In order to thoroughly implement Xi’s Thought on Socialism with Chinese Characteristics for a New Era and implement the spirit of the Talent Work Conference of Chinese Conmunist Party Central Committe, according to the requirements of the Notice of the Organization Department of the CPC Central Committee, the Ministry of Human Resources and Social Security, the China Association for Science and Technology, and the the Communist Youth League of Chinese Conmunist Party Central Committe on The Nomination of Candidates for the 17th China Youth Science and Technology Award (No. 59 [2021] of the Association for Science and Technology), On December 28, 2021, the Association launched the nomination of candidates for the 17th China Youth Science and Technology Award. Two candidates were selected by the Association. The shortlist is hereby announced from February 7 to 11, 2022. 

If there is any objection, please give feedback to the Office of the Secretariat of the Association in writing. the situation reflected must be objective and true, the materials reflecting the situation in the name of the unit should be stamped with the official seal of the unit, and the materials reflecting the situation in the name of the individual should be signed with a real name and provide effective contact information.

Contact: Zou Yaru 

Tel: 010-82686683

E-mail: msc@caai.cn

Address: Room 305, Block B, Xueyan Building, No. 33 Shuangqing Road, Haidian District, Beijing

Candidate Personal Information

Nominee Nie Liqiang

Gender Male

Date of Birth  1985. 10. 12

Ethnic Han 

 Academic Qualifications Doctoral Students 

 Degrees Boshang 

 Professional and Technical Positions Professors 

 Political Outlook Party Member of CPC

 Professional Expertise Computer Science and Technology 

 Work Units and Positions Professor of Shandong University, Dean of Shandong Artificial Intelligence Research Institute 

The nominee's main scientific and technological achievements and contributions

The applicant was selected as an overseas specially appointed young expert of Organization Department of the Central Committee of the CPC and a Jiang Scholar of the Ministry of Education. He has presided over the key research and development projects of the Fund Committee, the key research and development projects of the Ministry of Science and Technology, the Jieqing of Shandong Province, and the two tens of million-level horizontal projects with a total of more than 50 million yuan. He has published more than 100 papers in international CCF A conferences or ACM/IEEE journals, 4 monographs, and 13,000 citations by Google (Annexes 5-1). He is a member of the editorial boards of ACM ToMM, IEEE TMM, IEEE TKDE, IEEE TCSVT, etc., the chairman of the ACM MM 20182021 field, and the chairman of the ICIMCS 2017 and ChinaMM 2020 program committee. Winner of the CCFA Conference SIGIR 2019 and ACMMM 2019 Best Paper Nomination Award, SIGIR 2021 Best Student Paper Award, ACM China Rising Star Award, SIGMM Rising Star, TR 35 China, Ali Damo Academy Green Orange Award. The applicant is committed to the research on key technologies and an application of transmission line safety monitoring based on multimodal perception, and has achieved three original results, which solve the problems of data perception, image semantic understanding, and hardware equipment support in the transmission line industry. Won the 2021 Provincial Science and Technology Progress Award (ranked first)

Defects in the transmission line body and hidden dangers of external damage are the main causes of line tripping. The inherent characteristics of transmission lines bring challenges to intelligent identification and early warning, including: 1) the occasional occurrence of defects and hidden dangers makes it difficult to collect data, the smog environment or surface pollution causes 30% of the problems to be perceived by visible light equipment, ordinary people cannot label power data, and there are industry data perception problems such as incomplete data, unclear and difficult labeling. 2) Factors such as the difficulty of climbing the pole and the danger of electric shock of the high voltage arc lead to the semantic understanding problems of the image in the industry such as the image target collected at a long distance is not significant, the ancient proportion is small, and it is difficult to distinguish. 3) The environment along the line is complex, the single-eye fixed camera is difficult to capture the dead angle, and the cloud computing pressure is large, so it is necessary to solve the hardware equipment support problem of dynamic perception and side cloud collaborative analysis. 

