diff --git a/README.md b/README.md
index aba6c6f..7547359 100644
--- a/README.md
+++ b/README.md
@@ -1,2 +1,248 @@
-# cv2
-My new CV written with RenderCV
+# miti99's CV
+
+- Email: [john.doe@email.com](mailto:john.doe@email.com)
+- Location: San Francisco, CA
+- Website: [rendercv.com](https://rendercv.com/)
+- LinkedIn: [rendercv](https://linkedin.com/in/rendercv)
+- GitHub: [rendercv](https://github.com/rendercv)
+
+
+# Welcome to RenderCV
+RenderCV reads a CV written in a YAML file, and generates a PDF with professional typography.
+
+See the [documentation](https://docs.rendercv.com) for more details.
+
+# Education
+## **Princeton University**, Computer Science
+
+**PhD**
+
+Princeton, NJ
+
+Sept 2018 – May 2023
+
+- Thesis: Efficient Neural Architecture Search for Resource-Constrained Deployment
+
+- Advisor: Prof. Sanjeev Arora
+
+- NSF Graduate Research Fellowship, Siebel Scholar (Class of 2022)
+
+
+
+## **Boğaziçi University**, Computer Engineering
+
+**BS**
+
+Istanbul, Türkiye
+
+Sept 2014 – June 2018
+
+- GPA: 3.97/4.00, Valedictorian
+
+- Fulbright Scholarship recipient for graduate studies
+
+
+
+# Experience
+## **Nexus AI**, Co-Founder & CTO
+
+San Francisco, CA
+
+June 2023 – present
+
+
+
+2 years 9 months
+
+- Built foundation model infrastructure serving 2M+ monthly API requests with 99.97% uptime
+
+- Raised $18M Series A led by Sequoia Capital, with participation from a16z and Founders Fund
+
+- Scaled engineering team from 3 to 28 across ML research, platform, and applied AI divisions
+
+- Developed proprietary inference optimization reducing latency by 73% compared to baseline
+
+
+
+## **NVIDIA Research**, Research Intern
+
+Santa Clara, CA
+
+May 2022 – Aug 2022
+
+
+
+4 months
+
+- Designed sparse attention mechanism reducing transformer memory footprint by 4.2x
+
+- Co-authored paper accepted at NeurIPS 2022 (spotlight presentation, top 5% of submissions)
+
+
+
+## **Google DeepMind**, Research Intern
+
+London, UK
+
+May 2021 – Aug 2021
+
+
+
+4 months
+
+- Developed reinforcement learning algorithms for multi-agent coordination
+
+- Published research at top-tier venues with significant academic impact
+
+  - ICML 2022 main conference paper, cited 340+ times within two years
+
+  - NeurIPS 2022 workshop paper on emergent communication protocols
+
+  - Invited journal extension in JMLR (2023)
+
+
+
+## **Apple ML Research**, Research Intern
+
+Cupertino, CA
+
+May 2020 – Aug 2020
+
+
+
+4 months
+
+- Created on-device neural network compression pipeline deployed across 50M+ devices
+
+- Filed 2 patents on efficient model quantization techniques for edge inference
+
+
+
+## **Microsoft Research**, Research Intern
+
+Redmond, WA
+
+May 2019 – Aug 2019
+
+
+
+4 months
+
+- Implemented novel self-supervised learning framework for low-resource language modeling
+
+- Research integrated into Azure Cognitive Services, reducing training data requirements by 60%
+
+
+
+# Projects
+## **[FlashInfer](https://github.com/)**
+
+Jan 2023 – present
+
+Open-source library for high-performance LLM inference kernels
+
+- Achieved 2.8x speedup over baseline attention implementations on A100 GPUs
+
+- Adopted by 3 major AI labs, 8,500+ GitHub stars, 200+ contributors
+
+
+
+## **[NeuralPrune](https://github.com/)**
+
+Jan 2021
+
+Automated neural network pruning toolkit with differentiable masks
+
+- Reduced model size by 90% with less than 1% accuracy degradation on ImageNet
+
+- Featured in PyTorch ecosystem tools, 4,200+ GitHub stars
+
+
+
+# Publications
+## **Sparse Mixture-of-Experts at Scale: Efficient Routing for Trillion-Parameter Models**
+
+July 2023
+
+*John Doe*, Sarah Williams, David Park
+
+[10.1234/neurips.2023.1234](https://doi.org/10.1234/neurips.2023.1234) (NeurIPS 2023)
+
+
+
+## **Neural Architecture Search via Differentiable Pruning**
+
+Dec 2022
+
+James Liu, *John Doe*
+
+[10.1234/neurips.2022.5678](https://doi.org/10.1234/neurips.2022.5678) (NeurIPS 2022, Spotlight)
+
+
+
+## **Multi-Agent Reinforcement Learning with Emergent Communication**
+
+July 2022
+
+Maria Garcia, *John Doe*, Tom Anderson
+
+[10.1234/icml.2022.9012](https://doi.org/10.1234/icml.2022.9012) (ICML 2022)
+
+
+
+## **On-Device Model Compression via Learned Quantization**
+
+May 2021
+
+*John Doe*, Kevin Wu
+
+[10.1234/iclr.2021.3456](https://doi.org/10.1234/iclr.2021.3456) (ICLR 2021, Best Paper Award)
+
+
+
+# Selected Honors
+- MIT Technology Review 35 Under 35 Innovators (2024)
+
+- Forbes 30 Under 30 in Enterprise Technology (2024)
+
+- ACM Doctoral Dissertation Award Honorable Mention (2023)
+
+- Google PhD Fellowship in Machine Learning (2020 – 2023)
+
+- Fulbright Scholarship for Graduate Studies (2018)
+
+# Skills
+**Languages:** Python, C++, CUDA, Rust, Julia
+
+**ML Frameworks:** PyTorch, JAX, TensorFlow, Triton, ONNX
+
+**Infrastructure:** Kubernetes, Ray, distributed training, AWS, GCP
+
+**Research Areas:** Neural architecture search, model compression, efficient inference, multi-agent RL
+
+# Patents
+1. Adaptive Quantization for Neural Network Inference on Edge Devices (US Patent 11,234,567)
+
+1. Dynamic Sparsity Patterns for Efficient Transformer Attention (US Patent 11,345,678)
+
+1. Hardware-Aware Neural Architecture Search Method (US Patent 11,456,789)
+
+# Invited Talks
+1. Scaling Laws for Efficient Inference — Stanford HAI Symposium (2024)
+
+1. Building AI Infrastructure for the Next Decade — TechCrunch Disrupt (2024)
+
+1. From Research to Production: Lessons in ML Systems — NeurIPS Workshop (2023)
+
+1. Efficient Deep Learning: A Practitioner's Perspective — Google Tech Talk (2022)
+
+# Any Section Title
+You can use any section title you want.
