Postgraduate Program for International Students in Artificial Intelligence

I.Discipline Introduction

Artificial Intelligence (AI) is a cutting-edge interdisciplinary field integrating computer science, mathematics, cognitive science, robotics, and data science. This program emphasizes both theoretical foundations and practical applications, focusing on areas such as machine learning, deep learning, computer vision, intelligent systems and intelligent information processing. The curriculum is designed to equip students with the skills to develop intelligent systems that address real-world challenges in healthcare, environmental sustainability, autonomous systems, and beyond.

The school of computer science and technology currently has 123 faculty and staff members, including 19 professors, 37 associate professors, and 63 faculty members with doctoral degrees.  The college houses multiple provincial research platforms, including the Henan Key Laboratory of Food Safety Data Intelligence, the Network Engineering & Data Intelligence Pilot Base, and the Emergency Platform Information Technology Engineering Laboratory, alongside advanced teaching facilities like the Computer Science Elite Student Training Base and IoT Experimental Teaching Demonstration Center. Supported by stable on- and off-campus internship bases, it delivers exceptional practical training environments for student

II.Program Objectives

[1] Ethical and Responsible AI Practitioners: Cultivate professionals committed to ethical AI development, emphasizing fairness, transparency, and societal impact.

[2] Technical Mastery: Master core AI techniques: supervised/unsupervised learning, reinforcement learning, neural network architectures (CNNs, RNNs, Transformers), and optimization algorithms (SGD, Adam). Gain proficiency in programming (Python, TensorFlow, PyTorch) and tools (Jupyter, Docker, Git).

[3] Research and Innovation: Develop independent research capabilities to solve cutting-edge problems (e.g., explainable AI, federated learning, AI safety).

[4] Global Competence: Strengthen English proficiency for academic writing, presentations, and collaboration. Participate in international conferences and workshops.

III. Research Directions

[1]Intelligent Perception and Systems

Intelligent computing, edge computing, wearable device sensing, embedded systems and applications, and intelligent decision-making systems. This direction conducts research on new theories, methods, and applications related to intelligent perception, integrating technologies such as pattern recognition and machine learning to construct swarm intelligence metaheuristic algorithms. Applied research is carried out in areas such as industrial intelligence, smart cities, and smart healthcare, including model- and data-driven local continuous optimization algorithms and reinforcement learning-based evolutionary algorithms.

[2] Computer Vision and Image Processing

This direction encompasses areas such as artificial intelligence-driven video processing, remote sensing image processing, visual media computing, visual perception, and autonomous driving technologies. Key research efforts focus on conducting theoretical and methodological studies for fast multi-view video compression, 3D image quality assessment, and next-generation 3D video coding; investigating deep learning-based hyperspectral image super-resolution reconstruction, fine-grained classification, and target detection; and developing vision perception-based safety warning systems and autonomous driving technology models to address challenges in intelligent transportation and environmental interaction.

[3] Intelligent Information Processing

This direction primarily focuses on research into new theories, methodologies, and applied technologies related to computational intelligence. By integrating artificial intelligence techniques such as pattern recognition, machine learning, and combinatorial scheduling, it aims to construct intelligent metaheuristic algorithms and develop smart systems for big data processing, virtual reality/augmented reality (VR/AR), healthcare, and magnetic nanotechnology. The work involves conducting prospective pre-research on complex dynamic optimization problems in applications aligned with national informatization planning initiatives and key engineering projects, addressing challenges in critical areas of intelligent systems.

[4] Intelligent Networks and Security

This direction conducts research on key technologies for intelligent network security and trustworthiness based on endogenous security. It investigates intelligent terminal group key agreement theory grounded in multidimensional virtual permutation theory, studies rapid key agreement algorithms for industrial internet, explores fundamental theories and applications of post-quantum cryptography, establishes lightweight post-quantum cryptographic algorithms, and performs applied research in areas such as autonomous access control, bidirectional identity authentication, digital signatures, trusted computing measurement, and data communication security.

IV.Program Structure

Duration

• Full-time: 3 years

• Credit Requirements

V. Detailed Curriculum

Core Courses (20 Credits)

Elective Courses (10 Credits)

Compulsory Modules (5 Credits)

[1] Thesis Proposal (1 credit): Submit a detailed research plan with literature review, methodology, and timeline.

[2] Mid-term Review (1 credit): Present progress to a faculty committee.

[3] Academic Seminars (1 credits): Attend 15 seminars and present once.

[4] Internship/Practical Training (2 credits): 3-month internship in industry or research lab.

VI. Thesis Requirements

[1] Topic Selection: Must address an unresolved AI challenge (e.g., adversarial robustness, AI interpretability). Approved by a supervisory committee of 3 faculty members.

[2] Research Standards:Innovation, demonstrate novel contributions (e.g., new algorithms, datasets, or applications).Technical depth, rigorous experimentation with SOTA baselines (e.g., ablation studies, cross-dataset validation).Ethics, address potential societal impacts and biases.

[3] Dissertation Format: follow ACM/IEEE templates, minimum 50 pages (excluding references).

[4] Defense: public presentation followed by Q&A with a panel of 5 experts. At least one peer-reviewed publication required for graduation.

VII. Support for International Students

Language Support: Free Mandarin courses (beginner to advanced). Writing center for thesis editing and proofreading.

Cultural Integration: Workshops on Chinese business etiquette and cross-cultural communication. Guided tours to tech hubs (e.g., Shenzhen, Beijing).

Career Services: Job fairs with multinational companies. Alumni mentorship program.

VIII.Graduation and Degree Award

[1] Complete all credits and compulsory modules.

[2] Pass thesis defense and publish at least one paper.

[3] Degree: Master of Science in Artificial Intelligence.