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Uio96/README.md

Hi, I'm Yunzhi 👋

Machine Learning Engineer building large-scale ML systems, with a background in robotics and 3D perception.

Currently working on production recommendation systems at TikTok, serving billions of users across global markets. My work focuses on designing scalable ML systems, improving efficiency, and bridging modeling with real-world system constraints.

🤖 Background in Robotics & Perception

Before industry, my research at Georgia Tech focused on robotics perception:

  • 3D vision, object pose estimation, and tracking
  • Category-level understanding and robust perception under real-world conditions
  • Publications at ICRA / IROS

⚙️ What I Work On

  • Large-scale ML systems (training, serving, optimization)
  • User intent modeling & decision systems
  • System efficiency (latency, throughput, compute trade-offs)
  • Bridging models with infrastructure in production

🧠 Interests

  • Robotics & autonomy (perception + decision-making)
  • Real-world ML systems beyond offline metrics
  • RL / learning-based control for large-scale systems
  • Bringing research ideas into production environments

🤝 Let's connect

Interested in robotics, autonomy, or building ML systems that work in the real world.

Pinned Loading

  1. ivalab/grasp_primitiveShapeivalab/grasp_primitiveShapePublic

    the implementation code of the paper "Using Synthetic Data and Deep Networks to Recognize Primitive Shapes for Object Grasping"

    C++ 16 3

  2. NVlabs/CenterPoseNVlabs/CenterPosePublic

    Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)

    Python 344 40

  3. ivapylibs/puzzle_solverivapylibs/puzzle_solverPublic

    Python 1 2

  4. NVlabs/ParallelInversionNVlabs/ParallelInversionPublic

    Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation (ICRA 2023)

    Cuda 35 8

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
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@ivalab

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Uio96/README.md

Hi, I'm Yunzhi 👋

Machine Learning Engineer building large-scale ML systems, with a background in robotics and 3D perception.

Currently working on production recommendation systems at TikTok, serving billions of users across global markets. My work focuses on designing scalable ML systems, improving efficiency, and bridging modeling with real-world system constraints.

🤖 Background in Robotics & Perception

Before industry, my research at Georgia Tech focused on robotics perception:

  • 3D vision, object pose estimation, and tracking
  • Category-level understanding and robust perception under real-world conditions
  • Publications at ICRA / IROS

⚙️ What I Work On

  • Large-scale ML systems (training, serving, optimization)
  • User intent modeling & decision systems
  • System efficiency (latency, throughput, compute trade-offs)
  • Bridging models with infrastructure in production

🧠 Interests

  • Robotics & autonomy (perception + decision-making)
  • Real-world ML systems beyond offline metrics
  • RL / learning-based control for large-scale systems
  • Bringing research ideas into production environments

🤝 Let's connect

Interested in robotics, autonomy, or building ML systems that work in the real world.

Pinned Loading

  1. ivalab/grasp_primitiveShapeivalab/grasp_primitiveShapePublic

    the implementation code of the paper "Using Synthetic Data and Deep Networks to Recognize Primitive Shapes for Object Grasping"

    C++ 16 3

  2. NVlabs/CenterPoseNVlabs/CenterPosePublic

    Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)

    Python 344 40

  3. ivapylibs/puzzle_solverivapylibs/puzzle_solverPublic

    Python 1 2

  4. NVlabs/ParallelInversionNVlabs/ParallelInversionPublic

    Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation (ICRA 2023)

    Cuda 35 8

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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@ivalab

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Uio96/README.md

Hi, I'm Yunzhi 👋

Machine Learning Engineer building large-scale ML systems, with a background in robotics and 3D perception.

Currently working on production recommendation systems at TikTok, serving billions of users across global markets. My work focuses on designing scalable ML systems, improving efficiency, and bridging modeling with real-world system constraints.

🤖 Background in Robotics & Perception

Before industry, my research at Georgia Tech focused on robotics perception:

  • 3D vision, object pose estimation, and tracking
  • Category-level understanding and robust perception under real-world conditions
  • Publications at ICRA / IROS

⚙️ What I Work On

  • Large-scale ML systems (training, serving, optimization)
  • User intent modeling & decision systems
  • System efficiency (latency, throughput, compute trade-offs)
  • Bridging models with infrastructure in production

🧠 Interests

  • Robotics & autonomy (perception + decision-making)
  • Real-world ML systems beyond offline metrics
  • RL / learning-based control for large-scale systems
  • Bringing research ideas into production environments

🤝 Let's connect

Interested in robotics, autonomy, or building ML systems that work in the real world.

