CUHK PhD Student Wins Best Application Award at Global College AI Training Camp
Chen Yuting, a PhD student from the Institute of Space and Earth Information Science (ISEIS) at The Chinese University of Hong Kong (CUHK), and her team won the Best Application Award at the 2018 Global College Artificial Intelligence Training Camp (the ‘DeeCamp’) held at Peking University recently.
To nurture young talent from top universities in artificial intelligence (AI) to meet the growing demand for AI experts, the DeeCamp was held under the ‘International AI Training Programme for Chinese Universities’. The Programme is a collaboration between the Ministry of Education, Sinovation Ventures AI Institute and Peking University. It attracted more than 7,000 students from 600 colleges and universities worldwide to compete for 300 training places. Through five weeks of careful guidance from Turing Award winner John Hopcroft, Innovation Workshop CEO Kai-fu Lee, and deep-learning expert Andrew Ng, the students quickly grew into today’s most sought-after AI engineers.
The students were divided into 28 teams. Each was requested to submit a AI project at the end of the DeeCamp to demonstrate what they had learned. After a multi-level evaluation, Chen Yuting and her team became one of the top 8 winners and won the ‘DeeCamp 2018 Best Application Award’. The other members of Chen Yuting’s team came from leading institutions including Tsinghua University, Peking University, Wuhan University, and the Chinese Academy of Sciences. Their project built and trained a virtual driverless car which has the same technical architecture as a real car, exploring the huge potential of unmanned driving in future logistics, transportation and other fields.
The jury believed that the accurate understanding of the whole robotic technology stack and the efficient integration of the sub-module system enabled the team to achieve high-precision mapping and positioning, complex environmental obstacle perception, smooth tracking control of the vehicle trajectory, and the overall path planning in a short time, reflecting the best practice experience of AI talents in the engineering field.