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kkrish-tech/README.md

👋 Hi! I'm Karthi!

🎓 M.Eng. in Computer Science @ Virginia Tech
🤖 AI & Software Engineer

🧭 About Me

I build software at the intersection of machine learning, backend systems, and hardware.

Mainly, I focus on:

  • Computer Vision: Real-time object detection and tracking on edge devices
  • LLM Applications: Asynchronous document parsing and data extraction pipelines
  • Backend Infrastructure: APIs and software tools that keep models running fast

🚀 Key Projects & Experience

🛸 Real-Time Drone Detection System
Built a real-time tracking system for a camera gimbal using YOLO models, OpenCV, and a Hailo AI accelerator on a Raspberry Pi 5. Collaborated with Virginia Tech and the U.S. Secret Service.

🧠 Document Intelligence Tool (FedScale Inc)
Built an automated document parsing tool using Azure OpenAI, OCR parsers, and Flask to handle complex multi-format files and speed up internal review.

🏥 Medical Image Classifier
Developed deep learning vision models in PyTorch to classify medical imaging assets for diagnostic workflows.

🛠️ Tech Stack

  • Languages: Python, C++, SQL, JavaScript
  • AI / Vision: PyTorch, OpenCV, YOLO, Azure OpenAI, Tesseract OCR
  • Backend / Web: Flask, REST APIs, Asynchronous Tasks
  • Hardware: Raspberry Pi, Hailo-10 AI Accelerator

📫 Contact

📧 Email: karthikrish2002@outlook.com
🔗 LinkedIn: linkedin.com/in/kkrishn-tech

Pinned Loading

  1. drone-detection-tracking-system drone-detection-tracking-system Public

    Real-time AI system for detecting and tracking aerial objects using computer vision, edge AI acceleration, and live camera control for autonomous monitoring.

    Python

  2. low-resource-language-reasoning low-resource-language-reasoning Public

    Evaluation framework for measuring LLM reasoning and translation performance across low-resource languages using glossary-guided prompting and semantic similarity metrics.

    Python

  3. semi-supervised-medical-imaging-classifier semi-supervised-medical-imaging-classifier Public

    Chest X-ray classification system that shows how using unlabeled medical images alongside labeled data can improve diagnostic accuracy for COVID-19 and pneumonia detection.

    Python