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SZTU's 1st Röntgen AI class officially launched

Edited by:Release Time:2020/06/15

The launching ceremony of the first Röntgen Artificial Intelligence Program (hereinafter referred to as Röntgen AI class) of Shenzhen Technology University (SZTU) was held on June 9, witnessed by Prof. Ruan Shuangchen, president of SZTU, heads of relevant departments, instructors and 30 students of the program.


The launching ceremony of Röntgen AI class is successfully held. [Photo/Party Affairs Committee Publicity Office]


SZTU President Ruan Shuangchen congratulates the students selected for the program. [Photo/Party Affairs Committee Publicity Office]


Prof. Ruan Shuangchen congratulated 30 students from College of Big Data and Internet of SZTU selected for Röntgen AI class. It was jointly launched by University of Applied Sciences Würzburg-Schweinfurt (FHWS) and SZTU, he said, representing our university philosophy of adopting opening-up policies and training internationalized talents. He hoped that they can become professionals with global visions, making good use of three-year undergraduate education in China and two-year master’s education abroad.


Prof. Liu Hongwei and Prof. Zeng Siyu make speeches. [Photo/Party Affairs Committee Publicity Office]


Prof. Liu Hongwei, head of Academic Affairs Department and Prof. Zeng Siyu, head of International Cooperation and Student Affairs Office, also delivered speeches during the ceremony.


Prof. Xiang Shaohua introduces the preparatory work of the program. [Photo/Party Affairs Committee Publicity Office]


Prof. Xiang Shaohua, dean of College of Big Data and Internet, introduced the joint working group established by SZTU and FHWS, the training scheme, requirements of obtaining degrees and curriculum design for Röntgen AI class. He noted that these 30 students stood out after three rounds of selection and may still face more challenges in the future. The launching ceremony marked the commencement of a new journey to pursue their dreams.


Prof. Fu Xianghua gives more details of Röntgen AI class. [Photo/Party Affairs Committee Publicity Office]


Prof. Fu Xianghua, head of Computer Science Major at College of Big Data and Internet, introduced the selection committee for Röntgen AI class, the selection process, the curriculum of the program, etc.


Members of the selection committee (from left to right): Lue Yu, Zhao Heng, Wang Wenting, Xiang Shaohua, Fu Xianghua, Li Jingyu, Gu Ye [Photo/Party Affairs Committee Publicity Office]


Students communicate with their instructors. [Photo/Party Affairs Committee Publicity Office]


Jointly established by SZTU and FHWS, Röntgen AI class is a training base aiming at cultivating internationalized high-end technical talents in application research, technology development, and operation and maintenance of AI to meet the urgent demand in the industry.

 

FHWS and SZTU sign a MoU for Röntgen AI class. [Photo/Party Affairs Committee Publicity Office]


On November 22, 2018, Prof. Robert Grebner, president of FHWS and his counterpart Prof. Ruan Shuangchen signed a memorandum of understanding (MoU) for co-organizing Röntgen AI class.


Prof. Ruan and Prof. Grebner sign an agreement to push forward the future development of Röntgen AI class. [Photo/International Cooperation & Student Affairs Office]


During his visit to Würzburg, Germany on June 17, 2019, Prof. Ruan Shuangchen signed an agreement with Prof. Robert Grebner, under which the two universities will launch the Röntgen AI class.


Adopting the “3+2” talents training mode, Röntgen AI class requires students to take extra special courses except for the regular undergraduate courses at College of Big Data and Internet at SZTU in the first three years. Students passing the assessment can continue the 2-year master’s courses in FHWS. Those who have enough credits and pass the thesis defense can be granted a Bachelor of Science Degree and a certificate of graduation in Internet of Things Engineering from SZTU in the 4th year. A master’s degree in FHWS can be obtained in the 5th year subject to its training requirements.




Drafted by Daisy(姚琦)/ International Cooperation & Student Affairs Office

Edited by International Cooperation & Student Affairs Office

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