Laureates 2023
Announcement of 2023 Future Science Prize Eight Scientists Honoured with 2023 Future Science Prize
The Future Science Prize committee announces the laureates of 2023 on August 16th. Jijie Chai and Jian-Min Zhou receives the Future Science Prize in life sciences for the discovery of resistosomes and elucidation of their molecular structures and functions in plant immune responses against pathogens. Zhongxian Zhao and Xianhui Chen receives the Future Science Prize in physical sciences for their seminal breakthroughs in the discovery of high-temperature superconducting materials and systematic advancements in elevating the transition temperature. Kaiming He, Jian Sun (late), Shaoqing Ren and Xiangyu Zhang receives the Future Science Prize in mathematics and computer science, for fundamental contributions to artificial intelligence by introducing deep residual learning.
Jijie Chai
Jian-Min Zhou
2023 Future Science Prize
Life Science Prize Laureates
Citation:
For the discovery of resistosomes and elucidation of their molecular structures and functions in plant immune responses against pathogens.
Jijie Chai was born in Liaoning, China, in 1966. He received his Ph.D. from the Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College in 1997.
Jian-Min Zhou was born in Sichuan, China, in 1964. He received his Ph.D. from Purdue University in 1994.
Disease outbreaks in plants have had major impacts on civilizations. Currently, up to 40% of global food production is lost due to plant pests and microbial pathogen infection. The discovery of plant resistance loci in 1940s suggested that plants have innate immune mechanisms. This hypothesis was proven molecularly through the cloning of the first plant resistance genes in 1994. These resistance genes encode nucleotide-binding domain leucine-rich repeat-containing immune receptors, constituting a major plant immune mechanism against a wide range of pathogens and some insects. However, the molecular functions of these immune receptors remained a mystery before Chai and Zhou’s work.
Through their collaborative work in the past 19 years, Dr. Jijie Chai and Dr. Jian-Min Zhou discovered that plant immune receptors activate immune responses through formation of resistosomes by identifying the essential components of the first resistosome (ZAR1 resistosome) and revealing its structure and molecular function. Their work shows how the multi-component resistosome assembles after recognition of the pathogen effector by the immune receptor, ZAR1, and functions as a plasma membrane calcium-channel to trigger programmed cell death at the infection site to protect plants from infection. Understanding of resistosome functions will lead to better methods for controlling plant disease and therefore have enormous importance for global food security. Therefore, Dr. Jijie Chai and Dr. Jian-Min Zhou are awarded with the Future Science Prize in Life Sciences for their seminal contributions to the understanding of innate immune mechanisms in plants.
Zhongxian Zhao
Xianhui Chen
2023 Future Science Prize
Physical Science Prize Laureates
Citation:
For their seminal breakthroughs in the discovery of high-temperature superconducting materials and systematic advancements in elevating the transition temperature.
Zhongxian Zhao was born in Liaoning, China in 1941, graduated from the Department of Technical Physics of the University of Science and Technology of China in 1964.
Xianhui Chen was born in Hunan, China in 1963, and received his Ph.D. in the University of Science and Technology of China in 1992.
Superconductivity, the remarkable phenomenon of conducting electric current with zero resistance and complete diamagnetism in quantum materials, offers immense potential for applications in energy transmission, transportation, computation and communication. Traditionally, superconductivity has been observed at extremely low temperatures (<-230 °C) in most materials. The discovery of high transition temperature (Tc) superconducting materials has significantly propelled these applications, unveiling fundamental and captivating physical mechanisms.
As leaders of this international pursuit, Zhongxian Zhao and Xianhui Chen have played pivotal roles. Two primary families of high Tc materials have emerged: Cuprate superconductors and Iron-based superconductors. In the Cuprate family of high Tc materials, Zhao Zhongxian led a team that independently discovered the first superconducting material above the liquid nitrogen temperature. In the Iron-based family of high Tc materials, Xianhui Chen's group was the first to raise the transition temperature above the McMillan limit, confirming the unconventional nature of these materials. Additionally, Zhongxian Zhao's group holds the distinction of achieving the highest transition temperature in bulk samples. Notably, both Zhao and Chen conducted systematic studies to unravel the underlying physical mechanisms of high Tc materials, positioning themselves at the forefront of superconductor research for several decades.
Kaiming He
Jian Sun
Shaoqing Ren
Xiangyu Zhang
2023 Future Science Prize
Mathematics and Computer Science Prize Laureates
Citation:
For fundamental contributions to artificial intelligence by introducing deep residual learning.
Kaiming He
BS (2007) Tsinghua University, PhD (2011) Chinese University of Hong Kong.
Jian Sun
BS (1997) and PhD (2003), Xi'an Jiaotong University.
Shaoqing Ren
BS (2011) University of Science and Technology of China, PhD (2016) University of Science and Technology of China and Microsoft Research Asia.
Xiangyu Zhang
BS (2012) Xi'an Jiaotong University, and PhD (2017) Xi'an Jiaotong University and Microsoft Research Asia.
Deep neural networks have driven the revolution of artificial intelligence and its rapid development. Particularly, neural networks with increasing depths have led to groundbreaking progress in a wide range of artificial intelligence applications. The awardees as a team introduced deep residual learning as a framework for building deep neural networks. Deep residual learning has allowed neural networks to utilize unprecedented depths and unlock capabilities that previously deemed unachievable. Deep residual learning has been extensively adopted across many applications, paving the way for numerous breakthroughs such as AlphaGo, AlphaFold, and ChatGPT.
The research was undertaken by the awardees at Microsoft Research Asia in Beijing between 2012 and 2016.