Lecturer · MSc in Computer Science (Data Science), Universiti Malaya
静态横幅 / Static banner · 原创动画 / Behind the animation
Engineering & research portfolio · Engineering highlights · Research brief · Academic CV · Learning notebook · guhang2011@126.com
I'm Hang Gu (顾航), a lecturer and teaching section director at 江苏财经职业技术学院, with an MSc in Computer Science (Data Science) from Universiti Malaya and a background in frontend engineering.
Engineering focus: frontend systems, explicit workflow states, data-quality checks and verifiable delivery. The public cases connect implementation choices with code, interactive demonstrations and scoped verification records.
Research interests: reliable multimodal learning with limited labels, frozen vision-language adaptation, validation sensitivity and data artifacts.
这里以工程技术为主：前端交互、工作流状态、数据质量与可复查交付。通过公开代码、项目演示和学习笔记说明设计取舍；同时保留有限标注下的多模态学习与模型评估研究记录。
| Research question | Approach | Authorship | Status as of September 2026 |
|---|---|---|---|
| FCP · Low-resource multimodal fake-news detection | Frozen CLIP adaptation, token-level bidirectional co-attention, cosine prototypes and data-artifact analysis | First author | Journal resubmission: International Journal of Machine Learning and Cybernetics |
| Validation sensitivity in limited-label news classification | Model selection and paired validation sampling | Order not stated in CV | Submitted to DASFAA 2027 |
| Vision-language multimodal behavior prediction | VideoMAE, DistilBERT, cross-attention and LSTM temporal modeling | First author | Accepted at ISCAIT 2026 |
Authorship and statuses above follow the September 2026 CV. The October portfolio update does not establish a new publication status or independently recheck experimental results.
My MSc thesis, Dental Deformities Prediction Using Bayesian Networks among Adolescents, used R and Bayesian networks to study conditional relationships in clinical data.
Research brief · Discussion draft · Code & verification evidence · Full academic CV
| Work | Focus and scope | Read / verify / try |
|---|---|---|
| KICP · Research | CLIP, learned prompts, co-attention and knowledge retrieval for multimodal fake-news detection | Code & run requirements |
| KAPT · Reproducibility learning | Curated KANO-based prompt components, validated early stopping and sample-aligned probability ensembles; synthetic examples | Reading & source attribution · Reproduction · Early-stopping replay |
| Silk Road Intelligence · Teaching engineering | Cross-border order workflow, stock consistency, permission scopes and simulated fulfillment; adapted from an existing college application | Screenshot gallery · Engineering notes |
| Counselor Workflow · Engineering case | Role-based interaction, state transitions, version checks and retry contracts; curated static demonstration | Architecture & scope · Online demo |
| Frontend & Data Lab · Learning experiments | Synthetic-data analytics, annotation agreement, bounded crawling and model-evaluation notes | Reading map · Interactive lab |
Reading path: research question → core code → verification steps and limitations → interactive case. Model self-study notes.
| Capability | What is visible in the public work |
|---|---|
| Interface contracts | Dynamic forms, role-scoped states, keyboard access, responsive layouts and browser-level checks. |
| Data quality | Deterministic cleaning, annotation agreement, quarantine records, CSV/SQLite/JSON hand-offs and bounded crawling. |
| Model evaluation | Baselines, validation sensitivity, threshold selection, confusion analysis and sample-aligned prediction ensembles. |
| Evidence-shaped delivery | Release gates, artifact hashes, scope notes, synthetic fixtures and explicit “not rerun” boundaries. |
工程阅读顺序： 需求问题 → 输入与状态契约 → 核心实现 → 定向检查 → 范围与限制。主页的 Engineering lens 将这些能力映射到项目案例、在线实验和验证记录。
18-second project walkthroughs / 项目动画： Early stopping · 模型早停 · Data quality audit · 数据质量审计. Silent animations generated from the demo logic with synthetic data; captions and interactive experiments are available on the site.
The learning lab is a newly assembled educational example. It is separate from employer software and research experiments. KICP contains research code; its README describes the external data and assets required to run it. KAPT preserves KANO source attribution and documents the scope of its component tests.
Earlier coursework / 早期课程练习
- WQD7006: historical Python exercises in data collection, regional aggregation and visualization.
- introdatascience: early R exercises in extraction, data cleaning and JSON serialization.
丝路智链 · 桌面与手机界面 / Silk Road Intelligence gallery
从既有学院应用改造的跨境订单教学案例，展示中哈合作主题登录、营销审核、订单台账与物流仿真。下列业务界面使用合成教学数据。
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既有后端报告记录 41 项通过（含共享账户基础测试），本次未重跑。支付与设备为仿真，来源和验证范围详见案例。
把代码中的问题整理成可以复查的笔记：为什么这样设计、如何验证、还有什么没有回答。在线阅读 6 篇双语笔记，支持主题筛选、搜索和打印。
| 主题 / Topic | 阅读入口 / Read |
|---|---|
| 模型学习 | 早停、样本对齐与集成 · 提示学习的张量契约 |
| 前端与数据 | 双语搜索、焦点与动态效果 · 数据清洗的质量契约 |
| 项目心得 | 订单幂等与库存一致性 · 权限边界与可复查交付 |
Compiled from public code and project documents on 17 October 2026, with AI-assisted drafting and translation. Each note separates source observations, teaching examples and proposed checks, with links to evidence; these are not new benchmark results or a historical lab diary.
从本地高校资料归档与协作项目整理的原创笔记，记录设计取舍、验证结果和待完成的工作。附上线、容量测试与个人 AI 接入模板。
全部 6 篇笔记 / All notes · 官方资料导航 / Official reading
Design decisions, validation and reusable checklists / 设计取舍与验证
| Start with a question | Read / Use |
|---|---|
| “500 人在线”到底验证了什么？ | 容量复盘 · 测试报告模板 |
| 每个账号如何使用自己的 AI？ | 密钥与模型接入 · 验收表 |
| 从开发机到学校服务器还差什么？ | 部署笔记 · 发布检查表 |
These are original notes and reusable checklists, with explicit testing limits. Linked references stay on their official sites; private product code and user data are not published here.
上传系统界面预览 / Upload system preview
来自本地 Edge/WebKit 自动化测试夹具的合成界面截图，仅用于展示布局和功能状态，不包含真实账号、API Key 或用户文件。
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Applied experience and teaching / 工程与教学经历
- Intelligent applications: document parsing, entity extraction, semantic retrieval and RAG workflows.
- Frontend systems: Vue / React, TypeScript, dynamic forms, interface contracts, accessibility and performance.
- Data systems: Python, R, SQL, Hadoop / Spark, reproducible analysis and visualization.
- Teaching: computing courses and practical projects spanning data collection, storage, analysis and presentation.
Recent applied work includes an ongoing AI contract-management project, an ongoing intelligent information-retrieval project, and a completed modular administrative-dashboard project. These are described as experience; their proprietary source code is not part of this profile.
Profile updated 19 October 2026. Authorship and research status follow the September 2026 CV; see the portfolio for evidence and scope.