mirror of
https://github.com/tiennm99/cv.git
synced 2026-09-04 08:19:25 +00:00
Condense CV headings and regenerate PDF
Simplify and unify CV formatting: collapse multi-line education and experience blocks into single-line headings in README.md and index.html (e.g. institution/degree/location/date and "Role, Company -- Location"), and remove redundant duration/location paragraphs. Add new typography file (miti99.typ) and update miti99.yml. Regenerate/update miti99.pdf to reflect the structural/obj reference changes in the PDF (updated structure tree and page object references).
This commit is contained in:
@@ -13,13 +13,7 @@ RenderCV reads a CV written in a YAML file, and generates a PDF with professiona
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See the [documentation](https://docs.rendercv.com) for more details.
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# Education
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## **Princeton University**, Computer Science
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**PhD**
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Princeton, NJ
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Sept 2018 – May 2023
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## **Princeton University**, PhD in Computer Science -- Princeton, NJSept 2018 – May 2023
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- Thesis: Efficient Neural Architecture Search for Resource-Constrained Deployment
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@@ -29,13 +23,7 @@ Sept 2018 – May 2023
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## **Boğaziçi University**, Computer Engineering
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**BS**
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Istanbul, Türkiye
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Sept 2014 – June 2018
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## **Boğaziçi University**, BS in Computer Engineering -- Istanbul, TürkiyeSept 2014 – June 2018
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- GPA: 3.97/4.00, Valedictorian
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@@ -44,16 +32,10 @@ Sept 2014 – June 2018
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# Experience
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## **Nexus AI**, Co-Founder & CTO
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San Francisco, CA
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## **Co-Founder & CTO**, Nexus AI -- San Francisco, CA
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June 2023 – present
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2 years 9 months
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- Built foundation model infrastructure serving 2M+ monthly API requests with 99.97% uptime
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- Raised $18M Series A led by Sequoia Capital, with participation from a16z and Founders Fund
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@@ -64,32 +46,20 @@ June 2023 – present
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## **NVIDIA Research**, Research Intern
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Santa Clara, CA
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## **Research Intern**, NVIDIA Research -- Santa Clara, CA
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May 2022 – Aug 2022
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4 months
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- Designed sparse attention mechanism reducing transformer memory footprint by 4.2x
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- Co-authored paper accepted at NeurIPS 2022 (spotlight presentation, top 5% of submissions)
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## **Google DeepMind**, Research Intern
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London, UK
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## **Research Intern**, Google DeepMind -- London, UK
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May 2021 – Aug 2021
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4 months
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- Developed reinforcement learning algorithms for multi-agent coordination
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- Published research at top-tier venues with significant academic impact
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@@ -102,32 +72,20 @@ May 2021 – Aug 2021
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## **Apple ML Research**, Research Intern
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Cupertino, CA
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## **Research Intern**, Apple ML Research -- Cupertino, CA
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May 2020 – Aug 2020
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4 months
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- Created on-device neural network compression pipeline deployed across 50M+ devices
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- Filed 2 patents on efficient model quantization techniques for edge inference
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## **Microsoft Research**, Research Intern
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Redmond, WA
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## **Research Intern**, Microsoft Research -- Redmond, WA
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May 2019 – Aug 2019
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4 months
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- Implemented novel self-supervised learning framework for low-resource language modeling
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- Research integrated into Azure Cognitive Services, reducing training data requirements by 60%
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+7
-23
@@ -51,10 +51,7 @@
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<p>RenderCV reads a CV written in a YAML file, and generates a PDF with professional typography.</p>
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<p>See the <a href="https://docs.rendercv.com">documentation</a> for more details.</p>
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<h1>Education</h1>
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<h2><strong>Princeton University</strong>, Computer Science</h2>
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<p><strong>PhD</strong></p>
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<p>Princeton, NJ</p>
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<p>Sept 2018 – May 2023</p>
