The application deadline for 2026 full-time MPhil-PhD programme in Artificial Intelligence is June 30, 2026. We accept applications on a rolling basis, so we encourage you to apply early—admission is closed once all spots are filled.

Application conditions:

Applicants are generally expected to have an academic background in Computer Science and Engineering or a related field. However, we also welcome applications from outstanding students from other disciplines.

The applicants for a doctoral degree must meet the following requirements: 

1. Graduated from a recognized university with a master's degree; or 

2. Graduated from a recognized university with a bachelor's degree with an honors grade of not less than second class; or 

3. Graduated from a recognized university with a bachelor's degree. Grades not less than "B" and a GPA of not less than 3.2/4.0; or 

4. Completed studies at a higher education institution and obtained a professional qualification or similar qualification equivalent to an honors degree.  

The applicants for a master's degree must meet the following requirements: 

1. Graduated from a recognized university with a bachelor's degree with an honors grade of not less than second class; or 

2. Graduated from a recognized university with a bachelor's degree with a grade of not less than "B"; or 

3. Completed studies at a higher education institution and obtained a professional qualification or similar qualification equivalent to an honors degree. 

All applicants should fulfill the English Language Proficiency Requirement prescribed below before the submission: 

1. Obtained a degree from a university in Hong Kong^a or taken a degree programme of which the medium of instruction was English; or  

2. Achieved scores in the following English Language tests^b as indicated:

· TOEFL: 550 (Paper-based)/79 (Internet-based/Home Edition);

· IELTS (Academic): 6.5(Test Centre based/Online); 

· GMAT: Band 21 (Verbal)^c; 

· GMAT Focus Edition: Band 78 (Verbal); or  

3. Obtained a pass grade in English in one of the following examinations: 

· Hong Kong Advanced Level Examination (AS Level); 

· Hong Kong Higher Level Examination; 

· CUHK Matriculation Examination; 

· General Certificate of Education Examination (GCE) Advanced Level (A-Level) /Advanced Subsidiary Level (AS-Level). 

4. Achieved Level 4 or above in the English Language subject of the Hong Kong Diploma of Secondary Education (HKDSE) Examination.  

Notes: 

a. It is assumed that all degree courses in Hong Kong are taught in English. Please note that the Graduate School of CUHK-Shenzhen may still require applicants to provide other relevant documents to prove that their English proficiency meets the requirements. 

b. TOEFL and IELTS scores are valid for two years from the date of the test. GMAT scores are valid for 5 years from the date of the test. 

c. The minimum admission requirement of GMAT: Band 21 (Verbal) will remain until the end of its score validity period. 

Application Procedures: 

1. Please choose your preferred supervisors and/or research groups that match your interests.  

Before applying, please review the “Supervising Model” page to learn about the list of available supervisors and research groups. You may either contact your preferred supervisors and/or research groups in advance or apply directly; both options are acceptable.

When submitting the online application, you may list up to three preferred supervisors and up to three research groups. If you have previously contacted a supervisor or group, please indicate this in parentheses.

Example format for the "Intended Supervisor" field:
"1. Professor Name A; 2. Professor Name B (Contacted); 3. Professor Name C. Intended Research Group: 1. Research Group Name A; 2. Research Group Name B (Contacted); 3. Research Group Name C."

2. Online application: please go to the following website: https://pgapply.cuhk.edu.cn 

Required Application Materials (PDF format):  

a. Scanned copies of academic/professional qualification certificates (such as degree certificates and graduation certificates, the MOE Online Verification Reports for academic credentials and degrees, or the CSCSE Verification Certificate for foreign degrees, or proof of enrollment);  

b. Scanned copies of official transcripts (including a complete record of courses taken and test scores), evaluation criteria for all university studies, and proof of academic ranking. The University reserves the right to request applicants to submit original transcripts when necessary; 

c. Two confidential letters of recommendation (Once an application is submitted, the system will automatically send an email to the designated recommenders requesting a letter of recommendation.);  

d. English proficiency test scores: scanned copies of original valid official TOEFL or IELTS score reports, or meet any language requirements in the "Application Requirements" (Please note that TOEFL and IELTS scores are valid for two years from the date of the test, and some testing agencies will no longer accept transcript applications after a certain validity period.);  

e. Scanned copies of ID cards or other identity documents. Please note that applicants from mainland China should use their ID cards to apply. Otherwise, they will not be able to register with The Ministry of Education;  

f. Resume and personal statement (in English);  

g. Other materials (if any), such as essays, scholarship certificates, publications, etc.;  

h. The University may require applicants to submit additional information or supporting documents when necessary.  

