange and sparking innovation. Zhenhao advises students to thoroughly research relevant literature before joining collaborative projects. He suggests consolidating theoretical knowledge through practical experience and clarifying research interests to select the right mentors.

Looking ahead, IBSS will continue to promote academic research and educational innovation to cultivate future research leaders. Zhenhao also plans to pursue a doctoral degree related to large-scale models, exploring broader academic fields and uncover new chapters.