+
+You can choose any entry type for the section: `TextEntry`, `ExperienceEntry`, `EducationEntry`, `PublicationEntry`, `BulletEntry`, `NumberedEntry`, or `ReversedNumberedEntry`.
+
+Markdown syntax is supported everywhere.
+
+The `design` field in YAML gives you control over almost any aspect of your CV design.
+
+See the [documentation](https://docs.rendercv.com) for more details.
diff --git a/index.html b/index.html
new file mode 100644
index 0000000..7dc5b9d
--- /dev/null
+++ b/index.html
@@ -0,0 +1,256 @@
+<!DOCTYPE html>
+<html lang="en">
+
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1">
+    <meta http-equiv="X-UA-Compatible" content="ie=edge">
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+
+    <!-- To automatically render math in text elements, include the auto-render extension: -->
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+
+        @media (max-width: 767px) {
+            .markdown-body {
+                padding: 15px;
+            }
+        }
+    </style>
+</head>
+
+<body>
+    <article class="markdown-body">
+        <h1>miti99's CV</h1>
+        <ul>
+        <li>Email: <a href="mailto:john.doe@email.com">john.doe@email.com</a></li>
+        <li>Location: San Francisco, CA</li>
+        <li>Website: <a href="https://rendercv.com/">rendercv.com</a></li>
+        <li>LinkedIn: <a href="https://linkedin.com/in/rendercv">rendercv</a></li>
+        <li>GitHub: <a href="https://github.com/rendercv">rendercv</a></li>
+        </ul>
+        <h1>Welcome to RenderCV</h1>
+        <p>RenderCV reads a CV written in a YAML file, and generates a PDF with professional typography.</p>
+        <p>See the <a href="https://docs.rendercv.com">documentation</a> for more details.</p>
+        <h1>Education</h1>
+        <h2><strong>Princeton University</strong>, Computer Science</h2>
+        <p><strong>PhD</strong></p>
+        <p>Princeton, NJ</p>
+        <p>Sept 2018 – May 2023</p>
+        <ul>
+        <li>
+        <p>Thesis: Efficient Neural Architecture Search for Resource-Constrained Deployment</p>
+        </li>
+        <li>
+        <p>Advisor: Prof. Sanjeev Arora</p>
+        </li>
+        <li>
+        <p>NSF Graduate Research Fellowship, Siebel Scholar (Class of 2022)</p>
+        </li>
+        </ul>
+        <h2><strong>Boğaziçi University</strong>, Computer Engineering</h2>
+        <p><strong>BS</strong></p>
+        <p>Istanbul, Türkiye</p>
+        <p>Sept 2014 – June 2018</p>
+        <ul>
+        <li>
+        <p>GPA: 3.97/4.00, Valedictorian</p>
+        </li>
+        <li>
+        <p>Fulbright Scholarship recipient for graduate studies</p>
+        </li>
+        </ul>
+        <h1>Experience</h1>
+        <h2><strong>Nexus AI</strong>, Co-Founder &amp; CTO</h2>
+        <p>San Francisco, CA</p>
+        <p>June 2023 – present</p>
+        <p>2 years 9 months</p>
+        <ul>
+        <li>
+        <p>Built foundation model infrastructure serving 2M+ monthly API requests with 99.97% uptime</p>
+        </li>
+        <li>
+        <p>Raised $18M Series A led by Sequoia Capital, with participation from a16z and Founders Fund</p>
+        </li>
+        <li>
+        <p>Scaled engineering team from 3 to 28 across ML research, platform, and applied AI divisions</p>
+        </li>
+        <li>
+        <p>Developed proprietary inference optimization reducing latency by 73% compared to baseline</p>
+        </li>
+        </ul>
+        <h2><strong>NVIDIA Research</strong>, Research Intern</h2>
+        <p>Santa Clara, CA</p>
+        <p>May 2022 – Aug 2022</p>
+        <p>4 months</p>
+        <ul>
+        <li>
+        <p>Designed sparse attention mechanism reducing transformer memory footprint by 4.2x</p>
+        </li>
+        <li>
+        <p>Co-authored paper accepted at NeurIPS 2022 (spotlight presentation, top 5% of submissions)</p>
+        </li>
+        </ul>
+        <h2><strong>Google DeepMind</strong>, Research Intern</h2>
+        <p>London, UK</p>
+        <p>May 2021 – Aug 2021</p>
+        <p>4 months</p>
+        <ul>
+        <li>
+        <p>Developed reinforcement learning algorithms for multi-agent coordination</p>
+        </li>
+        <li>
+        <p>Published research at top-tier venues with significant academic impact</p>
+        </li>
+        <li>
+        <p>ICML 2022 main conference paper, cited 340+ times within two years</p>
+        </li>
+        <li>
+        <p>NeurIPS 2022 workshop paper on emergent communication protocols</p>
+        </li>
+        <li>
+        <p>Invited journal extension in JMLR (2023)</p>
+        </li>
+        </ul>
+        <h2><strong>Apple ML Research</strong>, Research Intern</h2>
+        <p>Cupertino, CA</p>
+        <p>May 2020 – Aug 2020</p>
+        <p>4 months</p>
+        <ul>
+        <li>