3. Pay the registration fee.

The registration fee is RMB 600 and is non-refundable. Your application will only be considered valid once you have submitted all required materials and paid the fee. Applications with incomplete materials will not proceed to the review process.  

Please note that admitted students must submit original, official academic transcripts for all previous degrees and original language test score reports upon registration. All original documents will be checked at the time of programme application and enrollment. Any misrepresentation in the documents and information provided will result in disqualification of their applications and subsequent enrollments in the University.

Contact us: 

Tel: 0755-23519400 

Office Hours: 8:30-12:00, 13:00-17:30 (Monday to Friday) 

Email: pg_sai@cuhk.edu.cn 

Office Address: 1^st Floor, TXA&TXB, 4^th Floor of TA, 2001 Longxiang Avenue, Longgang District, Shenzhen, Guangdong Province 

 1）持有研究型硕士学位者可申报博士项目；2）本科毕业生可申报哲学硕士或博士项目。所有申请者需具备计算机科学与工程或相关学科教育背景。1）持有研究型硕士学位者可申报博士项目；2）本科毕业生可申报哲学硕士或博士项目。所有申请者需具备计算机科学与工程或相关学科教育背景。

To facilitate the mutual selection process between applicants and supervisors, applicants may submit the names of their preferred supervisors or research groups. Please note that some research groups only admit MPhil students. A list of available research groups is provided below, categorized to address key AI challenges and opportunities. (Please click on the name of each research group for more details)

1. AI Core

(1) Trustworthy AI: This research group is dedicated to building safe, reliable, and ethical next-generation AI systems. Our research focuses on the adversarial defense, privacy protection, value alignment, and algorithmic fairness of large models and intelligent agents, aiming to drive the adoption of Trustworthy AI as a practical and deployable technical standard.

(2) Intelligent Optimization & Decision Analytics: This research group is dedicated to the development of next-generation intelligent decision-making algorithms. This is achieved by combining learning-based optimization and large language models with foundational approaches like integer programming and non-convex optimization. The application of these algorithms extends to practical domains such as industrial scheduling, revenue management, and large language model reasoning, with the aim of enabling high-quality, large-scale decision-making.

(3) Knowledge Graph & Large Language Model: This research group is dedicated to integrating Knowledge Graphs with Large Language Models to transform fragmented multimodal data from the fields of industrial and software engineering into computable, structured knowledge. Our goal is to construct the "knowledge brain" for next-generation intelligent systems, thereby empowering the leapfrog development of industrial intelligence and software engineering.

(4) AI Data Government: This research group focuses on data and compliance governance throughout the entire AI lifecycle. We are committed to establishing a new paradigm of tripartite synergy among "model, data, and governance," aiming to advance AI's development by unlocking its full potential while ensuring it remains trustworthy and controllable, thereby serving the national digital strategy and the development of an intelligent governance system.

(5) Advanced AI Systems and Infrastructure: This research group focuses on developing end-to-end AI systems by integrating novel deep learning algorithms with scalable training, deployment, and performance optimization workflows. We emphasize the full AI system lifecycle, from large-scale data collection and model training to evaluation, tuning, and efficient inference on distributed infrastructures. Our goal is to build robust, high-performing, and scalable AI systems capable of operating reliably in complex, real-world environments.

(6) Reinforcement Learning & Responsible AI: This research group advances Reinforcement Learning as a core paradigm for building adaptive, interactive AI systems, while integrating responsible AI principles to ensure alignment with human values, transparency in decision-making, and robustness in real-world deployment.

