1. Specialized in developing data-driven solutions for real-time movement analysis in wearable technology.2. Integrated EMG and IMU sensors, applying advanced signal processing and creating predictive models for biomechanical applications with and without haptic feedback.3. Improved accuracy of ground reaction force predictions, contributing to advancements in wearable technology for performance and health monitoring.4. Interacted with customers and team on GitHub, addressing bugs, gathering feedback, and resolving issues.5. Created a C++ SDK with a Python interface for Bluetooth/WiFi-enabled EEG devices, along with a real- time data visualization GUI using PyQt5 and Lab Streaming Layer (pylsl).

1. Managed data annotation for NLP tasks including intent recognition, speech-to-text, and text summarization, enabling high-quality training datasets for predictive models.2. Data mining using web crawling for LLM datasets for State-of-the-art TTS and LLM models