Why a rising AI star left a promising US academic career to return to China

Fu Tianfan leaves tenure-track assistant professor position in New York state for new research opportunities, and Nanjing University’s ‘fertile ground’

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Fu Tianfan, an expert in AI-powered scientific research, will pursue drug discovery and materials development at Nanjing University after spending several years in the United States. Photo: Handout

Published: 8:21pm, 25 Mar 2025Updated: 8:54pm, 25 Mar 2025

An expert in AI-powered scientific research, who studied and worked in the United States for several years, has returned home to China to pursue new opportunities emerging from the country’s rapid advances in artificial intelligence – particularly in pharmaceutical research.

Fu Tianfan, a former tenure-track assistant professor at Rensselaer Polytechnic Institute in Troy, New York, joined the School of Computer Science at Nanjing University in December. His work focuses on AI-driven drug discovery and materials development, according to his profile on the university’s website.

Fu, who is 32, said China’s growing investment in higher education had created unprecedented opportunities for young scientists like him.

“Nanjing University combines a rich cultural heritage with strong leadership in the natural sciences. Its broad strengths in basic science offer fertile ground for my research in applying artificial intelligence to accelerate scientific discovery,” Fu told the Post on Friday.

He added that being closer to his family after several years abroad was also a major factor in his decision.

AI technologies have profoundly transformed traditional scientific workflows, Fu said. In drug discovery, what once relied on time-consuming and costly trial-and-error experiments can now be accelerated with machine learning and big data.

Instead of manually testing thousands of compounds, researchers can now train deep learning models on known drug mechanisms and virtually screen vast molecular libraries to predict candidates with high therapeutic potential.