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<h2><strong>Princeton University</strong>, PhD in Computer Science -- Princeton, NJSept 2018 – May 2023</h2>
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<ul>
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<li>
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<p>Thesis: Efficient Neural Architecture Search for Resource-Constrained Deployment</p>
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@@ -66,10 +63,7 @@
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<p>NSF Graduate Research Fellowship, Siebel Scholar (Class of 2022)</p>
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</li>
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</ul>
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<h2><strong>Boğaziçi University</strong>, Computer Engineering</h2>
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<p><strong>BS</strong></p>
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<p>Istanbul, Türkiye</p>
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<p>Sept 2014 – June 2018</p>
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<h2><strong>Boğaziçi University</strong>, BS in Computer Engineering -- Istanbul, TürkiyeSept 2014 – June 2018</h2>
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<ul>
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<li>
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<p>GPA: 3.97/4.00, Valedictorian</p>
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@@ -79,10 +73,8 @@
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</li>
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</ul>
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<h1>Experience</h1>
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<h2><strong>Nexus AI</strong>, Co-Founder & CTO</h2>
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<p>San Francisco, CA</p>
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<h2><strong>Co-Founder & CTO</strong>, Nexus AI -- San Francisco, CA</h2>
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<p>June 2023 – present</p>
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<p>2 years 9 months</p>
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<ul>
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<li>
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<p>Built foundation model infrastructure serving 2M+ monthly API requests with 99.97% uptime</p>
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@@ -97,10 +89,8 @@
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<p>Developed proprietary inference optimization reducing latency by 73% compared to baseline</p>
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</li>
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</ul>
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<h2><strong>NVIDIA Research</strong>, Research Intern</h2>
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<p>Santa Clara, CA</p>
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<h2><strong>Research Intern</strong>, NVIDIA Research -- Santa Clara, CA</h2>
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<p>May 2022 – Aug 2022</p>
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<p>4 months</p>
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<ul>
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<li>
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<p>Designed sparse attention mechanism reducing transformer memory footprint by 4.2x</p>
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@@ -109,10 +99,8 @@
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<p>Co-authored paper accepted at NeurIPS 2022 (spotlight presentation, top 5% of submissions)</p>
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</li>
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</ul>
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<h2><strong>Google DeepMind</strong>, Research Intern</h2>
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<p>London, UK</p>
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<h2><strong>Research Intern</strong>, Google DeepMind -- London, UK</h2>
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<p>May 2021 – Aug 2021</p>
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<p>4 months</p>
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<ul>
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<li>
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<p>Developed reinforcement learning algorithms for multi-agent coordination</p>
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@@ -130,10 +118,8 @@
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<p>Invited journal extension in JMLR (2023)</p>
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</li>
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</ul>
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<h2><strong>Apple ML Research</strong>, Research Intern</h2>
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<p>Cupertino, CA</p>
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<h2><strong>Research Intern</strong>, Apple ML Research -- Cupertino, CA</h2>
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<p>May 2020 – Aug 2020</p>
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<p>4 months</p>
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<ul>
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<li>
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<p>Created on-device neural network compression pipeline deployed across 50M+ devices</p>
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@@ -142,10 +128,8 @@
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<p>Filed 2 patents on efficient model quantization techniques for edge inference</p>
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</li>
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</ul>
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<h2><strong>Microsoft Research</strong>, Research Intern</h2>
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<p>Redmond, WA</p>
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<h2><strong>Research Intern</strong>, Microsoft Research -- Redmond, WA</h2>
|
||||
<p>May 2019 – Aug 2019</p>
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<p>4 months</p>
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<ul>
|
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<li>
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<p>Implemented novel self-supervised learning framework for low-resource language modeling</p>
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+2069
-2156
File diff suppressed because it is too large
Load Diff
+403
@@ -0,0 +1,403 @@
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// Import the rendercv function and all the refactored components