2. Embodied AI & Robotics

(1) Embodied AI for Multi-robot Collaboration: This research group is committed to advancing multi-robot systems through several key areas: developing cross-scale autonomous collaborative localization and communication; exploring collaborative environmental perception under spatiotemporal variance; and creating decision-making and planning frameworks that bridge loosely and tightly coupled approaches, all to push the boundaries of embodied intelligence in multi-robot collaboration.

(2) Intelligent Systems: This research group focuses on developing intelligent decision-making systems capable of autonomous learning in unknown and uncertain environments. Our research emphasizes explainable AI models in domains such as robotics, perception, and communication. We are committed to constructing efficient and analyzable novel design schemes for intelligent systems through observation and reasoning about physical systems.

(3) Geospatial Intelligence: This research group specializes in Geospatial Intelligence and Brain-inspired Navigation. We are dedicated to developing intelligent agents capable of perceiving and reasoning in complex environments, driving innovation in high-precision positioning and adaptive learning technologies.

(4) Embodied AI: From Principle to Practice: This research group investigates the fundamental principles required to achieve embodied AI and develops practical applications in areas such as navigation, manipulation, and human/multi robot collaboration. The goal is to advance embodied AI both theoretically and technically.

(5) Language and Interactive Intelligence: This research group focuses on the intersection of artificial intelligence, language technology, and interactive intelligence. AI is transforming spoken and natural language processing, enabling breakthroughs in speech recognition, machine translation, dialogue systems, text understanding, multilingual communication, and generative AI for text and speech. The revolution in Language and Interactive Intelligence is exemplified by the rapid integration of AI into applications that shape how humans interact, communicate, learn, and collaborate across languages and modalities.

(6) General-Purpose Embodied Control: This research group focuses on advancing AI algorithms and control theory for embodied intelligence robots. We integrate cutting-edge AI methods to develop intelligent robotic platforms stable, adaptive, safe, and generalizable interactions with the physical world.

3. AI for Sciences, Engineering and Medicine

(1) AI for Science: This research group dedicated to developing AI-driven intelligent robotic experimental systems and constructing an integrated, self-learning, and continuously optimizing platform with full-scope intelligence. Our work focuses on addressing key scientific challenges in the application of artificial intelligence to materials science, while also tackling major sustainability issues through the design and synthesis of novel materials. The group has established China's first intelligent material chemistry synthesis platform, integrating large-scale model technologies such as the AI Academic Mentor to create an embodied intelligent chemical experiment and synthesis system with perception and operational capabilities. Currently, we are actively developing a "chemical world model" that incorporates over 80% of the national research data in the field of photocatalysis, advancing materials research and development toward a new data-driven paradigm.

(2) Artificial Intelligence of Things (AIoT): This research group is dedicated to the study of distributed machine learning and artificial intelligence technologies to drive the evolution and development of next-generation wireless networks.

(3) Geospatial Intelligence: This research group specializes in Geospatial Intelligence and Brain-inspired Navigation. We are dedicated to developing intelligent agents capable of perceiving and reasoning in complex environments, driving innovation in high-precision positioning and adaptive learning technologies.

(4) AI-powered Urban Transportation Systems: We are building the next generation of AI-powered urban transportation systems: modeling how people and vehicles move, predicting congestion before it happens, evaluating public transit networks for fairness and resilience, and simulating policy impacts through digital twins.

(5) AI-driven Biometrics: This research group focuses on leveraging artificial intelligence to analyze physiological signals, such as gait and voice, to develop biometric identification technologies. Our work aims to advance the clinical application of unobtrusive health monitoring and disease diagnosis.

4. AI for Social Sciences

(1) AI Education: This research group is dedicated to fundamentally reshaping teaching and learning through the deep integration of artificial intelligence and education, with the ultimate goal of pioneering a future for education that is more effective and personalized.

(2) Econometric Learning: This research group aims to address the key challenges, such as endogeneity bias, that arise when empowering causal inference with machine learning. We are committed to ensuring the scientific rigor of econometric models while leveraging data-driven advantages, with the goal of providing new tools for economic research.

(3) AI-driven Social-economic Studies: This research group aims to leverage artificial intelligence to simulate socioeconomic systems, bridging the gap between technological advancement and social application. We provide actionable insights for the platform economy and public policy, with the ultimate goal of achieving more equitable AI-enhanced governance.

