') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ', 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ', 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ', 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); })(); XiaoyangBi (Billyy) · GitHub
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    XiaoyangBi/README.md

    Typing SVG

    🚀 About Me

    I'm XiaoyangBi (毕骁扬 / Billyy), an AI Product Manager and researcher exploring the deep integration of AI with real-world scenarios. Currently pursuing my Master's degree in Automation (AI track) at Xiamen University (985), recommended for admission.

    I have product experience at Tencent (WeChat Pay & CSIG AI), working on WeChat Pay's "Withdrawal Savings" banking strategy and e-commerce search planning, as well as AI-powered industrial quality inspection. My research covers Computer Vision, Diffusion Models, and GANs, with publications at IJCNN (CCF-C) and a first-author paper submitted to JIMS (SCI Q1).

    中文版个人简介 (Click to expand)

    你好！我是 毕骁扬，AI 产品经理 & 研究者，致力于探索 AI 与真实场景的深度融合。目前就读于厦门大学（985）自动化系 AI 方向硕士，本科同样毕业于厦大人工智能专业，保研推免。

    曾在微信支付负责 提现笔笔省 金融银行策略 / 电商搜索规划落地，在腾讯 CSIG推动工业质检 AI 产品能力升级，主导多模态大模型 Demo 落地及 POC 实施。也在 MetaGPT 推动开源 Multi-Agent 产品迭代。

    研究方向包括扩散模型异常检测、GAN 图像生成，IJCNN（CCF-C）已录用一篇，SCI 一区 JIMS 在投一篇（一作）。

    曾获华为昇腾 AI 创新大赛全国金奖、NLPCC 2024 第一名、互联网+省级金奖、美赛 F 奖等奖项。

    Always open to collaborations on AI products, research, or interesting tech discussions!

    📸 Featured Projects

    Check out my GitHub Repositories for full source code, and visit my Personal Homepage for more details.

    • 墨卡 MoCard — Intelligent card creation tool that turns ideas into visual form instantly. Built with React, lightweight and elegant. ReactProductivityTools

    • "非技术人的 GitHub" — AI 职业实训模拟 — Entrepreneurial project: an AI-powered career training simulator addressing employment challenges in the AI era. Leverages AI dynamic simulation for experiential learning. AI EducationSimulation0-1

    • DSD-GAN — 中国画白描上色 — Proposes a multi-scale discriminator with attention mechanism for high-quality automatic coloring of Chinese painting line drawings. Published at IJCNN (CCF-C). GANPyTorchComputer VisionResearch

    • MCD-AAS — 掩码引导扩散异常检测 — First-author research proposing a mask-conditioned diffusion framework (MCD-AAS) to synthesize high-quality anomaly samples for industrial defect detection. Submitted to JIMS (SCI Q1). Diffusion ModelsComputer VisionResearch

    🛠 Technical Stack

    🤖 AI & LLM

    PyTorchHugging FaceOpenAIPrompt Engineering

    💻 Programming & Web

    PythonTypeScriptReactNext.jsSupabase

    📊 Product & Data

    Product DesignData AnalysisUser Research

    🛠 Tools & DevOps

    GitDockerLinux

    🤝🏻 Connect with Me

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    "Exploring the deep integration of AI with real-world scenarios to build products that matter." ✨

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