+        <p>Created on-device neural network compression pipeline deployed across 50M+ devices</p>
+        </li>
+        <li>
+        <p>Filed 2 patents on efficient model quantization techniques for edge inference</p>
+        </li>
+        </ul>
+        <h2><strong>Microsoft Research</strong>, Research Intern</h2>
+        <p>Redmond, WA</p>
+        <p>May 2019 – Aug 2019</p>
+        <p>4 months</p>
+        <ul>
+        <li>
+        <p>Implemented novel self-supervised learning framework for low-resource language modeling</p>
+        </li>
+        <li>
+        <p>Research integrated into Azure Cognitive Services, reducing training data requirements by 60%</p>
+        </li>
+        </ul>
+        <h1>Projects</h1>
+        <h2><strong><a href="https://github.com/">FlashInfer</a></strong></h2>
+        <p>Jan 2023 – present</p>
+        <p>Open-source library for high-performance LLM inference kernels</p>
+        <ul>
+        <li>
+        <p>Achieved 2.8x speedup over baseline attention implementations on A100 GPUs</p>
+        </li>
+        <li>
+        <p>Adopted by 3 major AI labs, 8,500+ GitHub stars, 200+ contributors</p>
+        </li>
+        </ul>
+        <h2><strong><a href="https://github.com/">NeuralPrune</a></strong></h2>
+        <p>Jan 2021</p>
+        <p>Automated neural network pruning toolkit with differentiable masks</p>
+        <ul>
+        <li>
+        <p>Reduced model size by 90% with less than 1% accuracy degradation on ImageNet</p>
+        </li>
+        <li>
+        <p>Featured in PyTorch ecosystem tools, 4,200+ GitHub stars</p>
+        </li>
+        </ul>
+        <h1>Publications</h1>
+        <h2><strong>Sparse Mixture-of-Experts at Scale: Efficient Routing for Trillion-Parameter Models</strong></h2>
+        <p>July 2023</p>
+        <p><em>John Doe</em>, Sarah Williams, David Park</p>
+        <p><a href="https://doi.org/10.1234/neurips.2023.1234">10.1234/neurips.2023.1234</a> (NeurIPS 2023)</p>
+        <h2><strong>Neural Architecture Search via Differentiable Pruning</strong></h2>
+        <p>Dec 2022</p>
+        <p>James Liu, <em>John Doe</em></p>
+        <p><a href="https://doi.org/10.1234/neurips.2022.5678">10.1234/neurips.2022.5678</a> (NeurIPS 2022, Spotlight)</p>
+        <h2><strong>Multi-Agent Reinforcement Learning with Emergent Communication</strong></h2>
+        <p>July 2022</p>
+        <p>Maria Garcia, <em>John Doe</em>, Tom Anderson</p>
+        <p><a href="https://doi.org/10.1234/icml.2022.9012">10.1234/icml.2022.9012</a> (ICML 2022)</p>
+        <h2><strong>On-Device Model Compression via Learned Quantization</strong></h2>
+        <p>May 2021</p>
+        <p><em>John Doe</em>, Kevin Wu</p>
+        <p><a href="https://doi.org/10.1234/iclr.2021.3456">10.1234/iclr.2021.3456</a> (ICLR 2021, Best Paper Award)</p>
+        <h1>Selected Honors</h1>
+        <ul>
+        <li>
+        <p>MIT Technology Review 35 Under 35 Innovators (2024)</p>
+        </li>
+        <li>
+        <p>Forbes 30 Under 30 in Enterprise Technology (2024)</p>
+        </li>
+        <li>
+        <p>ACM Doctoral Dissertation Award Honorable Mention (2023)</p>
+        </li>
+        <li>
+        <p>Google PhD Fellowship in Machine Learning (2020 – 2023)</p>
+        </li>
+        <li>
+        <p>Fulbright Scholarship for Graduate Studies (2018)</p>
+        </li>
+        </ul>
+        <h1>Skills</h1>
+        <p><strong>Languages:</strong> Python, C++, CUDA, Rust, Julia</p>
+        <p><strong>ML Frameworks:</strong> PyTorch, JAX, TensorFlow, Triton, ONNX</p>
+        <p><strong>Infrastructure:</strong> Kubernetes, Ray, distributed training, AWS, GCP</p>
+        <p><strong>Research Areas:</strong> Neural architecture search, model compression, efficient inference, multi-agent RL</p>
+        <h1>Patents</h1>
+        <ol>
+        <li>
+        <p>Adaptive Quantization for Neural Network Inference on Edge Devices (US Patent 11,234,567)</p>
+        </li>
+        <li>
+        <p>Dynamic Sparsity Patterns for Efficient Transformer Attention (US Patent 11,345,678)</p>
+        </li>
+        <li>
+        <p>Hardware-Aware Neural Architecture Search Method (US Patent 11,456,789)</p>
+        </li>
+        </ol>
+        <h1>Invited Talks</h1>
+        <ol>
+        <li>
+        <p>Scaling Laws for Efficient Inference — Stanford HAI Symposium (2024)</p>
+        </li>
+        <li>
+        <p>Building AI Infrastructure for the Next Decade — TechCrunch Disrupt (2024)</p>
+        </li>
+        <li>
+        <p>From Research to Production: Lessons in ML Systems — NeurIPS Workshop (2023)</p>
+        </li>
+        <li>
+        <p>Efficient Deep Learning: A Practitioner's Perspective — Google Tech Talk (2022)</p>
+        </li>
+        </ol>
+        <h1>Any Section Title</h1>
