personal profile

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孙 贺全
孙 贺全
教授 Professor
hequan.sun@xjtu.edu.cn

Positions

2023.03 - Now  

School of Automation Science and Engineering, Xi'an Jiaotong University

Professor  
2020.01 - 2023.03

Institute of Genetics, University of Munich, Germany

Bioinformatician
2013.01 - 2023.03

Max Plants Breeding Institute, Germany

Bioinformatician
2011.01  - 2011.05  

School of Computer Engineering, Nanyang Technological University, Singapore

Teaching assistant (part-time)

Education

2008.08 - 2012.12

Nanyang Technological University, Singapore

Computer Engineering Ph.D 
2005.09 - 2008.06

Xi'an Jiaotong University (XJTU)

Control Science and Engineering Master 
2001.08 - 2005.07

Xidian University

Automation Bachelor

Contact

E-mail：hequan.sun@xjtu.edu.cn

Address：No. 28 Xianning West Road, Xi'an, Shaanxi, China, 710049 

Basic Information

Prof. Dr. Hequan Sun, Ph.D supervisor

XJTU Young Talent (Tier-A)

National Excellent Young Scholar

Member of Chinese Association of Automation; Member of IEEE

Institute of Systems Engineering

School of Automation Science and Engineering

Faculty of Electronic and Information Engineering

Xi'an Jiaotong University (Xi’an 710049, P.R. China)

 

His research is focused on bioinformatics, crop genomics and AI-assisted crop breeding. He has published more than 30 research papers in high impact journals like Nature Genetics, Nature Communications, and Genome Biology etc. His research has been reported by the mainstream scientific and technological news media and research organizations around the world. He serves as a reviewer for Nature Group journals, Genome Biology, Plant Biotechnology Journal, and other international journals. He also serves as a guest editor for several scientific journals such as Frontiers in Plant Science.

Scientific Research

I. Rearch Field: bioinformatics, genomics, AI-assisted crop breeding, smart agriculture, automation in agriculture

The group is committed to facing the frontiers in agricultural science and technology, facing the concerns in food security, by making full use of interdisciplinary knowledge, and based on the theory of parallel systems, by integrating biological, big data, artificial intelligence, automation and other technologies, and taking the reconstruction of crop genomes as the starting point to carry out research, explore the new methods of digital crop molecular breeding, dig out and answer the major scientific questions of digital crop germplasm innovation, expand the interdisplinary research field of modern breeding assisted by parallel intelligence and genomic selection, develop new intelligent digital breeding technologies, build new platforms for automated precision breeding, and contribute to the promotion of green, ecological, and sustainable development of agriculture and to the solution of food security problems brought about by factors such as significant population growth and global climate change.

 

II.Research Direction

0. Big data modelling and analysis algorithm

1. Computational method development in genome research

2. Crop phenotyping using artificial intelligence and IoTs
3. Genomic prediction using foundation models