🎓 Mentored by Harvard · Stanford · Peking University · Tsinghua Faculty

Build an AI-Powered Academic Portfolio
That Top Universities Notice

TinkerLab is an elite research lab where high school students work with world-class mentors to complete full research-to-product AI projects, producing publishable papers and portfolio pieces for university applications.

🎓 哈佛·斯坦福·北大·清华导师团队联合指导

用 AI 构建学术作品集
让名校看见真实的创造力

TinkerLab 是面向高中生的精英研究实验室。在顶尖院校导师指导下,完成从研究设计到产品开发的完整学术项目,产出可用于大学申请的论文与作品集。

10 Weeks
Full project cycle
1:4
Mentor-to-student ratio
3
Academic deliverables
100%
Completion rate
10 周
完整项目周期
1:4
师生比,个性化指导
3 项
最终学术产出
100%
学员完成率
🏛️

Harvard & Stanford

Mentors from top CS &
AI research labs

🎓

Peking & Tsinghua

Academic advisors &
research methodology

🔬

Published Research

Students produce
peer-reviewable papers

📜

Mentor Recommendation

Personalized letters from
faculty-level advisors

🏛️

哈佛·斯坦福

来自顶尖 CS 与
AI 实验室的导师

🎓

北大·清华

学术顾问团队
指导研究方法

🔬

可发表论文

学生产出达到
学术发表标准

📜

导师推荐信

来自教授级导师的
个性化推荐信

Not "Learning AI" — Using AI for Research

不是「学 AI」,是「用 AI 做研究」

A three-layer progressive model that transforms students from AI users into AI researchers and creators

三层递进能力模型,让学生从 AI 使用者成长为 AI 研究者与创造者

Layer 1 · Understand

Understand AI's Nature & Boundaries

Not memorizing concepts, but truly understanding how AI works, when to trust it, and when it fails. Building the foundation of critical thinking.

Layer 2 · Research

Use AI to Power Academic Research

Design research questions, build datasets, create evaluation frameworks. Students learn to transform curiosity into testable hypotheses.

Layer 3 · Create

Build Real Products with AI

From code to interface, turning research findings into runnable, demonstrable applications. This is the most compelling material for applications.

Layer 1 · 理解

理解 AI 的本质与边界

不是记概念,而是真正理解 AI 如何工作、何时可信、何时会出错。建立批判性思维的基础。

Layer 2 · 研究

用 AI 辅助学术研究

设计研究问题、构建数据集、设计评估框架。学生掌握将好奇心转化为可验证假设的能力。

Layer 3 · 创造

用 AI 构建真实产品

从代码到界面,将研究成果变成可运行、可展示的应用程序。这是最有说服力的申请材料。

Student Project Showcase

Each project represents a complete research-to-product pipeline — the kind of work that stands out in university applications

学生项目展示

每个项目都是完整的「研究→产品」流程 — 正是名校申请中最具区分度的材料

AI + Psychology

Micro-Expression Detection in Interview Contexts

Developed an AI system that identifies subtle facial micro-expressions during mock interviews, comparing machine detection accuracy against trained psychologists to explore perception gaps.

AI + 心理学

面试场景中的微表情识别系统

构建 AI 微表情识别系统,在模拟面试场景中捕捉细微面部信号,对比机器与专业心理学家的判断差异,探索感知盲区。

Digital Humanities

Silk Road Trade Record Pattern Mining

Applied NLP to extract and visualize trade patterns from historical merchant correspondence along the Silk Road, mapping commodity flows and cultural exchange across dynasties.

数字人文

丝绸之路贸易记录模式挖掘

运用 NLP 从丝路商人往来书信中提取贸易模式,可视化历代商品流动与文化交流路径。

Computational Linguistics

Proto-Austronesian Sound System Reconstruction

Leveraging AI-powered comparative analysis to reconstruct phonological patterns of an ancient language family by identifying systematic sound correspondences across modern descendant languages.