+        <p>You can use any section title you want.</p>
+        <p>You can choose any entry type for the section: <code>TextEntry</code>, <code>ExperienceEntry</code>, <code>EducationEntry</code>, <code>PublicationEntry</code>, <code>BulletEntry</code>, <code>NumberedEntry</code>, or <code>ReversedNumberedEntry</code>.</p>
+        <p>Markdown syntax is supported everywhere.</p>
+        <p>The <code>design</code> field in YAML gives you control over almost any aspect of your CV design.</p>
+        <p>See the <a href="https://docs.rendercv.com">documentation</a> for more details.</p>
+    </article>
+</body>
+
+</html>
\ No newline at end of file
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diff --git a/miti99.typ b/miti99.typ
new file mode 100644
index 0000000..e391b05
--- /dev/null
+++ b/miti99.typ
@@ -0,0 +1,407 @@
+// Import the rendercv function and all the refactored components
+#import "@preview/rendercv:0.1.0": *
+
+// Apply the rendercv template with custom configuration
+#show: rendercv.with(
+  name: "miti99",
+  footer: context { [#emph[miti99 -- #str(here().page())\/#str(counter(page).final().first())]] },
+  top-note: [ #emph[Last updated in Feb 2026] ],
+  locale-catalog-language: "en",
+  page-size: "us-letter",
+  page-top-margin: 0.7in,
+  page-bottom-margin: 0.7in,
+  page-left-margin: 0.7in,
+  page-right-margin: 0.7in,
+  page-show-footer: true,
+  page-show-top-note: true,
+  colors-body: rgb(0, 0, 0),
+  colors-name: rgb(0, 79, 144),
+  colors-headline: rgb(0, 79, 144),
+  colors-connections: rgb(0, 79, 144),
+  colors-section-titles: rgb(0, 79, 144),
+  colors-links: rgb(0, 79, 144),
+  colors-footer: rgb(128, 128, 128),
+  colors-top-note: rgb(128, 128, 128),
+  typography-line-spacing: 0.6em,
+  typography-alignment: "justified",
+  typography-date-and-location-column-alignment: right,
+  typography-font-family-body: "Source Sans 3",
+  typography-font-family-name: "Source Sans 3",
+  typography-font-family-headline: "Source Sans 3",
+  typography-font-family-connections: "Source Sans 3",
+  typography-font-family-section-titles: "Source Sans 3",
+  typography-font-size-body: 10pt,
+  typography-font-size-name: 30pt,
+  typography-font-size-headline: 10pt,
+  typography-font-size-connections: 10pt,
+  typography-font-size-section-titles: 1.4em,
+  typography-small-caps-name: false,
+  typography-small-caps-headline: false,
+  typography-small-caps-connections: false,
+  typography-small-caps-section-titles: false,
+  typography-bold-name: true,
+  typography-bold-headline: false,
+  typography-bold-connections: false,
+  typography-bold-section-titles: true,
+  links-underline: false,
+  links-show-external-link-icon: false,
+  header-alignment: center,
+  header-photo-width: 3.5cm,
+  header-space-below-name: 0.7cm,
+  header-space-below-headline: 0.7cm,
+  header-space-below-connections: 0.7cm,
+  header-connections-hyperlink: true,
+  header-connections-show-icons: true,
+  header-connections-display-urls-instead-of-usernames: false,
+  header-connections-separator: "",
+  header-connections-space-between-connections: 0.5cm,
+  section-titles-type: "with_partial_line",
+  section-titles-line-thickness: 0.5pt,
+  section-titles-space-above: 0.5cm,
+  section-titles-space-below: 0.3cm,
+  sections-allow-page-break: true,
+  sections-space-between-text-based-entries: 0.3em,
+  sections-space-between-regular-entries: 1.2em,
+  entries-date-and-location-width: 4.15cm,
+  entries-side-space: 0.2cm,
+  entries-space-between-columns: 0.1cm,
+  entries-allow-page-break: false,
+  entries-short-second-row: true,
+  entries-summary-space-left: 0cm,
+  entries-summary-space-above: 0cm,
+  entries-highlights-bullet:  "•" ,
+  entries-highlights-nested-bullet:  "•" ,
+  entries-highlights-space-left: 0.15cm,
+  entries-highlights-space-above: 0cm,
+  entries-highlights-space-between-items: 0cm,
+  entries-highlights-space-between-bullet-and-text: 0.5em,
+  date: datetime(
+    year: 2026,
+    month: 2,
+    day: 20,
+  ),
+)
+
+
+= miti99
+
+#connections(
+  [#connection-with-icon("location-dot")[San Francisco, CA]],
+  [#link("mailto:john.doe@email.com", icon: false, if-underline: false, if-color: false)[#connection-with-icon("envelope")[john.doe\@email.com]]],
+  [#link("https://rendercv.com/", icon: false, if-underline: false, if-color: false)[#connection-with-icon("link")[rendercv.com]]],
+  [#link("https://linkedin.com/in/rendercv", icon: false, if-underline: false, if-color: false)[#connection-with-icon("linkedin")[rendercv]]],
+  [#link("https://github.com/rendercv", icon: false, if-underline: false, if-color: false)[#connection-with-icon("github")[rendercv]]],
+)
+
+
+== Welcome to RenderCV
+
+RenderCV reads a CV written in a YAML file, and generates a PDF with professional typography.
