🌟 About Me
I'm a Master's student in Electrical and Computer Engineering at Johns Hopkins University with a passion for leveraging Machine Learning and Embedded Systems to solve real-world problems, particularly in healthcare and medical devices. My journey in technology is fueled by curiosity and a drive to create impactful solutions.

💻 Technical Skills

• Programming: Python, C++, C, JavaScript (Node.js, React.js), HTML, CSS
• Machine Learning: Signal Processing, TensorFlow, PyTorch, Wav2Vec, MetricGAN+
• Embedded Systems: Verilog, Embedded C, Arduino, ESP32
• Data Communication: Wireless Protocols, MQTT
• Databases: MongoDB
• Tools: MATLAB, Git, Docker

📂 Highlighted Projects

1. COPD Detection System

   • Developed a machine learning model for non-invasive COPD detection using respiratory sounds.
   • Integrated MEMS microphones for data collection and built a scalable diagnostic solution.

2. Emotion Recognition in Noisy Environments

   • Created a robust framework for speech emotion recognition under noisy conditions.
   • Employed MetricGAN+ and Wav2Vec2 for signal denoising and feature extraction.

3. Surgical Navigation Algorithms

   • Implemented calibration, distortion correction, and point cloud registration algorithms for a stereotactic navigation system.
   • Enhanced accuracy of 3D transformations for real-time surgical applications.

4. Marine VHF Scanner

   • Designed a software-defined radio-based marine VHF scanner using Embedded C and signal processing techniques.

🚀 Current Focus

• Deepening my expertise in Machine Learning for Signal Processing and Medical Applications.
• Exploring advanced frameworks like TensorFlow, PyTorch, and multimodal ML models.
• Actively contributing to open-source projects and building a portfolio showcasing innovation in healthcare technology.

📫 Let's Connect!

• LinkedIn: linkedin.com/in/Harshith
• Email: [email protected]