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Neuron-Symbolic Technology of Dynamic Transportation Perception


   School of Advanced Technology

  , , , Prof P Wong  Applications accepted all year round  Funded PhD Project (Students Worldwide)

About the Project

Cameras can perceive the appearance, color and shape information of objects in the environment, and are widely used in target classification, target detection, target segmentation, target tracking and other fields. With the development of deep learning, although significant progress has been made in general target detection, the detection of vehicles and pedestrians in autonomous driving is different from general target detection, so there are still many challenges in the detection of vehicles and pedestrians in the driving environment. Based on the video or image captured by road conditions, the scale distribution range of vehicles and pedestrians is very wide, and small and medium-sized targets account for a large proportion. The existing target detection algorithms have low accuracy in detecting small and medium-sized vehicles and pedestrian targets. It is necessary to study the multi-scale vehicle and pedestrian detection under real road conditions, and study the detection algorithm that is suitable for multi-scale targets and can significantly improve the detection effect of small and medium-scale targets.

For more information about doctoral scholarship and PhD programme at Xi’an Jiaotong-Liverpool University (XJTLU): Please visit

http://www.xjtlu.edu.cn/en/study-with-us/admissions/entry-requirements

http://www.xjtlu.edu.cn/en/admissions/phd/feesscholarships.html

Requirements:

The candidate should have a first class or upper second class honours degree, or a master’s degree (or equivalent qualification) in Mathematics, physics, computer, automation and other related professional background

Strong knowledge background in machine learning

Evidence of good spoken and written English is essential. The candidate should have an IELTS score of 6.5 or above, if the first language is not English. This position is open to all qualified candidates irrespective of nationality.

Degree: 

The student will be awarded a PhD degree from the University of Liverpool (UK) upon successful completion of the program.

Supervisor Profile:

Principal Supervisor:

Steven Guan (Sheng-Uei Guan) received his BSc. from Tsinghua University and M.Sc. & Ph.D. from the University of North Carolina at Chapel Hill.

He is currently an Honorary Professor at University of Liverpool & also a Professor at Xi'an Jiaotong-Liverpool University (XJTLU). He served the head of department position at XJTLU for 4.5 years, creating the department from scratch and now in shape. Before joining XJTLU, he was a tenured professor and chair in intelligent systems at Brunel University, UK.

Prof. Guan has worked in a prestigious organization for several years, serving as a design engineer, project leader, and department manager. After leaving the industry, he joined the academia for three and half years. He served as deputy director for the Computing Center and the chairman for the Department of Information & Communication Technology. Later he joined the Electrical & Computer Engineering Department at National University of Singapore as an associate professor for 8 years.

Prof. Guan’s research interests include: machine learning, computational intelligence, big data analytics, mobile commerce, modeling, networking, personalization, security, coding theory, and pseudorandom number generation. He has published extensively in these areas, with 140+ journal papers and 200+ book chapters or conference papers. He has chaired, delivered keynote speech for 100+ international conferences and served in 190 international conference committees and 20+ editorial boards.

JITRI co-supervisor:

Dr. Yutao Yue received his Bachelor's degree of applied physics from University of Science and Technology of China, master and PhD degrees of computational physics from Purdue University of USA. He then served as team leader of Guangdong “Zhujiang Plan” 3rd Introduced Innovation Scientific Research Team, senior scientist and Chief Human Resources Officer of Shenzhen Kuang-Chi Group, etc.

His research interest include computational modeling and artificial intelligence, radar vision fusion, electromagnetic fields, etc. He has been engaged in frontier technology research and development and industrialization for 20 years. He has co-invented 354 granted Chinese patents, 18 USA patents, and 7 EU patents. He has led 6 major research projects with a total funding of nearly 150 million RMB. He has advised 13 postdoc research fellows, published over 20 papers, and received multiple awards including Wu Wenjun Artificial Intelligence Science and Technology Award. He has been received by General Secretary Xi Jinping due to outstanding achievements.

How to Apply:

Interested applicants are advised to email  and () the following documents for initial review and assessment (please put the project title in the subject line).

  • CV
  • Two reference letters with company/university letterhead
  • Personal statement outlining your interest in the position
  • Proof of English language proficiency (an IELTS score of 6.5 or above)
  • Verified school transcripts in both Chinese and English (for international students, only the English version is required)
  • Verified certificates of education qualifications in both Chinese and English (for international students, only the English version is required) 
  • PDF copy of Master Degree dissertation (or an equivalent writing sample) and examiners reports available

Funding Notes

This PhD project is a collaborative research project between XJTLU (View Website) at Suzhou and JITRI (Jiangsu Industrial Technology Research Institute) Institute of Deep Perception Technology (IDPT) at Wuxi. The student will be registered as an XJLTU PhD student but is expected to carry out the major part of his or her research at the Institute at Wuxi.
The PhD studentship is available for three years subject to satisfactory progress by the student. The award covers tuition fees for three years (currently equivalent to RMB 80,000 per annum).

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