+
+See the #link("https://docs.rendercv.com")[documentation] for more details.
+
+== Education
+
+#education-entry(
+  [
+    #strong[Princeton University], Computer Science
+
+    - Thesis: Efficient Neural Architecture Search for Resource-Constrained Deployment
+
+    - Advisor: Prof. Sanjeev Arora
+
+    - NSF Graduate Research Fellowship, Siebel Scholar (Class of 2022)
+
+  ],
+  [
+    Princeton, NJ
+
+    Sept 2018 – May 2023
+
+  ],
+  degree-column: [
+    #strong[PhD]
+  ],
+)
+
+#education-entry(
+  [
+    #strong[Boğaziçi University], Computer Engineering
+
+    - GPA: 3.97\/4.00, Valedictorian
+
+    - Fulbright Scholarship recipient for graduate studies
+
+  ],
+  [
+    Istanbul, Türkiye
+
+    Sept 2014 – June 2018
+
+  ],
+  degree-column: [
+    #strong[BS]
+  ],
+)
+
+== Experience
+
+#regular-entry(
+  [
+    #strong[Nexus AI], Co-Founder & CTO
+
+    - Built foundation model infrastructure serving 2M+ monthly API requests with 99.97\% uptime
+
+    - Raised \$18M Series A led by Sequoia Capital, with participation from a16z and Founders Fund
+
+    - Scaled engineering team from 3 to 28 across ML research, platform, and applied AI divisions
+
+    - Developed proprietary inference optimization reducing latency by 73\% compared to baseline
+
+  ],
+  [
+    San Francisco, CA
+
+    June 2023 – present
+
+    2 years 9 months
+
+  ],
+)
+
+#regular-entry(
+  [
+    #strong[NVIDIA Research], Research Intern
+
+    - Designed sparse attention mechanism reducing transformer memory footprint by 4.2x
+
+    - Co-authored paper accepted at NeurIPS 2022 (spotlight presentation, top 5\% of submissions)
+
+  ],
+  [
+    Santa Clara, CA
+
+    May 2022 – Aug 2022
+
+    4 months
+
+  ],
+)
+
+#regular-entry(
+  [
+    #strong[Google DeepMind], Research Intern
+
+    - Developed reinforcement learning algorithms for multi-agent coordination
+
+    - Published research at top-tier venues with significant academic impact
+
+      - ICML 2022 main conference paper, cited 340+ times within two years
+
+      - NeurIPS 2022 workshop paper on emergent communication protocols
+
+      - Invited journal extension in JMLR (2023)
+
+  ],
+  [
+    London, UK
+
+    May 2021 – Aug 2021
+
+    4 months
+
+  ],
+)
+
+#regular-entry(
+  [
+    #strong[Apple ML Research], Research Intern
+
+    - Created on-device neural network compression pipeline deployed across 50M+ devices
+
+    - Filed 2 patents on efficient model quantization techniques for edge inference
+
+  ],
+  [
+    Cupertino, CA
+
+    May 2020 – Aug 2020
+
+    4 months
+
+  ],
+)
+
+#regular-entry(
+  [
+    #strong[Microsoft Research], Research Intern
+
+    - Implemented novel self-supervised learning framework for low-resource language modeling
+
+    - Research integrated into Azure Cognitive Services, reducing training data requirements by 60\%
+
+  ],
+  [
+    Redmond, WA
+
+    May 2019 – Aug 2019
+
+    4 months
+
+  ],
+)
+
+== Projects
+
+#regular-entry(
+  [
+    #strong[#link("https://github.com/")[FlashInfer]]
+
+    #summary[Open-source library for high-performance LLM inference kernels]
+
+    - Achieved 2.8x speedup over baseline attention implementations on A100 GPUs
+
+    - Adopted by 3 major AI labs, 8,500+ GitHub stars, 200+ contributors
+
+  ],
+  [
+    Jan 2023 – present
+
+  ],
+)
+
+#regular-entry(
+  [
+    #strong[#link("https://github.com/")[NeuralPrune]]
+
+    #summary[Automated neural network pruning toolkit with differentiable masks]
+
+    - Reduced model size by 90\% with less than 1\% accuracy degradation on ImageNet
+
+    - Featured in PyTorch ecosystem tools, 4,200+ GitHub stars
+
+  ],
+  [
+    Jan 2021
+