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#import "@preview/rendercv:0.1.0": *
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// Apply the rendercv template with custom configuration
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#show: rendercv.with(
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name: "miti99",
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footer: context { [#emph[miti99 -- #str(here().page())\/#str(counter(page).final().first())]] },
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top-note: [ #emph[Last updated in Feb 2026] ],
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locale-catalog-language: "en",
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page-size: "us-letter",
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page-top-margin: 0.7in,
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page-bottom-margin: 0.7in,
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page-left-margin: 0.7in,
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page-right-margin: 0.7in,
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page-show-footer: true,
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page-show-top-note: true,
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colors-body: rgb(0, 0, 0),
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colors-name: rgb(0, 79, 144),
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colors-headline: rgb(0, 79, 144),
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colors-connections: rgb(0, 79, 144),
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colors-section-titles: rgb(0, 79, 144),
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colors-links: rgb(0, 79, 144),
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colors-footer: rgb(128, 128, 128),
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colors-top-note: rgb(128, 128, 128),
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typography-line-spacing: 0.6em,
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typography-alignment: "justified",
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typography-date-and-location-column-alignment: right,
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typography-font-family-body: "Raleway",
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typography-font-family-name: "Raleway",
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typography-font-family-headline: "Raleway",
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typography-font-family-connections: "Raleway",
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typography-font-family-section-titles: "Raleway",
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typography-font-size-body: 10pt,
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typography-font-size-name: 30pt,
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typography-font-size-headline: 10pt,
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typography-font-size-connections: 10pt,
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typography-font-size-section-titles: 1.4em,
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typography-small-caps-name: false,
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typography-small-caps-headline: false,
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typography-small-caps-connections: false,
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typography-small-caps-section-titles: false,
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typography-bold-name: false,
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typography-bold-headline: false,
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typography-bold-connections: false,
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typography-bold-section-titles: false,
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links-underline: false,
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links-show-external-link-icon: false,
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header-alignment: left,
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header-photo-width: 3.5cm,
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header-space-below-name: 0.7cm,
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header-space-below-headline: 0.7cm,
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header-space-below-connections: 0.7cm,
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header-connections-hyperlink: true,
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header-connections-show-icons: true,
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header-connections-display-urls-instead-of-usernames: false,
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header-connections-separator: "",
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header-connections-space-between-connections: 0.5cm,
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section-titles-type: "with_full_line",
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section-titles-line-thickness: 0.5pt,
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section-titles-space-above: 0.5cm,
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section-titles-space-below: 0.3cm,
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sections-allow-page-break: true,
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sections-space-between-text-based-entries: 0.3em,
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sections-space-between-regular-entries: 1.2em,
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entries-date-and-location-width: 4.15cm,
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entries-side-space: 0.2cm,
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entries-space-between-columns: 0.1cm,
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entries-allow-page-break: false,
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entries-short-second-row: false,
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entries-summary-space-left: 0cm,
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entries-summary-space-above: 0.12cm,
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entries-highlights-bullet: "•" ,
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entries-highlights-nested-bullet: "•" ,
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entries-highlights-space-left: 0cm,
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||||
entries-highlights-space-above: 0.12cm,
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entries-highlights-space-between-items: 0.12cm,
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entries-highlights-space-between-bullet-and-text: 0.5em,