计算语言学

原始南岛语音系重建

利用 AI 驱动的比较分析方法,通过识别现代后裔语言间的系统音变对应规律,重建古语族的音韵系统。

Creative Tech

Classical Music to Visual Narrative Generation

Transforms musical compositions into procedurally generated 3D visual stories, mapping harmony and rhythm to dynamic scene elements with real-time WebGL rendering.

创意科技

古典音乐→视觉叙事生成

将音乐作品转化为程序化生成的 3D 视觉故事,将和声与节奏映射为动态场景元素,实时 WebGL 渲染。

AI + Literature

AI Short Fiction Generation & Literary Critique

Built a system that generates short stories following genre conventions, with a multi-dimensional evaluation framework assessing narrative structure, character depth, and stylistic coherence.

AI + 文学

AI 短篇小说生成与文学评价系统

构建短篇小说生成系统,遵循类型文学范式创作,并从叙事结构、人物深度、风格一致性等维度进行多维质量评估。

Brand + Culture

Cross-Cultural Color Symbolism in Global Advertising

Developed an AI-powered framework analyzing how color usage in advertisements carries different cultural meanings across East Asian and Western markets, scoring brand-color alignment.

品牌 + 文化

全球广告中的跨文化色彩象征研究

构建 AI 驱动的分析框架,研究广告中色彩运用在东亚与西方市场的文化含义差异,量化品牌-色彩适配度。

What Students Walk Away With

Tangible outcomes that strengthen university applications

学生最终获得什么

可直接用于大学申请的有力材料

📄

Research Paper

Publishable academic paper with original methodology and findings

💻

Working Product

Deployed web application demonstrating technical capability

🏆

Certificate

TinkerLab completion certificate endorsed by Harvard · Stanford · PKU · Tsinghua mentor team

📄

学术论文

具有独立方法论和研究发现的可发表学术论文

💻

可运行产品

已部署的 Web 应用,展示技术落地能力

🏆

权威证书

TinkerLab 结业证书,哈佛·斯坦福·北大·清华导师团联合签发

8-Week Intensive Program

From zero to a complete AI-powered academic project

8 周强化项目

从零开始,完成一个完整的 AI 学术项目

W1

AI Fundamentals & Research Design

Understand how AI works, define research questions, draft project proposals

W2

Data Collection & Prompt Engineering

Learn to build datasets, master AI prompting techniques, set up development tools

W3-4

Core Development Sprint

Build AI pipelines (LangChain/LangGraph), create evaluation frameworks, iterate on prototypes

W5-6

Product Building & Testing

Deploy interactive web interfaces (Gradio/HTML), conduct user testing, refine outputs

W7-8

Paper Writing & Final Presentation

Write research paper, prepare portfolio materials, present at demo day

W1

AI 基础与研究设计

理解 AI 工作原理,确定研究方向,撰写项目提案

W2

数据采集与 Prompt 工程

学习构建数据集,掌握 AI 提示词技术,搭建开发环境

W3-4

核心开发冲刺

搭建 AI 管道(LangChain/LangGraph),创建评估框架,迭代原型

W5-6

产品构建与测试

部署交互界面(Gradio/HTML),进行用户测试,优化输出

W7-8

论文撰写与最终展示

撰写研究论文,准备作品集材料,参加 Demo Day 汇报

"The moment my son demonstrated his AI project at the family dinner table — analyzing ancient poetry with machine learning — I knew this program was different. It wasn't just a certificate. He built something real."
— Parent of 2025 Cohort Student, admitted to Cornell University
"当儿子在家庭聚餐时展示他的 AI 项目——用机器学习分析古诗词——我知道这个项目和别的不一样。这不只是一张证书,他真的做出了东西。"
— 2025 届学生家长,该生已录取康奈尔大学

Limited to 30 Students Per Cohort

Applications for 2026 Fall Cohort are now open. Spots are limited — reach out to learn more.

Contact us: hello@tinkerlab.com.cn

每期仅限 30 名学生

2026 秋季班现已开放申请,名额有限,欢迎咨询了解详情。

联系我们:hello@tinkerlab.com.cn