+  ],
+)
+
+== Publications
+
+#regular-entry(
+  [
+    #strong[Sparse Mixture-of-Experts at Scale: Efficient Routing for Trillion-Parameter Models]
+
+    #emph[John Doe], Sarah Williams, David Park
+
+    #link("https://doi.org/10.1234/neurips.2023.1234")[10.1234\/neurips.2023.1234] (NeurIPS 2023)
+
+  ],
+  [
+    July 2023
+
+  ],
+)
+
+#regular-entry(
+  [
+    #strong[Neural Architecture Search via Differentiable Pruning]
+
+    James Liu, #emph[John Doe]
+
+    #link("https://doi.org/10.1234/neurips.2022.5678")[10.1234\/neurips.2022.5678] (NeurIPS 2022, Spotlight)
+
+  ],
+  [
+    Dec 2022
+
+  ],
+)
+
+#regular-entry(
+  [
+    #strong[Multi-Agent Reinforcement Learning with Emergent Communication]
+
+    Maria Garcia, #emph[John Doe], Tom Anderson
+
+    #link("https://doi.org/10.1234/icml.2022.9012")[10.1234\/icml.2022.9012] (ICML 2022)
+
+  ],
+  [
+    July 2022
+
+  ],
+)
+
+#regular-entry(
+  [
+    #strong[On-Device Model Compression via Learned Quantization]
+
+    #emph[John Doe], Kevin Wu
+
+    #link("https://doi.org/10.1234/iclr.2021.3456")[10.1234\/iclr.2021.3456] (ICLR 2021, Best Paper Award)
+
+  ],
+  [
+    May 2021
+
+  ],
+)
+
+== Selected Honors
+
+- MIT Technology Review 35 Under 35 Innovators (2024)
+
+- Forbes 30 Under 30 in Enterprise Technology (2024)
+
+- ACM Doctoral Dissertation Award Honorable Mention (2023)
+
+- Google PhD Fellowship in Machine Learning (2020 – 2023)
+
+- Fulbright Scholarship for Graduate Studies (2018)
+
+== Skills
+
+#strong[Languages:] Python, C++, CUDA, Rust, Julia
+
+#strong[ML Frameworks:] PyTorch, JAX, TensorFlow, Triton, ONNX
+
+#strong[Infrastructure:] Kubernetes, Ray, distributed training, AWS, GCP
+
+#strong[Research Areas:] Neural architecture search, model compression, efficient inference, multi-agent RL
+
+== Patents
+
++ Adaptive Quantization for Neural Network Inference on Edge Devices (US Patent 11,234,567)
+
++ Dynamic Sparsity Patterns for Efficient Transformer Attention (US Patent 11,345,678)
+
++ Hardware-Aware Neural Architecture Search Method (US Patent 11,456,789)
+
+== Invited Talks
+
+#reversed-numbered-entries(
+  [
+
++ Scaling Laws for Efficient Inference — Stanford HAI Symposium (2024)
+
++ Building AI Infrastructure for the Next Decade — TechCrunch Disrupt (2024)
+
++ From Research to Production: Lessons in ML Systems — NeurIPS Workshop (2023)
+
++ Efficient Deep Learning: A Practitioner's Perspective — Google Tech Talk (2022)
+  ],
+)
+
+== Any Section Title
+
+You can use any section title you want.
+
+You can choose any entry type for the section: `TextEntry`, `ExperienceEntry`, `EducationEntry`, `PublicationEntry`, `BulletEntry`, `NumberedEntry`, or `ReversedNumberedEntry`.
+
+Markdown syntax is supported everywhere.
+
+The `design` field in YAML gives you control over almost any aspect of your CV design.
+
+See the #link("https://docs.rendercv.com")[documentation] for more details.
diff --git a/miti99.yml b/miti99.yml
new file mode 100644
index 0000000..9142c5c
--- /dev/null
+++ b/miti99.yml
@@ -0,0 +1,368 @@
+# yaml-language-server: $schema=https://raw.githubusercontent.com/rendercv/rendercv/refs/tags/v2.6/schema.json
+cv:
+  name: miti99
+  headline:
+  location: San Francisco, CA
+  email: john.doe@email.com
+  photo:
+  phone:
+  website: https://rendercv.com/
+  social_networks:
+    - network: LinkedIn
+      username: rendercv
+    - network: GitHub
+      username: rendercv
+  custom_connections:
+  sections:
+    Welcome to RenderCV:
+      - RenderCV reads a CV written in a YAML file, and generates a PDF with professional typography.
+      - See the [documentation](https://docs.rendercv.com) for more details.
