2026 CSRankings Released: Nanjing University's AI Discipline Tops the World
Recently, the authoritative ranking in the field of computer science, 2026 CSRankings, was officially released. In the global ranking of the artificial intelligence discipline, Nanjing University ranked first globally with a score of 23.7, setting a new historical best performance for domestic universities in this ranking.
More notably, the top 10 positions are all occupied by domestic institutions, marking that China's artificial intelligence research strength has officially reached the top of the world.
Ranking Interpretation: Domestic Universities Form an AI "Cluster Advantage"
From the ranking, it can be seen that domestic universities have formed a cluster advantage in the AI field. The top 10 positions are all occupied by domestic institutions, and the score gradient among top universities is clear.
Core Data of the Global Top 10
| Rank | University | Score |
|---|---|---|
| 1 | Nanjing University | 23.7 |
| 2 | Zhejiang University | 20.7 |
| 3 | Harbin Institute of Technology | 18.5 |
| 8 | Shenzhen University | — |
Among them, Shenzhen University from the Greater Bay Area ranks eighth, demonstrating the rapid rise of regional AI research strength.
Nanjing University's AI Leader: Academician Zhou Zhihua's Team
As the leader of Nanjing University's AI discipline, Academician Zhou Zhihua's team at Nanjing University has long been deeply engaged in machine learning, fundamental theories and applications of artificial intelligence.
Core Research Directions and Achievements
- Ensemble Learning: One of the team's leading directions, with achievements published multiple times at top international conferences.
- AutoML: Automated machine learning, forming broad academic influence.
- Emphasis on both fundamental theory and applications, covering multiple frontier branches of machine learning.
The research output in these directions is an important support for Nanjing University's high score in CSRankings.
Explanation of the CSRankings Evaluation Mechanism
The evaluation of CSRankings is based on the publication output of faculty from global universities at top conferences, rather than subjective reputation surveys.
Key Evaluation Points
- The statistical subjects are faculty members from global universities.
- Based on the quantity and quality of their papers published at top computer science conferences.
- Rankings are subdivided by discipline direction, with artificial intelligence being one of them.
Therefore, this ranking is often used by engineering and technical personnel and procurement as an objective reference for evaluating the AI research strength of universities.
Reference Value for Industry and Procurement
For the industrial instrumentation and automation industry, the AI discipline ranking reflects the source strength of algorithms and talent supply. Breakthroughs by universities in directions such as machine learning and AutoML will gradually penetrate into scenarios such as smart instruments, predictive maintenance, and edge computing.
When evaluating AI partners or technical solutions, procurement and technical personnel can pay attention to whether the team has top conference paper output and continuous research capabilities.
(Yangcheng Evening News · Yangcheng Pai, compiled from the Jiangsu Communist Youth League WeChat public account and Xinhua Daily)