Sichuan University (SCU)
四川大学

China

Sichuan University is one of the earliest modern universities in China, with a history that can be traced back to the Sichuan Sino-Western School founded in 1896. The current Sichuan University is the result of two mergers, first with the former Chengdu University of Science and Technology and then with the former West China University of Medical Sciences. The expanded Sichuan University has three campuses --- Wangjiang, Huaxi and Jiang’an in the historical and cultural city of Chengdu, sprawling 7,050 mu (approximately 470 hectares).

With a long tradition in education, Sichuan University has, over the past 120 years, given rise to many academic heavyweights, industrial elites and leading administrators who are pillars of the society. Its famous alumni include Zhu De, one of the founding fathers of the People’s Republic of China, and Yang Shangkun, China’s former president, as well as Guo Moruo and Ba Jin, renowned masters of modern Chinese literature, who have all once studied at Sichuan University. Moreover, over 50 academicians of the Chinese Academy of Sciences (CAS) and the Chinese Academy of Engineering (CAE) are Sichuan University alumni.

Currently, the university is dedicated to cultivating globally competitive innovators. It has more than 37,000 full-time undergraduate students and 20,000-plus master and PhD candidates, as well as nearly 3,000 international students.

The university offers a comprehensive range of disciplines to its students, with 33 colleges, covering 12 subject areas, such as humanities, science, engineering and medicine. According to Thomson Reuters’ Essential Science Indicators (ESI), 13 of its disciplines, including chemistry, clinical medicine, engineering, pharmacology and toxicology, biology and biochemistry, mathematics, physics, neuroscience and behavioral science, molecular biology and genetics, agricultural sciences, plant and animal sciences and social science are ranked among the global top 1%. Particularly, chemistry is ranked among top 1‰ globally.

With a strong faculty team of 5,238 full-time faculty members, including 1,051 full professors, 1,230 associate professors and 15 CAS and CAE academicians, Sichuan University has built robust research programs, having made a series of representative research achievements. For example, Feng Xiaoming’s catalytic asymmetric Roskamp reaction provided a new method for the synthesis of chiral compounds. Studies on carbon capture and utilization (CCU) and CO2-mineralization are promoting the rise of a new energy industry in China and even globally. Cross-disciplinary studies on translational medicine led to an innovative technological chain of gene discovery – drug R&D – clinical treatment. In 2014 alone, 3,647 papers were published in journals listed in the Science Citation Index (SCI). Based on the Nature Index data in 2014, Sichuan University is ranked at 106th among global academic institutions.

The university’s research strength is also demonstrated in 13 national-level research bases and four state-level international science and technology cooperation bases. Having achieved many national-level science and technology awards, the university has already become a major driver of the socioeconomic development in western China.

Looking forward, Sichuan University is committed to making greater contributions to the progress of society and human civilization.

Find Sichuan University’s custom publishing on Nature

1 May 2017 - 30 April 2018

Region: Global
Subject/journal group: All

The table to the right includes counts of all research outputs for Sichuan University (SCU) published between 1 May 2017 - 30 April 2018 which are tracked by the Nature Index.

Hover over the donut graph to view the FC output for each subject. Below, the same research outputs are grouped by subject. Click on the subject to drill-down into a list of articles organized by journal, and then by title.

Note: Articles may be assigned to more than one subject area.

AC	FC
225	123.24

Outputs by subject (FC)

Subject	AC	FC
Chemistry	144	90.15
Life Sciences	40	13.26
Physical Sciences	45	21.10
Earth & Environmental Sciences	6	2.06

Highlight of the month

Harnessing artificial intelligence for diagnosis

A tool that uses the power of neural networks to aid the interpretation of biomedical images could help doctors diagnose and treat diseases, according to a study in Cell.

The use of artificial intelligence for analyzing medical images, such as X-ray and magnetic resonance imaging (MRI) scans, to support diagnostic decision making has faced accuracy and interpretation challenges.

Now, an international team of scientists, including researchers from Sichuan University in China, has used neural networks to assist clinicians in diagnosing diabetic retinopathy, a condition in which an excess of blood sugar damages blood vessels in the back of the eye.

A neural network analyses images of a patient’s eye obtained using a special retina camera to determine the presence of macular degeneration and diabetic retinopathy. This is the first artificial intelligence diagnostic device to be approved by the US Food and Drug Administration.

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