NAAI 2026 Online PhD Program in Artificial Intelligence
National Academy of Artificial Intelligence (NAAI)
1. Program Overview
The National Academy of Artificial Intelligence (NAAI) is committed to cultivating AI researchers with international vision and innovative capabilities.
The 2026 Online PhD Program in Artificial Intelligence is now open for applications from outstanding young scholars worldwide.
Program Highlights:
Fully online research mode, supporting cross-country and cross-time-zone collaboration
Supervisory team composed of all NAAI members
Emphasis on original research and international academic publications
Access to PhD forums, research reports, and digital research platforms
Two intakes per year: Spring (February) and Autumn (September)
2. Program Duration & Tuition
Standard Duration: 4 years (minimum 3 years, maximum 6 years)
Tuition Fee: USD 10,000/year
Covers mentorship, access to online platforms, courses, and seminars
Does not cover international conference travel or additional experimental resources
3. English Requirements
IELTS ≥ 6.5 or TOEFL ≥ 90
4. Research Specializations & Suggested Topics
Applicants may select one primary research area. Each area includes 3–5 suggested topics for guidance:
1. AI Foundations
Mathematical logic and algorithm complexity
Probabilistic reasoning and statistical learning theory
Optimization algorithms and convex/non-convex analysis
2. Machine Learning
Supervised, unsupervised, and reinforcement learning
Graph neural networks and self-supervised learning
Meta-learning and lifelong learning
Transfer learning and domain adaptation
3. Deep Learning & Neural Networks
Convolutional neural networks (CNN) and visual models
Recurrent neural networks (RNN), Transformers, and language models
Model compression and efficient computation
Neural architecture search (NAS)
4. Natural Language Processing (NLP)
Semantic understanding and knowledge representation
Machine translation and text generation
Dialogue systems and large language models
Text summarization and sentiment analysis
5. Computer Vision
Image recognition, object detection, and segmentation
3D reconstruction and augmented reality
Video analysis and action recognition
Multi-modal vision understanding
6. Intelligent Robotics & Automation
Mobile robots and autonomous navigation
Robotic arms and intelligent control
Multi-robot collaborative systems
Reinforcement learning for robot control
7. Big Data & Intelligent Analytics
Data mining and knowledge discovery
Time-series analysis and forecasting
Cloud computing and distributed intelligent systems
Graph data and network analysis
8. AI in Healthcare
Medical image analysis and diagnostic support
Personalized healthcare and intelligent treatment plans
Bioinformatics and drug discovery
Health data modeling and prediction
9. AI Ethics, Policy & Society
Fairness, interpretability, and controllability of AI
AI governance and legal policy
Social impact and ethical risk assessment
Algorithm transparency and accountability
10. Intelligent Transportation & Autonomous Vehicles
Autonomous driving perception and decision systems
Traffic flow prediction and intelligent scheduling
Vehicle networking and smart infrastructure
Intelligent route planning and safety assessment
11. Human-AI Interaction & Augmented Intelligence
Intelligent user interface and interaction design
Augmented learning and decision support systems
Multi-modal interaction technologies
User behavior modeling and recommendation systems
12. AI in FinTech
Risk prediction and credit assessment
Financial intelligent decision systems
Blockchain and smart contract analysis
Portfolio optimization and quantitative strategies
13. IoT & Edge Intelligence
IoT device optimization and management
Edge computing and distributed AI
Sensor data analysis and applications
Smart home and smart city applications
14. AI Security & Privacy
Adversarial attacks and defense
Data privacy protection and federated learning
AI system reliability and robustness
Security strategy modeling and risk assessment
15. Quantum AI
Quantum machine learning
Quantum computing models and algorithms
Quantum information processing in AI
Quantum optimization and simulation
5. Eligibility
Master’s degree (or equivalent research experience)
Research experience in AI or related fields
English proficiency (IELTS ≥ 6.5 or TOEFL ≥ 90)
Complete research proposal and evidence of prior research achievements
6. Application Materials
Curriculum Vitae (CV)
Master’s degree certificate and transcript scans
Research proposal
Two academic recommendation letters
Evidence of research outputs (papers, patents, or project reports)
English proficiency test score (IELTS or TOEFL)
Submission Email:
secretary@thenaai.org
Application Deadlines:
Spring Intake: December 1, 2025
Autumn Intake: June 1, 2026
7. Admission & Registration
Admissions determined by academic committee review and announcement
Upon acceptance, students receive assigned supervisors, Researcher ID, and platform access
Program start dates:
Spring: February 2026
Autumn: September 2026
8. Academic & Research Requirements
Complete original research and publish at least one international journal or conference paper
Regularly submit progress reports and participate in mentor-led online seminars
Complete and defend the PhD dissertation through international review
Attend at least one international academic conference and submit a report or paper
All outputs archived in the NAAI Digital Thesis Repository
9. Supervisory Team
Supervised by all NAAI members
Each PhD student has at least one primary and one co-supervisor
Mentors provide guidance on research directions, methods, and publications
Regular international academic reviews and collaborative seminars
10. Contact
National Academy of Artificial Intelligence (NAAI)
secretary@thenaai.org
www.thenaai.org
Publication Date: October 16, 2025