Pinned Loading

  1. ivalab/grasp_primitiveShapeivalab/grasp_primitiveShapePublic

    the implementation code of the paper "Using Synthetic Data and Deep Networks to Recognize Primitive Shapes for Object Grasping"

    C++ 16 3

  2. NVlabs/CenterPoseNVlabs/CenterPosePublic

    Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)

    Python 344 40

  3. ivapylibs/puzzle_solverivapylibs/puzzle_solverPublic

    Python 1 2

  4. NVlabs/ParallelInversionNVlabs/ParallelInversionPublic

    Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation (ICRA 2023)

    Cuda 35 8

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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Organizations

@ivalab

Block or report Uio96

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Uio96/README.md

Hi, I'm Yunzhi 👋

Machine Learning Engineer building large-scale ML systems, with a background in robotics and 3D perception.

Currently working on production recommendation systems at TikTok, serving billions of users across global markets. My work focuses on designing scalable ML systems, improving efficiency, and bridging modeling with real-world system constraints.

🤖 Background in Robotics & Perception

Before industry, my research at Georgia Tech focused on robotics perception:

  • 3D vision, object pose estimation, and tracking
  • Category-level understanding and robust perception under real-world conditions
  • Publications at ICRA / IROS

⚙️ What I Work On

  • Large-scale ML systems (training, serving, optimization)
  • User intent modeling & decision systems
  • System efficiency (latency, throughput, compute trade-offs)
  • Bridging models with infrastructure in production

🧠 Interests

  • Robotics & autonomy (perception + decision-making)
  • Real-world ML systems beyond offline metrics
  • RL / learning-based control for large-scale systems
  • Bringing research ideas into production environments

🤝 Let's connect

Interested in robotics, autonomy, or building ML systems that work in the real world.

Pinned Loading

  1. ivalab/grasp_primitiveShapeivalab/grasp_primitiveShapePublic

    the implementation code of the paper "Using Synthetic Data and Deep Networks to Recognize Primitive Shapes for Object Grasping"

    C++ 16 3

  2. NVlabs/CenterPoseNVlabs/CenterPosePublic

    Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)

    Python 344 40

  3. ivapylibs/puzzle_solverivapylibs/puzzle_solverPublic

    Python 1 2

  4. NVlabs/ParallelInversionNVlabs/ParallelInversionPublic

    Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation (ICRA 2023)

    Cuda 35 8

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content
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@ivalab

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Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

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Report abuse
Uio96/README.md

Hi, I'm Yunzhi 👋

Machine Learning Engineer building large-scale ML systems, with a background in robotics and 3D perception.

Currently working on production recommendation systems at TikTok, serving billions of users across global markets. My work focuses on designing scalable ML systems, improving efficiency, and bridging modeling with real-world system constraints.

🤖 Background in Robotics & Perception

Before industry, my research at Georgia Tech focused on robotics perception:

  • 3D vision, object pose estimation, and tracking
  • Category-level understanding and robust perception under real-world conditions
  • Publications at ICRA / IROS

⚙️ What I Work On

  • Large-scale ML systems (training, serving, optimization)
  • User intent modeling & decision systems
  • System efficiency (latency, throughput, compute trade-offs)
  • Bridging models with infrastructure in production

🧠 Interests

  • Robotics & autonomy (perception + decision-making)
  • Real-world ML systems beyond offline metrics
  • RL / learning-based control for large-scale systems
  • Bringing research ideas into production environments

🤝 Let's connect

Interested in robotics, autonomy, or building ML systems that work in the real world.

Pinned Loading

  1. ivalab/grasp_primitiveShapeivalab/grasp_primitiveShapePublic

    the implementation code of the paper "Using Synthetic Data and Deep Networks to Recognize Primitive Shapes for Object Grasping"

    C++ 16 3

  2. NVlabs/CenterPoseNVlabs/CenterPosePublic

    Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)

    Python 344 40

  3. ivapylibs/puzzle_solverivapylibs/puzzle_solverPublic

    Python 1 2

  4. NVlabs/ParallelInversionNVlabs/ParallelInversionPublic

    Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation (ICRA 2023)

    Cuda 35 8

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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@ivalab

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Uio96/README.md

Hi, I'm Yunzhi 👋

Machine Learning Engineer building large-scale ML systems, with a background in robotics and 3D perception.

Currently working on production recommendation systems at TikTok, serving billions of users across global markets. My work focuses on designing scalable ML systems, improving efficiency, and bridging modeling with real-world system constraints.