+    education:
+      - institution: Princeton University
+        area: Computer Science
+        degree: PhD
+        date:
+        start_date: 2018-09
+        end_date: 2023-05
+        location: Princeton, NJ
+        summary:
+        highlights:
+          - 'Thesis: Efficient Neural Architecture Search for Resource-Constrained Deployment'
+          - 'Advisor: Prof. Sanjeev Arora'
+          - NSF Graduate Research Fellowship, Siebel Scholar (Class of 2022)
+      - institution: Boğaziçi University
+        area: Computer Engineering
+        degree: BS
+        date:
+        start_date: 2014-09
+        end_date: 2018-06
+        location: Istanbul, Türkiye
+        summary:
+        highlights:
+          - 'GPA: 3.97/4.00, Valedictorian'
+          - Fulbright Scholarship recipient for graduate studies
+    experience:
+      - company: Nexus AI
+        position: Co-Founder & CTO
+        date:
+        start_date: 2023-06
+        end_date: present
+        location: San Francisco, CA
+        summary:
+        highlights:
+          - Built foundation model infrastructure serving 2M+ monthly API requests with 99.97% uptime
+          - Raised $18M Series A led by Sequoia Capital, with participation from a16z and Founders Fund
+          - Scaled engineering team from 3 to 28 across ML research, platform, and applied AI divisions
+          - Developed proprietary inference optimization reducing latency by 73% compared to baseline
+      - company: NVIDIA Research
+        position: Research Intern
+        date:
+        start_date: 2022-05
+        end_date: 2022-08
+        location: Santa Clara, CA
+        summary:
+        highlights:
+          - Designed sparse attention mechanism reducing transformer memory footprint by 4.2x
+          - Co-authored paper accepted at NeurIPS 2022 (spotlight presentation, top 5% of submissions)
+      - company: Google DeepMind
+        position: Research Intern
+        date:
+        start_date: 2021-05
+        end_date: 2021-08
+        location: London, UK
+        summary:
+        highlights:
+          - Developed reinforcement learning algorithms for multi-agent coordination
+          - Published research at top-tier venues with significant academic impact
+            - ICML 2022 main conference paper, cited 340+ times within two years
+            - NeurIPS 2022 workshop paper on emergent communication protocols
+            - Invited journal extension in JMLR (2023)
+      - company: Apple ML Research
+        position: Research Intern
+        date:
+        start_date: 2020-05
+        end_date: 2020-08
+        location: Cupertino, CA
+        summary:
+        highlights:
+          - Created on-device neural network compression pipeline deployed across 50M+ devices
+          - Filed 2 patents on efficient model quantization techniques for edge inference
+      - company: Microsoft Research
+        position: Research Intern
+        date:
+        start_date: 2019-05
+        end_date: 2019-08
+        location: Redmond, WA
+        summary:
+        highlights:
+          - Implemented novel self-supervised learning framework for low-resource language modeling
+          - Research integrated into Azure Cognitive Services, reducing training data requirements by 60%
+    projects:
+      - name: '[FlashInfer](https://github.com/)'
+        date:
+        start_date: 2023-01
+        end_date: present
+        location:
+        summary: Open-source library for high-performance LLM inference kernels
+        highlights:
+          - Achieved 2.8x speedup over baseline attention implementations on A100 GPUs
+          - Adopted by 3 major AI labs, 8,500+ GitHub stars, 200+ contributors
+      - name: '[NeuralPrune](https://github.com/)'
+        date: '2021'
+        start_date:
+        end_date:
+        location:
+        summary: Automated neural network pruning toolkit with differentiable masks
+        highlights:
+          - Reduced model size by 90% with less than 1% accuracy degradation on ImageNet
+          - Featured in PyTorch ecosystem tools, 4,200+ GitHub stars
+    publications:
+      - title: 'Sparse Mixture-of-Experts at Scale: Efficient Routing for Trillion-Parameter Models'
+        authors:
+          - '*John Doe*'
+          - Sarah Williams
+          - David Park
+        summary:
+        doi: 10.1234/neurips.2023.1234
+        url:
+        journal: NeurIPS 2023
+        date: 2023-07
+      - title: Neural Architecture Search via Differentiable Pruning
+        authors:
+          - James Liu
+          - '*John Doe*'
+        summary:
+        doi: 10.1234/neurips.2022.5678
+        url:
+        journal: NeurIPS 2022, Spotlight
+        date: 2022-12
+      - title: Multi-Agent Reinforcement Learning with Emergent Communication
+        authors:
+          - Maria Garcia
+          - '*John Doe*'
+          - Tom Anderson
+        summary:
+        doi: 10.1234/icml.2022.9012
+        url:
+        journal: ICML 2022
+        date: 2022-07
+      - title: On-Device Model Compression via Learned Quantization
+        authors:
+          - '*John Doe*'
+          - Kevin Wu
+        summary:
+        doi: 10.1234/iclr.2021.3456
+        url:
+        journal: ICLR 2021, Best Paper Award
+        date: 2021-05
+    selected_honors:
+      - bullet: MIT Technology Review 35 Under 35 Innovators (2024)
+      - bullet: Forbes 30 Under 30 in Enterprise Technology (2024)
+      - bullet: ACM Doctoral Dissertation Award Honorable Mention (2023)
+      - bullet: Google PhD Fellowship in Machine Learning (2020 – 2023)
+      - bullet: Fulbright Scholarship for Graduate Studies (2018)
+    skills:
+      - label: Languages
+        details: Python, C++, CUDA, Rust, Julia
+      - label: ML Frameworks
+        details: PyTorch, JAX, TensorFlow, Triton, ONNX
+      - label: Infrastructure
+        details: Kubernetes, Ray, distributed training, AWS, GCP
+      - label: Research Areas
+        details: Neural architecture search, model compression, efficient inference, multi-agent RL
+    patents:
+      - number: Adaptive Quantization for Neural Network Inference on Edge Devices (US Patent 11,234,567)
+      - number: Dynamic Sparsity Patterns for Efficient Transformer Attention (US Patent 11,345,678)
+      - number: Hardware-Aware Neural Architecture Search Method (US Patent 11,456,789)
+    invited_talks:
+      - reversed_number: Scaling Laws for Efficient Inference — Stanford HAI Symposium (2024)
+      - reversed_number: Building AI Infrastructure for the Next Decade — TechCrunch Disrupt (2024)
+      - reversed_number: 'From Research to Production: Lessons in ML Systems — NeurIPS Workshop (2023)'
+      - reversed_number: "Efficient Deep Learning: A Practitioner's Perspective — Google Tech Talk (2022)"
+    any_section_title:
+      - You can use any section title you want.
+      - 'You can choose any entry type for the section: `TextEntry`, `ExperienceEntry`, `EducationEntry`, `PublicationEntry`, `BulletEntry`, `NumberedEntry`, or `ReversedNumberedEntry`.'
+      - Markdown syntax is supported everywhere.
+      - The `design` field in YAML gives you control over almost any aspect of your CV design.
+      - See the [documentation](https://docs.rendercv.com) for more details.