Original Research and Develpment Achievement one: Constructed a data-driven multimodal fusion and enhancement model, integrated multimodal images, expanded sample data, enhanced model stickiness, and solved the problems of industry data perception such as incomplete transmission line data, unclear and difficult labeling. He won the 2018 “Teddy Cup” Data Mining Challenge Grand Prize, the SIGIR 2021 Best Student Paper Award, and the Alibaba Green Orange Award.

Original Research and Develpment Achievement two: Established a knowledge-guided small target and multi-target recognition technology, and overcome the problem of industry image language understanding of small target and multi-target recognition of transmission lines. Won the first place in the 2019 State Grid Organization of “Channel Visualization Image Artificial Intelligence Recognition Technology Detection Work”, the first person to complete the selection of 35 people under 35 years old in 2020, SIGIR 2019 Best Paper Nomination Award, Overseas Youth Distinguished Expert of Organization Department of the Central Committee of the CPC in 2016.

Original Research and Development achievement three: the development of demand-driven multi-eye sensing and edge computing equipment. A new edge computing system of dynamic and static collaboration is proposed, and a dynamic and static collaborative multi-eye perception device and a cloud-side collaborative mutual learning computing device are developed, which solves the problem of all-round image perception and cloud-side collaborative computing of transmission line body defects and hidden dangers of external damage. The first finisher won the SIGMM Rising Star, ACM China Rising Star Award, ACM MM 2019 Best Paper Nomination Award, AI2000 World Most Influential Scholar Award, and was selected for the 2021 Ministry of Education Chang Jiang Scholar Program.

Nominee Name Zhou Jun

Gender Male

Date of Birth 1986. 4

Ethnic Han

Education Graduate Students

Degrees Master's Degrees Professional and Technical Positions Senior Network Engineers

Political Outlook Party Member of CPC

Professional Expertise Artificial Intelligence

Work Units and Positions Mosquito Technology Collective Co., Ltd., General Manager of Financial Machine Intelligence Department

The nominee's main scientific and technological achievements and contributions

The candidates have long been engaged in theoretical research, technology research and development and application in the field of artificial intelligence, and have made positive contributions to technological innovation and large-scale applications in the fields of graph machine learning, privacy computing, and AI security risk control etc.. Leading the team to build a financial machine intelligent platform from 0 to 1, it has achieved large-scale application in Ant Group’s digital finance, digital government affairs and other businesses, serving 1 billion users, more than 80 million merchants and more than 600 financial institutions around the world. He has published more than 100 papers in TOP AI conferences and journals such as ICML and NeuriPs (1200 times cited), obtained more than 200 authorized patents (including 20 international patents), and participated in the formulation of IEEE international standards for machine learning for privacy protection. He has won many scientific and technological awards such as Wu Wenjun Artificial Intelligence Science and Technology Progress Award (first completer), science and technology progress first prize in Zhejiang provice (the fifth completer), CCF Science and Technology Award Science and Technology Progress Excellence Award (the first completer) and so on.

The candidate’s main scientific and technological innovation includes three aspects: first. it is the leading research and development of the financial intelligent graph machine learning system, which supports the trillions of nodes and trillions of edges, breaks through the problem of intelligent modeling of massive graph structure data in the financial scenario, and has significant innovations in deep dynamic graph learning, logical reasoning and full-link graph machine learning; second, it leads the research and development of the financial intelligent privacy computing platform, which solves the technical problem of ensuring data security and privacy protection and realizing collaborative computing in the distributed storage of data assets and the environment of different subjects. It has significant innovations in hybrid dense state computing protocols and security machine learning algorithms; the third is to participate in the research and development and application of financial intelligent risk control systems, build and complete the fifth generation of Alipay risk control engine, put forward innovative methods such as rule learning of human-machine collaboration, optimization-driven intelligent decision-making, and explanation learning of restrictions on disturbances, etc., supporting Alipay's transaction loss rate to be reduced from 1 in 100,000 to less than 0.5 in 10 million, and financial risk control technology as a whole has reached the international advanced level.

At the same time, candidates actively participate in industry activities and organizations, and promote in-depth cooperation between their companies and universities at home and abroad, and help technological innovation, achievement transformation and talent training through industry-university-research cooperation.