At a Glance

1. Overview

    The full-time professional Master’s Program in Electronic Information (AI for Science) is built on the discipline of electronic information and focuses on emerging frontiers in artificial intelligence, including generative AI, world models, Agentic AI, Physical AI, and embodied intelligence. By deeply integrating advances in AI with scientific discovery and engineering innovation, the program aims to cultivate interdisciplinary leaders who can use AI to understand, model, and improve real-world systems and scientific problems.

    Leveraging the digital-intelligence faculty and interdisciplinary platforms of Tsinghua Shenzhen International Graduate School (Tsinghua SIGS), the program develops close industry–academia–research collaboration with leading enterprises in scientific and industrial intelligence. Its training emphasizes world models, large-model agents, robotics and embodied intelligence, human–AI/superintelligence integration, and physical simulation. Students are encouraged to work on authentic scientific questions and real engineering scenarios through integrated academic and practical training.

    The program welcomes applicants from both AI-related backgrounds—such as computer science, artificial intelligence, electronic information, and automation—and “X” disciplines such as mathematics, physics, chemistry, and biology. Students with AI backgrounds can deepen their mastery of frontier AI technologies, while students from scientific disciplines can systematically build an AI toolchain and apply it to frontier problems in their own fields. This diverse cohort structure is designed to promote cross-disciplinary inspiration and collaboration.

Program Objectives

    Students are expected to develop a systematic understanding of frontier AI theories and algorithms, including machine learning, deep learning, and world models, and to build the ability to independently tackle core AI research and engineering challenges. On this foundation, the program further guides students to apply advanced AI technologies to scientific and engineering frontiers, combining technological depth with broad interdisciplinary application.

Program Features

• AI × Science Integration: Connect frontier AI methods with fundamental scientific questions and complex engineering systems.

• Frontier Technology Orientation: Focus on generative AI, world models, Agentic AI, Physical AI, embodied intelligence, robotics, and physical simulation.

• Interdisciplinary Cohort: Bring together students from AI-related disciplines and mathematics, physics, chemistry, biology, and other scientific fields.

• Industry–Academia–Research Collaboration: Use real scientific and engineering scenarios to strengthen research, innovation, and practical problem-solving capabilities.

2. Faculty Information

    The program is supported by an interdisciplinary faculty team at Tsinghua SIGS. The current supervisor list is shown below. The list will continue to be updated, and the final supervisor arrangement is subject to the supervisor–student matching process after enrollment.

3. Core Courses and Training Components

    The curriculum is designed around the dual objective of strengthening core AI capabilities and enabling AI-driven scientific and engineering innovation. Based on the program’s current training objectives, the core curriculum and training activities will center on the following areas:

• Foundations of Artificial Intelligence: Systematic training in machine learning, deep learning, and related AI theories and algorithms.

• Frontier AI Technologies: Advanced study of areas such as generative AI, world models, large-model agents, Physical AI, robotics, and embodied intelligence.

• AI for Scientific Discovery: Methods and tools for using AI to model, analyze, and accelerate scientific discovery across disciplinary domains.

• Physical Modeling and Simulation: AI-enabled modeling and simulation for understanding and improving real-world physical systems.

Interdisciplinary Research and Engineering Practice: Project-based training built around authentic scientific questions and real engineering scenarios, with opportunities for industry–academia–research collaboration.

• Research Training and Degree Thesis: Supervised research, academic communication, research progress assessment, and completion of the master’s thesis in accordance with Tsinghua University and Tsinghua SIGS degree requirements.

Note: Specific course titles and training requirements are subject to the officially approved curriculum and training plan for the relevant academic year.

4. Tuition Fee and Language of Instruction

Tuition Fee

    RMB 33,000 per academic year for the 2027 intake. Other fees, including application fee, insurance, accommodation, and living expenses, are subject to the relevant regulations and notices of Tsinghua University and Tsinghua SIGS.

Language of Instruction and Language Requirements

    This program offers courses in both Chinese and English. Applicants should provide a standardized Chinese or English proficiency test score recognized by our institute, or proof that their prior degree program was taught in Chinese or English. Accepted standard tests are not limited to IELTS, TOEFL, Duolingo, and HSK, etc.

5. Program Duration

    The program is a full-time master’s program with a standard duration of 2 academic years. Students are required to complete the prescribed coursework, research and practical training, and degree thesis requirements within the period stipulated by Tsinghua University.

6. Degree Awarded

    Upon successful completion of all degree requirements, students will receive the relevant graduation certificate and degree certificate issued by Tsinghua University. The program is under Electronic Information (Program Code: 085400).

7. Contact Information

admission.ai4sci@sz.tsinghua.edu.cn