Head: Dr Yuxuan Zhao (Yuxuan.Zhao02@xjtlu.edu.cn)
This subject area provides the mathematical and algorithmic foundation for modern data-driven technologies, bridging theory with large-scale implementation. Students develop competencies in data structures, algorithm analysis, statistical modelling, optimisation, and advanced data mining.
Key modules include Data Structures and Algorithms, Mathematics for AI and Data Science, Optimisation, and Big Data Analytics.
Head: Dr Jingxin Liu (Jingxin.Liu@xjtlu.edu.cn)
This subject area focuses on the core algorithmic principles and theoretical frameworks that power contemporary AI systems. Students develop a rigorous understanding of machine learning, deep learning, reinforcement learning, and generative models.
Key modules include Machine Learning, Deep Learning, Reinforcement Learning, and Large Model Techniques.
Head: Dr Qing Liu (Qing.Liu@xjtlu.edu.cn)
This subject area explores the theories, systems and technologies that support modern communication networks and signal processing. Students study analogue and digital communications, signal processing, photonics, and wireless systems.
Key modules include Digital Signal Processing, Information Theory and Data Communications, Wireless Systems, and Coding and Cryptography.
Head: Dr Yue Li (Yue.Li@xjtlu.edu.cn)
This subject area provides students with a comprehensive understanding of the hardware, operating systems and networking infrastructure that underpin computing environments. Students learn to design and manage systems across computer architecture, parallel computing, cybersecurity, and cloud technologies.
Key modules include Computer Systems, Operating System Concepts, Information Security, and Cloud Computing.
Head: Dr Fei Xue (Fei.Xue@xjtlu.edu.cn)
This subject area covers the principles and advanced applications of electrical and electronic engineering, from microelectronics to large-scale power systems. Students develop skills in circuit design, power electronics and sustainable energy technologies.
Key modules include Electrical Circuits, Digital Electronics, Power Generation Technologies, and Sustainable Energy and Environment.
Head: Dr Qi Chen (Qi.Chen02@xjtlu.edu.cn)
This subject area examines the design, deployment and application of intelligent systems across a wide range of real-world domains. Students explore how AI techniques are used to build autonomous vehicles, healthcare diagnostics, immersive gaming experiences, and intelligent robots.
Key modules include AI in Autonomous Vehicles, Intelligent Robotics, Natural Language Processing, and Multi-Agent Systems.
Head: Dr Qinyao Liu (Qinyao.Liu@xjtlu.edu.cn)
This subject area integrates mechanical engineering, electronics, control theory, and computing to design and build intelligent, automated physical systems. Students engage with the full lifecycle of robotic and mechatronic devices, from dynamic modelling to industrial automation.
Key modules include Introduction to Mechatronics, Mechanical Engineering Design, Industrial Automation and Robot Control, and Robotic Systems.
Head: Dr Zhenzhen Jiang (Zhenzhen.Jiang02@xjtlu.edu.cn)
This subject area equips students with the essential professional, ethical and management competencies needed for careers in technology and related fields. Students engage with research methodologies, project management, entrepreneurship, and responsible AI practices.
Key modules include Entrepreneurial Skills for Advanced Technologies; Research Methods; Technological Project Management; and Ethics, Privacy, and AI in Society.
Head: Dr Paul Craig (P.Craig@xjtlu.edu.cn)
This subject area concentrates on the systematic development of robust and scalable software systems throughout the software lifecycle. Students develop skills in programming paradigms, database design, software architecture, and current industry practices.
Key modules include Software Engineering, Object‑Oriented Programming, Database Development and Design, and Computer Graphics.
Education Overview
The faculty and staff at the research- and practice-led Academy of Artificial Intelligence and Advanced Technology (AIAT) are committed to providing students with a challenging and stimulating learning environment. Upon graduation, students will have developed strong academic knowledge in artificial intelligence (AI), technology, and related fields, as well as transferable soft skills in communication, teamwork and project management.
The AIAT operates under the XJTLU 3.0 Education Model, which seeks to strengthen the University’s engagement with society by breaking down traditional barriers between academia and industry and building a systematic, innovative and integrated ecosystem with various industries.
At the AIAT, students have numerous opportunities to pursue real-world interdisciplinary projects in collaboration with industry and societal partners.
The AIAT hosts nine undergraduate programmes and 10 master’s programmes across a wide range of engineering and technology fields, including electrical engineering, computer science, AI, telecommunications, and mechatronics and robotics.
To provide a coherent curriculum and enhance the student learning experience, AIAT modules are organised into nine subject areas.