(4) AI Data Government: This research group focuses on data and compliance governance throughout the entire AI lifecycle. We are committed to establishing a new paradigm of tripartite synergy among "model, data, and governance," aiming to advance AI's development by unlocking its full potential while ensuring it remains trustworthy and controllable, thereby serving the national digital strategy and the development of an intelligent governance system.

5. AI for Medicine and Health

(1) AI-driven Precision Pathogenomics and Personalized Therapeutics: This research group focuses on the cutting-edge intersection of artificial intelligence and life sciences. We are dedicated to building precise and interpretable clinical intelligent analysis systems by fusing multimodal medical data with bioinformatics. Our research directions span intelligent diagnosis, pathogen detection, and public health emergency response, with the ultimate goal of driving the clinical translation and real-world application of AI technologies in the fields of precision medicine and healthcare.

(2) Embodied Intelligence for Next-generation Medicine: This research group focuses on integrating cutting-edge technology, including learning-based algorithms, novel surgical robot platform, new imaging modalities and processing methods, and miniature medical robotics, to achieve next-generation medical and surgical operations with high precision and effectiveness.

(3) AI in Clinical Medicine: We focus on the interdisciplinary frontier of AI and clinical medicine. The goal is to develop reliable AI models to address critical challenges in clinical medicine and to translating the developed systems into clinical practice.

6. Applied AI & Industry

(1) Industry-University Innovation Network: Bridging Academic Excellence with Real-World Impact: Industry-University Innovation Network is a collaborative platform under the School of Artificial Intelligence (SAI) at CUHK-Shenzhen dedicated to bridging academic excellence with real-world industrial needs. The group connects faculty, students, staff, and industry partners to co-create impactful AI solutions through joint projects, internships, seminars, and technology transfer and collaboration initiatives.

Anchored in GBA’s innovation ecosystem, the network focuses on transforming cutting-edge research into deployable applications across sectors. By fostering long-term partnerships and practice-oriented education, it aims to enhance students’ industry-readiness, support enterprises in their digital and AI-driven transformation, and strengthen CUHKSZ SAI as a leading AI institution.

The School of Artificial Intelligence offers the following scholarships and funding opportunities for outstanding PhD students. Doctoral students who maintain satisfactory academic progress are generally eligible for scholarships or funding support. The Admissions Committee will automatically assess doctoral applicants and award scholarships or funding at the appropriate level. No separate application is required.

Presidential Fellowship / Dean’s Scholarship

This category of scholarship includes a full tuition waiver (RMB 140,000 for 2026 Intake) and an annual living allowance of RMB 180,000. During the semesters in which the scholarship is awarded, recipients are required to undertake teaching assistantship or research assistantship duties for no more than 10 hours per week.
 

Teaching Assistantship / Research Assistantship / Graduate Assistantship

This funding scheme includes a full or half tuition scholarship, along with a stipend (or salary) corresponding to a 50% assistantship appointment during the nine-month regular academic year. Graduate students supported under this scheme typically serve as teaching assistants, research assistants, or administrative assistants, or a combination of these roles. A 50% assistantship involves 20 working hours per week, with a monthly stipend of no less than RMB 6,000.

These positions provide more than financial support—they play a vital role in students’ academic and professional development. While responsibilities and compensation vary by position, assistantships offer in-depth training within the student’s field of study, enhance research capabilities, and provide valuable teaching experience essential for academic careers. In addition, students develop key professional skills such as leadership, communication, and performance evaluation, and often engage in close academic collaboration with faculty members, leading to joint research publications.
 

SLAI Joint PhD Program

PhD students admitted to this program will receive tuition scholarships and living allowances provided by SLAI (Shenzhen Loop Area Institute). The selection and management of participating students are administered solely by SLAI.

● Are there scholarships and financial support available for MPhil students?

Currently, scholarships and financial support at the School of Artificial Intelligence are primarily oriented towards outstanding PhD students. Meanwhile, the Academia-Industry Collaboration Center is actively fostering close partnerships with various enterprises. We are exploring opportunities for enrolled MPhil students to participate in enterprise projects, which will provide corresponding project stipends or internship remuneration.