Academic Exchange

Zeng Shiping’s journey into economics was somewhat unexpected. “Before I chose my university major, my understanding of ‘economics’ was rooted in the idea of 'benefiting society,' a discipline steeped in humanistic ideals. However, upon entering the field, I found it filled with extensive mathematical proofs and derivations,” he explains. This stark contrast between his expectations and the reality of economics—a field rich in complex mathematical models—marked the beginning of his research path, which was a serendipitous turn of events.

Although it diverged from his initial expectations, Zeng began to find enjoyment in economic research through literature reviews, model simulations, and writing papers. He noted, “The economic conclusions derived from mathematical models and data-driven approaches feel rigorous and grounded.” Encouraged by top scholars in economic statistics like Kevin Fox and Erwin Diewert, he embarked on a new journey into big data. While collaborating on a research project with the Australian Bureau of Statistics, he developed a productivity model and code suited for high-efficiency calculations, tackling datasets involving millions of enterprises. This experience was pivotal when he discovered a job opportunity at the Shenzhen Big Data Research Institute that required a combination of economics and computer science expertise. The alignment of these fields thrilled him: “Economics, programming, big data, and government-related topics—all these elements perfectly matched.”

After joining the Government and Enterprise Big Data Laboratory, Zeng quickly took on his first project as an execution leader. This project was commissioned by the Shenzhen Science and Technology Innovation Commission, focusing on specialized research for high-tech enterprises in the city. During the project, he increasingly realized the importance of having a background that fused economics and computer science. His knowledge of management and business functions facilitated his understanding of the project, while programming skills enabled quantitative analysis. This synergy allowed the research to progress smoothly. Alongside his team, he collaborated with leading banking institutions to provide targeted marketing solutions through big data modeling, achieving significant results from the first round of experiments. He expressed optimism about the laboratory’s efficient organizational structure and international talent team, believing that their experiences and cases will lead to broader and deeper collaborations with government and enterprise sectors.

Reflecting on the evolution of big data, Zeng noted, “2013 was dubbed the ‘year of big data,’ and ten years later, big data has penetrated various industries, playing a crucial role.” He recalled his earlier interpretation of economics as “benefiting society,” realizing that both he and the Shenzhen Research Institute of Big Data are committed to contributing to social development. What initially appeared to be a coincidence in his career path has proven to lead to a common goal. As a young researcher, Zeng sees a similar “youthful” characteristic in the institute: “The research institute is a young platform,” he expressed with heartfelt emotion. “In just a few years, its scientific output and social impact resemble those of a long-established research institution. The contrast between this youthfulness and depth is both surprising and inspiring.”

When discussing advice for other young researchers, Zeng shared his experiences of navigating the dual pressures of mastering both economics and big data technologies. “But doing the right thing is rarely effortless. Success doesn’t have to happen in my time, but my efforts will not be in vain,” he asserts. He believes that young people, full of vigor and unafraid of challenges, are inspired by the vast potential of the big data field, motivating them to overcome obstacles and forge ahead.