chore: init

README.md

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-# 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.