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Achievement: Pull SharkAchievement: YOLO

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Achievement: Pull SharkAchievement: YOLO

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Sree-Gudapati/README.md

Hi there, I'm Sree Satya Jayanth Gudapati 👋

I am a Computer Science student at UC Santa Cruz (Class of 2027/2028), passionate about machine learning, mechanistic interpretability, and building cloud infrastructure.

🔭 What I'm Working On

  • AI Research: Investigating propositional logic operators and mechanistic interpretability at the UCSC Neuron Explanations Lab.
  • RAG Architectures: Developing a localized RAG research tool utilizing LangChain, ChromaDB, and tree-sitter for structural mapping.
  • LLM Orchestration: Building an LLM-Delegator to dynamically route prompts across different provider APIs based on intent and complexity.
  • Personal Agent Harness Building a harness where a parent LLM orchestrates cheap local mini-agents for coding tasks to minimize API token costs.
  • Sensor Context Encoders: Building a 1D-CNN pipeline to map raw smartphone sensor data directly into the continuous embedding space of a frozen LLM for activity recognition.

💻 Tech Stack

  • Languages: Python, TypeScript, C/C++, Haskell, GraphQL/MySQL
  • AI & Data: PyTorch, Hugging Face, Scikit-Learn, LangChain, Multimodal RAG, Ollama, Vision-Language Models (VLMs), Model Interpretability, Prompt Engineering, Pandas
  • Cloud & Infrastructure: AWS (Amplify, AppSync), Docker, Kubernetes, Self-hosted servers (iMac)
  • Systems & OS: Linux, MacOS, Windows

Pinned Loading

  1. Research_RAG_Pipeline Research_RAG_Pipeline Public

    Python

  2. Personalized-Fitness-Assistant Personalized-Fitness-Assistant Public

    TypeScript

  3. Gemini_Harness Gemini_Harness Public

    Gemini API based harness built from scratch.

    Python

  4. Sensor-Context-Encoder-Challenge Sensor-Context-Encoder-Challenge Public

    Building a 1D-CNN pipeline to map raw smartphone sensor data directly into the continuous embedding space of a frozen LLM for activity recognition.

    Python