+design:
+  theme: classic
+  # page:
+  #   size: us-letter
+  #   top_margin: 0.7in
+  #   bottom_margin: 0.7in
+  #   left_margin: 0.7in
+  #   right_margin: 0.7in
+  #   show_footer: true
+  #   show_top_note: true
+  # colors:
+  #   body: rgb(0, 0, 0)
+  #   name: rgb(0, 79, 144)
+  #   headline: rgb(0, 79, 144)
+  #   connections: rgb(0, 79, 144)
+  #   section_titles: rgb(0, 79, 144)
+  #   links: rgb(0, 79, 144)
+  #   footer: rgb(128, 128, 128)
+  #   top_note: rgb(128, 128, 128)
+  # typography:
+  #   line_spacing: 0.6em
+  #   alignment: justified
+  #   date_and_location_column_alignment: right
+  #   font_family:
+  #     body: Source Sans 3
+  #     name: Source Sans 3
+  #     headline: Source Sans 3
+  #     connections: Source Sans 3
+  #     section_titles: Source Sans 3
+  #   font_size:
+  #     body: 10pt
+  #     name: 30pt
+  #     headline: 10pt
+  #     connections: 10pt
+  #     section_titles: 1.4em
+  #   small_caps:
+  #     name: false
+  #     headline: false
+  #     connections: false
+  #     section_titles: false
+  #   bold:
+  #     name: true
+  #     headline: false
+  #     connections: false
+  #     section_titles: true
+  # links:
+  #   underline: false
+  #   show_external_link_icon: false
+  # header:
+  #   alignment: center
+  #   photo_width: 3.5cm
+  #   photo_position: left
+  #   photo_space_left: 0.4cm
+  #   photo_space_right: 0.4cm
+  #   space_below_name: 0.7cm
+  #   space_below_headline: 0.7cm
+  #   space_below_connections: 0.7cm
+  #   connections:
+  #     phone_number_format: national
+  #     hyperlink: true
+  #     show_icons: true
+  #     display_urls_instead_of_usernames: false
+  #     separator: ''
+  #     space_between_connections: 0.5cm
+  # section_titles:
+  #   type: with_partial_line
+  #   line_thickness: 0.5pt
+  #   space_above: 0.5cm
+  #   space_below: 0.3cm
+  # sections:
+  #   allow_page_break: true
+  #   space_between_regular_entries: 1.2em
+  #   space_between_text_based_entries: 0.3em
+  #   show_time_spans_in:
+  #     - experience
+  # entries:
+  #   date_and_location_width: 4.15cm
+  #   side_space: 0.2cm
+  #   space_between_columns: 0.1cm
+  #   allow_page_break: false
+  #   short_second_row: true
+  #   summary:
+  #     space_above: 0cm
+  #     space_left: 0cm
+  #   highlights:
+  #     bullet: •
+  #     nested_bullet: •
+  #     space_left: 0.15cm
+  #     space_above: 0cm
+  #     space_between_items: 0cm
+  #     space_between_bullet_and_text: 0.5em
+  # templates:
+  #   footer: '*NAME -- PAGE_NUMBER/TOTAL_PAGES*'
+  #   top_note: '*LAST_UPDATED CURRENT_DATE*'
+  #   single_date: MONTH_ABBREVIATION YEAR
+  #   date_range: START_DATE – END_DATE
+  #   time_span: HOW_MANY_YEARS YEARS HOW_MANY_MONTHS MONTHS
+  #   one_line_entry:
+  #     main_column: '**LABEL:** DETAILS'
+  #   education_entry:
+  #     main_column: |-
+  #       **INSTITUTION**, AREA
+  #       SUMMARY
+  #       HIGHLIGHTS
+  #     degree_column: '**DEGREE**'
+  #     date_and_location_column: |-
+  #       LOCATION
+  #       DATE
+  #   normal_entry:
+  #     main_column: |-
+  #       **NAME**
+  #       SUMMARY
+  #       HIGHLIGHTS
+  #     date_and_location_column: |-
+  #       LOCATION
+  #       DATE
+  #   experience_entry:
+  #     main_column: |-
+  #       **COMPANY**, POSITION
+  #       SUMMARY
+  #       HIGHLIGHTS
+  #     date_and_location_column: |-
+  #       LOCATION
+  #       DATE
+  #   publication_entry:
+  #     main_column: |-
+  #       **TITLE**
+  #       SUMMARY
+  #       AUTHORS
+  #       URL (JOURNAL)
+  #     date_and_location_column: DATE
+locale:
+  language: english
+  # last_updated: Last updated in
+  # month: month
+  # months: months
+  # year: year
+  # years: years
+  # present: present
+  # month_abbreviations:
+  #   - Jan
+  #   - Feb
+  #   - Mar
+  #   - Apr
+  #   - May
+  #   - June
+  #   - July
+  #   - Aug
+  #   - Sept
+  #   - Oct
+  #   - Nov
+  #   - Dec
+  # month_names:
+  #   - January
+  #   - February
+  #   - March
+  #   - April
+  #   - May
+  #   - June
+  #   - July
+  #   - August
+  #   - September
+  #   - October
+  #   - November
+  #   - December
+settings:
+  current_date: '2026-02-20'
+  render_command:
+    design:
+    locale:
+    typst_path: NAME_IN_SNAKE_CASE.typ
+    pdf_path: NAME_IN_SNAKE_CASE.pdf
+    markdown_path: README.md
+    html_path: index.html
+    png_path: NAME_IN_SNAKE_CASE.png
+    dont_generate_markdown: false
+    dont_generate_html: false
+    dont_generate_typst: false
+    dont_generate_pdf: false
+    dont_generate_png: false
+  bold_keywords: []
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