THE LONG VIEW

Bottom Line Up Front: The relocation of renowned AI researcher Haibin Ling from Stony Brook University to China’s Westlake University represents a measurable strategic threat to U.S. leadership in foundational artificial intelligence research, particularly in computer vision and intelligent computing, with long-term implications for technological competitiveness and national security. Threat Identification: The loss of high-impact AI researchers like Ling—especially those with deep expertise in dual-use technologies such as visual tracking, AR/VR, and medical imaging algorithms—amplifies China’s growing capacity to innovate independently and potentially outpace U.S. advances in critical AI domains. Ling’s leadership of the Intelligent Computing and Application Lab at Westlake positions him to influence next-generation AI development within China’s national science framework. Probability Assessment: The trend of overseas Chinese scientists returning to China is accelerating; Ling’s move follows similar high-profile returns, including researchers from Google, MIT, and Stanford. This trajectory is highly probable to continue, especially given reported incentives such as greater research autonomy, state-backed funding, and strategic recruitment programs like China’s Thousand Talents Plan (or successors). The timeline for observable impact on China’s AI capabilities is 3–7 years, with early outputs likely in specialized vision systems and edge-AI deployment (citations: South China Morning Post, 2025; Clarivate, 2024). Impact Analysis: Ling’s work has been cited over 51,000 times (Google Scholar), and his contributions underpin technologies used in surveillance, autonomous systems, and healthcare diagnostics. His return transfers not only tacit knowledge but also international collaboration networks, which may be reoriented toward Chinese institutions. This weakens U.S. soft power in global AI research and increases the risk of technology divergence, where China sets standards in AI subfields without Western input. The broader impact includes reduced U.S. ability to anticipate emerging AI threats developed outside open academic channels. Recommended Actions: 1) Expand targeted retention programs for high-impact foreign-born researchers in sensitive AI fields; 2) Strengthen counter-recruitment initiatives via NSF and DOE innovation grants with long-term funding guarantees; 3) Monitor publications and patents emerging from Westlake University’s AI lab under Ling’s leadership; 4) Enhance visa and export control frameworks to track dual-use knowledge transfer while avoiding overreach that stifles collaboration; 5) Increase support for high-risk, high-reward research pathways in U.S. universities to match perceived agility in Chinese institutions. Confidence Matrix: Threat Identification – High confidence (based on verifiable career trajectory and institutional announcement); Probability Assessment – Medium-High confidence (supported by trend data and researcher statements); Impact Analysis – High confidence (leveraging citation metrics, IEEE recognition, and dual-use applicability); Recommended Actions – Medium confidence (dependent on political and budgetary factors). [Citations: VnExpress International, Dec 2025; SCMP, 2025; Clarivate Highly Cited Researchers 2024; IEEE VR 2021 Best Paper Award; NSF CAREER Award records] —Dr. Yuki Tanaka Dispatch from Moves S2