Policy presence
Southern University of Science and Technology (SUSTech) has 3 source-backed public claims for policy presence; deterministic analysis status: unclear.
Shenzhen, China (Mainland)
Southern University of Science and Technology (SUSTech)
Southern University of Science and Technology (SUSTech) is listed as QS 2026 rank =343. Southern University of Science and Technology (SUSTech) has 5 source-backed AI policy claim records from 3 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
Southern University of Science and Technology (SUSTech) is listed as QS 2026 rank =343. Southern University of Science and Technology (SUSTech) has 5 source-backed AI policy claim records from 3 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Citation-ready summary
As of this public record, University AI Policy Tracker lists Southern University of Science and Technology (SUSTech) as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 5 source-backed claims, including 5 reviewed claims, from 3 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/southern-university-of-science-and-technology-sustech.json. The entity-level confidence is 96%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.
Policy signals in this record
- Evidence includes Academic integrity claims.
- Evidence includes Source status claims.
- No specific AI service name is highlighted by the current public claim text.
- Disclosure, acknowledgment, citation, or attribution language appears in the public claim text.
- Privacy, sensitive-data, or security language appears in the public claim text.
Review: Agent reviewed
This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.
This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.
Policy profile
Deterministic source-backed dimensions derived from this record's public claims.
Review: Machine candidate
Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.
Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.
AI disclosure
Southern University of Science and Technology (SUSTech) has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.
Coursework
Southern University of Science and Technology (SUSTech) has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
Southern University of Science and Technology (SUSTech) has 2 source-backed public claims for exams; deterministic analysis status: blocked.
Privacy and data entry
Southern University of Science and Technology (SUSTech) has 2 source-backed public claims for privacy and data entry; deterministic analysis status: recommended.
Academic integrity
Southern University of Science and Technology (SUSTech) has 2 source-backed public claims for academic integrity; deterministic analysis status: blocked.
Approved tools
Southern University of Science and Technology (SUSTech) has 3 source-backed public claims for approved tools; deterministic analysis status: required.
Named AI services
No source-backed public claim naming a specific AI service is present in this profile.
The current public tracker record does not contain claim evidence naming a specific AI service.
Teaching guidance
Southern University of Science and Technology (SUSTech) has 2 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
Southern University of Science and Technology (SUSTech) has 1 source-backed public claim for research guidance; deterministic analysis status: restricted.
Security and procurement
Southern University of Science and Technology (SUSTech) has 1 source-backed public claim for security and procurement; deterministic analysis status: required.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
Evidence-backed claims
5 reviewed evidence-backed public claim
Academic Integrity
SUSTech's Control Science and Engineering doctoral degree standard says that if AI tools such as language models or text-generation tools are used during thesis writing, their role must be auxiliary and they may not replace the degree applicant's core research work or independent thinking.
Review: Agent reviewed
Normalized value: control_science_doctoral_thesis_ai_tools_auxiliary_only
Original evidence
Evidence 1若在论文写作过程中使用人工智能工具（如语言模型、文本生成工具等），需明确人工智能工具的辅助性作用，不得替代学位申请人的核心研究工作和独立思考。
Localized display only
If AI tools are used in thesis writing, their role must be auxiliary and may not replace the applicant's core research work or independent thinking.
Academic Integrity
SUSTech's Control Science and Engineering doctoral degree standard says supervisors should oversee AI-tool use throughout the thesis process, ensure it conforms to academic norms, and confirm it in the thesis originality statement.
Review: Agent reviewed
Normalized value: control_science_doctoral_thesis_ai_supervision_originality_statement
Original evidence
Evidence 1导师应全程监督人工智能工具的使用，确保其符合学术规范，并在学位论文原创性声明中予以确认。
Localized display only
The supervisor should oversee AI-tool use throughout, ensure it conforms to academic norms, and confirm this in the thesis originality statement.
Source Status
SUSTech's CS114 Introduction to Generative Artificial Intelligence course specification is course-level curriculum material that says the course covers generative AI history, principles, deployment, interdisciplinary applications, and ethical, security, and privacy discussions; it is not an institutional AI-use policy.
Review: Agent reviewed
Normalized value: course-level curriculum source only; not institutional AI-use policy
Original evidence
Evidence 1本课程旨在介绍生成式人工智能的发展历史、基本原理、部署应用、跨学科实践、伦理安全等内容。通过本课程，学生可以（以 DeepSeek 为例）理解生成式人工智能的基本原理与能力边界，掌握部署实用方式。
Localized display only
The course specification says CS114 introduces GAI history, principles, deployment, interdisciplinary practice, and ethics/security content.
Source Status
SUSTech's CS114 course calendar includes lessons on GAI privacy and security, GAI ethics, AI hallucination in large models, GAI-assisted programming, and AI agent engineering; this is course-level curriculum evidence rather than an institutional AI-use policy.
Review: Agent reviewed
Normalized value: course calendar source only; not institutional AI-use policy
Original evidence
Evidence 1第十一课：大模型幻觉... 第十二课：GAI 与智能体搭建... 第十四课：GAI 隐私保护与安全 GAI 数据隐私保护机制 GAI 安全实现技术介绍 第十五课：GAI 伦理 生成内容可信度评估 伦理问题讨论
Localized display only
The teaching calendar includes AI hallucination, agent building, GAI privacy and security, and GAI ethics lessons.
Source Status
A 2026 SUSTech Library embedded AI-literacy teaching page reports that a library session for the Intelligent Ocean Exploration course introduced AI hallucination, algorithmic bias, AI academic writing norms, citation-labeling guidance, and AI academic application boundaries; this is course-session evidence rather than institutional policy.
Review: Agent reviewed
Normalized value: course-session report only; not institutional AI-use policy
Original evidence
Evidence 14月3日，在嵌入式教学第二讲“AI在学术研究中的边界与伦理”中，学科馆员张依兮介绍了AI幻觉和算法偏见、AI目前在学术研究场景下的利用，以及图书馆订购的学术AI工具。课程结合大量案例带同学们了解AI学术不端与伦理问题，并详细介绍了AI学术写作规范与引用标注指南，明确AI学术应用的“红线”与“绿道”，筑牢科研诚信的底线。
Localized display only
The library page says the session introduced AI hallucination, algorithmic bias, AI academic use, writing norms, citation labeling, and academic-use boundaries.
Candidate claims
0 machine or needs-review claim
Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.
Official sources
3 source attribution
CS114 Introduction to Generative Artificial Intelligence course specification
mirrors.sustech.edu.cn
图书馆AI素养教育嵌入林间院士《智能海洋探测》课程教学
lib.sustech.edu.cn
控制科学与工程学科博士学位授予标准
aim.sustech.edu.cn
Change log
Source-check timeline and diff-style claim/evidence preview.
View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.
Corrections and missing evidence
Corrections create review tasks and do not directly change this public record.
If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.