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Achievement: YOLOAchievement: Pull Shark

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Achievement: YOLOAchievement: Pull Shark

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Josh396s/README.md

Hi there, I'm Josh! 👋

I'm a Machine Learning Engineer and recent UC San Diego MSCS grad (class of '25). I'm passionate about building intelligent systems, working with data, and solving complex problems through AI.

🚀 What I'm working on

  • Email.ing: An intelligent email management system designed to streamline communication.
  • Refining my skills in Large Language Models (LLMs) and Data Science workflows.
  • Exploring new ways to bridge the gap between research and production-ready AI.

🛠️ Technical Toolkit

  • Languages: Python, C/C++, SQL, GoLang, HTML/CSS, JavaScript
  • AI/ML: PyTorch, TensorFlow, Scikit-learn, Hugging Face, LLMs
  • Tools: Git, Docker, AWS, Google Cloud, Linux

📊 My Stats

Josh's GitHub stats Top Langs

🏃 Beyond the Code

When I'm not training models or debugging code, you can find me:

  • 🏋️‍♂️ At the gym
  • 🥾 Going for a run
  • 🎧 Listening to The Weeknd
  • 🏀 Suffering watching the LA Clippers

📫 Let's Connect!

"The best way to predict the future is to invent it."

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  1. email.ing email.ing Public

    A privacy-first, intelligent email management system. Utilizes a hybrid AI architecture with local Llama models for secure classification and Google Gemini for context-aware summarization and draft…

    Python 1

  2. Semantic_Segmentation_Research Semantic_Segmentation_Research Public

    Research implementation of advanced computer vision techniques including Semantic and Panoptic Segmentation. Explores architectures like Mask2Former and SAM (Segment Anything Model) with a focus on…

    Jupyter Notebook 1

  3. Post-Gen-AI Post-Gen-AI Public

    An AI-driven content generation tool utilizing Natural Language Generation (NLG) to automate social media copy. Optimized for engagement through fine-tuned transformer models and promotional analysis.

    Python 1

  4. BERT-Contrastive-LoRA BERT-Contrastive-LoRA Public

    Optimizing BERT for intent classification on the Amazon Massive dataset using Supervised Contrastive Learning (SupCon), LoRA, and Layer-wise Learning Rate Decay. Achieved a 1.2% F1-score improvement.

    Python 1