🤖 Background in Robotics & Perception

Before industry, my research at Georgia Tech focused on robotics perception:

  • 3D vision, object pose estimation, and tracking
  • Category-level understanding and robust perception under real-world conditions
  • Publications at ICRA / IROS

⚙️ What I Work On

  • Large-scale ML systems (training, serving, optimization)
  • User intent modeling & decision systems
  • System efficiency (latency, throughput, compute trade-offs)
  • Bridging models with infrastructure in production

🧠 Interests

  • Robotics & autonomy (perception + decision-making)
  • Real-world ML systems beyond offline metrics
  • RL / learning-based control for large-scale systems
  • Bringing research ideas into production environments

🤝 Let's connect

Interested in robotics, autonomy, or building ML systems that work in the real world.

Pinned Loading

  1. ivalab/grasp_primitiveShapeivalab/grasp_primitiveShapePublic

    the implementation code of the paper "Using Synthetic Data and Deep Networks to Recognize Primitive Shapes for Object Grasping"

    C++ 16 3

  2. NVlabs/CenterPoseNVlabs/CenterPosePublic

    Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)

    Python 344 40

  3. ivapylibs/puzzle_solverivapylibs/puzzle_solverPublic

    Python 1 2

  4. NVlabs/ParallelInversionNVlabs/ParallelInversionPublic

    Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation (ICRA 2023)

    Cuda 35 8

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content
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Organizations

@ivalab

Block or report Uio96

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Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

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Uio96/README.md

Hi, I'm Yunzhi 👋

Machine Learning Engineer building large-scale ML systems, with a background in robotics and 3D perception.

Currently working on production recommendation systems at TikTok, serving billions of users across global markets. My work focuses on designing scalable ML systems, improving efficiency, and bridging modeling with real-world system constraints.

🤖 Background in Robotics & Perception

Before industry, my research at Georgia Tech focused on robotics perception:

  • 3D vision, object pose estimation, and tracking
  • Category-level understanding and robust perception under real-world conditions
  • Publications at ICRA / IROS

⚙️ What I Work On

  • Large-scale ML systems (training, serving, optimization)
  • User intent modeling & decision systems
  • System efficiency (latency, throughput, compute trade-offs)
  • Bridging models with infrastructure in production

🧠 Interests

  • Robotics & autonomy (perception + decision-making)
  • Real-world ML systems beyond offline metrics
  • RL / learning-based control for large-scale systems
  • Bringing research ideas into production environments

🤝 Let's connect

Interested in robotics, autonomy, or building ML systems that work in the real world.

Pinned Loading

  1. ivalab/grasp_primitiveShapeivalab/grasp_primitiveShapePublic

    the implementation code of the paper "Using Synthetic Data and Deep Networks to Recognize Primitive Shapes for Object Grasping"

    C++ 16 3

  2. NVlabs/CenterPoseNVlabs/CenterPosePublic

    Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)

    Python 344 40

  3. ivapylibs/puzzle_solverivapylibs/puzzle_solverPublic

    Python 1 2

  4. NVlabs/ParallelInversionNVlabs/ParallelInversionPublic

    Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation (ICRA 2023)

    Cuda 35 8

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
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Uio96/README.md

Hi, I'm Yunzhi 👋

Machine Learning Engineer building large-scale ML systems, with a background in robotics and 3D perception.

Currently working on production recommendation systems at TikTok, serving billions of users across global markets. My work focuses on designing scalable ML systems, improving efficiency, and bridging modeling with real-world system constraints.

🤖 Background in Robotics & Perception

Before industry, my research at Georgia Tech focused on robotics perception:

  • 3D vision, object pose estimation, and tracking
  • Category-level understanding and robust perception under real-world conditions
  • Publications at ICRA / IROS

⚙️ What I Work On

  • Large-scale ML systems (training, serving, optimization)
  • User intent modeling & decision systems
  • System efficiency (latency, throughput, compute trade-offs)
  • Bridging models with infrastructure in production

🧠 Interests

  • Robotics & autonomy (perception + decision-making)
  • Real-world ML systems beyond offline metrics
  • RL / learning-based control for large-scale systems
  • Bringing research ideas into production environments

🤝 Let's connect

Interested in robotics, autonomy, or building ML systems that work in the real world.

Pinned Loading

  1. ivalab/grasp_primitiveShapeivalab/grasp_primitiveShapePublic

    the implementation code of the paper "Using Synthetic Data and Deep Networks to Recognize Primitive Shapes for Object Grasping"

    C++ 16 3

  2. NVlabs/CenterPoseNVlabs/CenterPosePublic

    Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)

    Python 344 40

  3. ivapylibs/puzzle_solverivapylibs/puzzle_solverPublic

    Python 1 2

  4. NVlabs/ParallelInversionNVlabs/ParallelInversionPublic

    Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation (ICRA 2023)

    Cuda 35 8