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date: datetime(
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year: 2026,
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month: 2,
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day: 20,
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),
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)
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= miti99
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|
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#connections(
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[#connection-with-icon("location-dot")[San Francisco, CA]],
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[#link("mailto:john.doe@email.com", icon: false, if-underline: false, if-color: false)[#connection-with-icon("envelope")[john.doe\@email.com]]],
|
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[#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
|
||||
|
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#education-entry(
|
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[
|
||||
#strong[Princeton University], PhD in Computer Science -- Princeton, NJ
|
||||
|
||||
],
|
||||
[
|
||||
Sept 2018 – May 2023
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
- Thesis: Efficient Neural Architecture Search for Resource-Constrained Deployment
|
||||
|
||||
- Advisor: Prof. Sanjeev Arora
|
||||
|
||||
- NSF Graduate Research Fellowship, Siebel Scholar (Class of 2022)
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
#education-entry(
|
||||
[
|
||||
#strong[Boğaziçi University], BS in Computer Engineering -- Istanbul, Türkiye
|
||||
|
||||
],
|
||||
[
|
||||
Sept 2014 – June 2018
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
- GPA: 3.97\/4.00, Valedictorian
|
||||
|
||||
- Fulbright Scholarship recipient for graduate studies
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
== Experience
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[Co-Founder & CTO], Nexus AI -- San Francisco, CA
|
||||
|
||||
],
|
||||
[
|
||||
June 2023 – present
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
- 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
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[Research Intern], NVIDIA Research -- Santa Clara, CA
|
||||
|
||||
],
|
||||
[
|
||||
May 2022 – Aug 2022
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
- Designed sparse attention mechanism reducing transformer memory footprint by 4.2x
|
||||
|
||||
- Co-authored paper accepted at NeurIPS 2022 (spotlight presentation, top 5\% of submissions)
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[Research Intern], Google DeepMind -- London, UK
|
||||
|
||||
],
|
||||
[
|
||||
May 2021 – Aug 2021
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
- 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)
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[Research Intern], Apple ML Research -- Cupertino, CA
|
||||
|
||||
],
|
||||
[
|
||||
May 2020 – Aug 2020
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
- Created on-device neural network compression pipeline deployed across 50M+ devices
|
||||
|
||||
- Filed 2 patents on efficient model quantization techniques for edge inference
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[Research Intern], Microsoft Research -- Redmond, WA
|
||||
|
||||
],
|
||||
[
|
||||
May 2019 – Aug 2019
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
- Implemented novel self-supervised learning framework for low-resource language modeling
|
||||
|
||||
- Research integrated into Azure Cognitive Services, reducing training data requirements by 60\%
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
== Projects
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[#link("https://github.com/")[FlashInfer]]
|
||||
|
||||
],
|
||||
[
|
||||
Jan 2023 – present
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
#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
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[#link("https://github.com/")[NeuralPrune]]
|
||||
|
||||
],
|
||||
[
|
||||
Jan 2021
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
#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
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
== Publications
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[Sparse Mixture-of-Experts at Scale: Efficient Routing for Trillion-Parameter Models]
|
||||
|
||||
],
|
||||
[
|
||||
July 2023
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
#emph[John Doe], Sarah Williams, David Park
|
||||
|
||||
#link("https://doi.org/10.1234/neurips.2023.1234")[10.1234\/neurips.2023.1234] (NeurIPS 2023)
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[Neural Architecture Search via Differentiable Pruning]
|
||||
|
||||
],
|
||||
[
|
||||
Dec 2022
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
James Liu, #emph[John Doe]
|
||||
|
||||
#link("https://doi.org/10.1234/neurips.2022.5678")[10.1234\/neurips.2022.5678] (NeurIPS 2022, Spotlight)
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[Multi-Agent Reinforcement Learning with Emergent Communication]
|
||||
|
||||
],
|
||||
[
|
||||
July 2022
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
Maria Garcia, #emph[John Doe], Tom Anderson
|
||||
|
||||
#link("https://doi.org/10.1234/icml.2022.9012")[10.1234\/icml.2022.9012] (ICML 2022)
|
||||
|
||||
],
|
||||
)
|
||||
|
||||
#regular-entry(
|
||||
[
|
||||
#strong[On-Device Model Compression via Learned Quantization]
|
||||
|
||||
],
|
||||
[
|
||||
May 2021
|
||||
|
||||
],
|
||||
main-column-second-row: [
|
||||
#emph[John Doe], Kevin Wu
|
||||
|
||||
#link("https://doi.org/10.1234/iclr.2021.3456")[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
|
||||
|
||||
#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.
|
||||
+5
-5
@@ -186,7 +186,7 @@ cv:
|
||||
- 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
|
||||
theme: engineeringclassic
|
||||
# page:
|
||||
# size: us-letter
|
||||
# top_margin: 0.7in
|
||||
@@ -355,14 +355,14 @@ settings:
|
||||
render_command:
|
||||
design:
|
||||
locale:
|
||||
typst_path: NAME_IN_SNAKE_CASE.typ
|
||||
pdf_path: NAME_IN_SNAKE_CASE.pdf
|
||||
typst_path: miti99.typ
|
||||
pdf_path: miti99.pdf
|
||||
markdown_path: README.md
|
||||
html_path: index.html
|
||||
png_path: NAME_IN_SNAKE_CASE.png
|
||||
png_path: miti99.png
|
||||
dont_generate_markdown: false
|
||||
dont_generate_html: false
|
||||
dont_generate_typst: true
|
||||
dont_generate_typst: false
|
||||
dont_generate_pdf: false
|
||||
dont_generate_png: true
|
||||
bold_keywords: []
|
||||
|
||||
Reference in New Issue
Block a user